Статті в журналах: "3D brain imaging"

1

Sumithra, M., P. Madhumitha, S. Madhumitha, D. Malini, and B. Poorni Vinayaa. "3D Segmentation of Brain Tumor Imaging." International Journal of Advanced Engineering, Management and Science 6, no. 6 (2020): 256–60. http://dx.doi.org/10.22161/ijaems.66.5.

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2

Kakeda, Shingo, Yukunori Korogi, Yasuhiro Hiai, Norihiro Ohnari, Toru Sato, and Toshinori Hirai. "Pitfalls of 3D FLAIR Brain Imaging." Academic Radiology 19, no. 10 (October 2012): 1225–32. http://dx.doi.org/10.1016/j.acra.2012.04.017.

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3

Taranda, Julian, and Sevin Turcan. "3D Whole-Brain Imaging Approaches to Study Brain Tumors." Cancers 13, no. 8 (April 15, 2021): 1897. http://dx.doi.org/10.3390/cancers13081897.

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Although our understanding of the two-dimensional state of brain tumors has greatly expanded, relatively little is known about their spatial structures. The interactions between tumor cells and the tumor microenvironment (TME) occur in a three-dimensional (3D) space. This volumetric distribution is important for elucidating tumor biology and predicting and monitoring response to therapy. While static 2D imaging modalities have been critical to our understanding of these tumors, studies using 3D imaging modalities are needed to understand how malignant cells co-opt the host brain. Here we summarize the preclinical utility of in vivo imaging using two-photon microscopy in brain tumors and present ex vivo approaches (light-sheet fluorescence microscopy and serial two-photon tomography) and highlight their current and potential utility in neuro-oncology using data from solid tumors or pathological brain as examples.

4

Pooh, Ritsuko K. "Three-dimensional Evaluation of the Fetal Brain." Donald School Journal of Ultrasound in Obstetrics and Gynecology 11, no. 4 (2017): 268–75. http://dx.doi.org/10.5005/jp-journals-10009-1532.

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ABSTRACT Three-dimensional (3D) ultrasound is one of the most attractive modalities in the field of fetal ultrasound imaging. Combination of both transvaginal sonography and 3D ultrasound may be a great diagnostic tool for evaluation of 3D structure of fetal central nervous system (CNS). Recent advanced 3D ultrasound equipments have several useful functions, such as surface anatomy imaging; multiplanar imaging of the intracranial structure; tomographic ultrasound imaging of fetal brain in the any cutting section; bony structural imaging of the calvaria and vertebrae; thick slice imaging of the intracranial structure; simultaneous volume contrast imaging of the same section or vertical section of fetal brain structure; volume calculation of target organs, such as intracranial cavity, ventricle, choroid plexus, and intracranial lesions; and 3D sonoangiography of the brain circulation (3D power or color Doppler). Furthermore, recent advanced technologies, such as HDlive silhouette and HDlive flow are quite attractive modalities and they can be applied for neuroimaging. Up-to-date 3D technologies described in this study allow extending the detection of congenital brain maldevelopment, and it is beyond description that noninvasive direct viewing of the embryo/fetus by all-inclusive ultrasound technology is definitely the first modality in a field of fetal neurology and helps our goal of proper perinatal care and management, even in the era of molecular genetics and advanced sequencing of fetal deoxyribonucleic acid (DNA) in the maternal blood. As a future aspect, collaboration of both molecular genetics and 3D neuroimaging will reveal responsible gene mutation of neuronal migration disorder, and this fetal neuro-sono-genetics will be able to contribute to accurate diagnoses, proper management, possible genetic therapy, and prophylaxis. How to cite this article Pooh RK. Three-dimensional Evaluation of the Fetal Brain. Donald School J Ultrasound Obstet Gynecol 2017;11(4):268-275.

5

Yao, Junjie. "Deep-brain imaging with 3D integrated photoacoustic tomography and ultrasound localization microscopy." Journal of the Acoustical Society of America 155, no. 3_Supplement (March 1, 2024): A53. http://dx.doi.org/10.1121/10.0026774.

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Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain’s oxygen saturation of hemoglobin (sO2), US imaging can probe the blood flow based on the Doppler effect. Furthermore, by tracking gas-filled microbubbles, ultrasound localization microscopy (ULM) can map the blood flow velocity with sub-diffraction spatial resolution. In this work, we present a 3D deep-brain imaging system that seamlessly integrates PACT and ULM into a single device, 3D-PAULM. Using a low ultrasound frequency of 4 MHz, 3D-PAULM is capable of imaging the whole-brain hemodynamic functions with intact scalp and skull in a totally non-invasive manner. Using 3D-PAULM, we studied the mouse brain functions with ischemic stroke. Multi-spectral PACT, US B-mode imaging, microbubble-enhanced power Doppler (PD), and ULM were performed on the same mouse brain with intrinsic image co-registration. From the multi-modality measurements, we future quantified blood perfusion, sO2, vessel density, and flow velocity of the mouse brain, showing stroke-induced ischemia, hypoxia, and reduced blood flow. We expect that 3D-PAULM can find broad applications in studying deep brain functions on small animal models.

6

Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (August 30, 2017): 1603. http://dx.doi.org/10.12688/f1000research.12336.1.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium) a dedicated medical image processing software for the purposes of image segmentation and 3D modeling. The imported axial images were automatically formatted to display coronal and sagittal slices within the software. The imaging study was then segmented into regions and surface rendered to achieve 3D virtual printable files of the desired structures of interest. Rendering brain tumor(s) in 3D has been attempted with the specific intent of extending the options available to a surgeon but no study to our knowledge has attempted to quantify brain disease in MS that has, for all practical purposes, no surgical options.

7

Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (September 20, 2017): 1603. http://dx.doi.org/10.12688/f1000research.12336.2.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium) a dedicated medical image processing software for the purposes of image segmentation and 3D modeling. The imported axial images were automatically formatted to display coronal and sagittal slices within the software. The imaging study was then segmented into regions and surface rendered to achieve 3D virtual printable files of the desired structures of interest. Rendering brain tumor(s) in 3D has been attempted with the specific intent of extending the options available to a surgeon but no study to our knowledge has attempted to quantify brain disease in MS that has, for all practical purposes, no surgical options.

8

Ren, Jiahao, Xiaocen Wang, Chang Liu, He Sun, Junkai Tong, Min Lin, Jian Li, et al. "3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks." Sensors 23, no. 19 (October 9, 2023): 8341. http://dx.doi.org/10.3390/s23198341.

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Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hindered by the high acoustic impedance contrast between the skull and soft tissue. This study introduces a 3D AI algorithm, Brain Imaging Full Convolution Network (BIFCN), combining waveform modeling and deep learning for precise brain ultrasound reconstruction. We constructed a network comprising one input layer, four convolution layers, and one pooling layer to train our algorithm. In the simulation experiment, the Pearson correlation coefficient between the reconstructed and true images was exceptionally high. In the laboratory, the results showed a slightly lower but still impressive coincidence degree for 3D reconstruction, with pure water serving as the initial model and no prior information required. The 3D network can be trained in 8 h, and 10 samples can be reconstructed in just 12.67 s. The proposed 3D BIFCN algorithm provides a highly accurate and efficient solution for mapping wavefield frequency domain data to 3D brain models, enabling fast and precise brain tissue imaging. Moreover, the frequency shift phenomenon of blood may become a hallmark of BIFCN learning, offering valuable quantitative information for whole-brain blood imaging.

9

de Crespigny, Alex, Hani Bou-Reslan, Merry C. Nishimura, Heidi Phillips, Richard A. D. Carano, and Helen E. D’Arceuil. "3D micro-CT imaging of the postmortem brain." Journal of Neuroscience Methods 171, no. 2 (June 2008): 207–13. http://dx.doi.org/10.1016/j.jneumeth.2008.03.006.

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10

Miao, Peng, Zhixia Wu, Miao Li, Yuanyuan Ji, Bohua Xie, Xiaojie Lin, and Guo-Yuan Yang. "Synchrotron Radiation X-Ray Phase-Contrast Tomography Visualizes Microvasculature Changes in Mice Brains after Ischemic Injury." Neural Plasticity 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3258494.

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Imaging brain microvasculature is important in plasticity studies of cerebrovascular diseases. Applying contrast agents, traditionalμCT andμMRI methods gain imaging contrast for vasculature. The aim of this study is to develop a synchrotron radiation X-ray inline phase-contrast tomography (SRXPCT) method for imaging the intact mouse brain (micro)vasculature in high resolution (~3.7 μm) without contrast agent. A specific preparation protocol was proposed to enhance the phase contrast of brain vasculature by using density difference over gas-tissue interface. The CT imaging system was developed and optimized to obtain 3D brain vasculature of adult male C57BL/6 mice. The SRXPCT method was further applied to investigate the microvasculature changes in mouse brains (n=14) after 14-day reperfusion from transient middle cerebral artery occlusion (tMCAO). 3D reconstructions of brain microvasculature demonstrated that the branching radius ratio (post- to preinjury) of small vessels (radius < 7.4 μm) in the injury group was significantly smaller than that in the sham group (p<0.05). This result revealed the active angiogenesis in the recovery brain after stroke. As a high-resolution and contrast-agent-free method, the SRXPCT method demonstrates higher potential in investigations of functional plasticity in cerebrovascular diseases.

11

Wang, Hao, Qingyuan Zhu, Lufeng Ding, Yan Shen, Chao-Yu Yang, Fang Xu, Chang Shu, et al. "Scalable volumetric imaging for ultrahigh-speed brain mapping at synaptic resolution." National Science Review 6, no. 5 (April 24, 2019): 982–92. http://dx.doi.org/10.1093/nsr/nwz053.

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Abstract The speed of high-resolution optical imaging has been a rate-limiting factor for meso-scale mapping of brain structures and functional circuits, which is of fundamental importance for neuroscience research. Here, we describe a new microscopy method of Volumetric Imaging with Synchronized on-the-fly-scan and Readout (VISoR) for high-throughput, high-quality brain mapping. Combining synchronized scanning beam illumination and oblique imaging over cleared tissue sections in smooth motion, the VISoR system effectively eliminates motion blur to obtain undistorted images. By continuously imaging moving samples without stopping, the system achieves high-speed 3D image acquisition of an entire mouse brain within 1.5 hours, at a resolution capable of visualizing synaptic spines. A pipeline is developed for sample preparation, imaging, 3D image reconstruction and quantification. Our approach is compatible with immunofluorescence methods, enabling flexible cell-type specific brain mapping and is readily scalable for large biological samples such as primate brains. Using this system, we examined behaviorally relevant whole-brain neuronal activation in 16 c-Fos-shEGFP mice under resting or forced swimming conditions. Our results indicate the involvement of multiple subcortical areas in stress response. Intriguingly, neuronal activation in these areas exhibits striking individual variability among different animals, suggesting the necessity of sufficient cohort size for such studies.

12

Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (February 28, 2018): 1603. http://dx.doi.org/10.12688/f1000research.12336.3.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient’s images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium) a dedicated medical image processing software designed for the purposes of image segmentation and 3D modeling. The imported axial images were automatically formatted to display coronal and sagittal slices within the software. The imaging data were then segmented into regions and surface rendering was done to achieve 3D virtual printable files of the desired structures of interest. Rendering brain tumor(s) in 3D has been attempted with the specific intent of extending the options available to a surgeon but no study to our knowledge has attempted to quantify brain disease in MS that has, for all practical purposes, no surgical options. The purpose of our study was to demonstrate that 3D depiction of chronic neurological diseases is possible in a printable model while serving a fundamental need for patient education. Medical teaching is moored in 2D graphics and it is time to evolve into 3D models that can be life-like and deliver instant impact.

13

Avasarala, Jagannadha, and Todd Pietila. "The first 3D printed multiple sclerosis brain: Towards a 3D era in medicine." F1000Research 6 (May 18, 2018): 1603. http://dx.doi.org/10.12688/f1000research.12336.4.

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Conventional magnetic resonance imaging (MRI) studies depict disease of the human brain in 2D but the reconstruction of a patient’s brain stricken with multiple sclerosis (MS) in 3D using 2D images has not been attempted. Using 3D reconstruction algorithms, we built a 3D printed patient-specific brain model to scale. It is a first of its kind model that depicts the total white matter lesion (WML) load using T2 FLAIR images in an MS patient. The patient’s images in Digital Imaging and Communications in Medicine (DICOM) format were imported into Mimics inPrint 2.0 (Materialise NV, Leuven, Belgium) a dedicated medical image processing software designed for the purposes of image segmentation and 3D modeling. The imported axial images were automatically formatted to display coronal and sagittal slices within the software. The imaging data were then segmented into regions and surface rendering was done to achieve 3D virtual printable files of the desired structures of interest. Rendering brain tumor(s) in 3D has been attempted with the specific intent of extending the options available to a surgeon but no study to our knowledge has attempted to quantify brain disease in MS that has, for all practical purposes, no surgical options. The purpose of our study was to demonstrate that 3D depiction of chronic neurological diseases is possible in a printable model while serving a fundamental need for patient education. Medical teaching is moored in 2D graphics and it is time to evolve into 3D models that can be life-like and deliver instant impact.

14

Shi, Shupeng, Haoran Zhang, Xianzhen Yin, Zhuolu Wang, Bin Tang, Yuebei Luo, Hui Ding, et al. "3D digital anatomic angioarchitecture of the mouse brain using synchrotron-radiation-based propagation phase-contrast imaging." Journal of Synchrotron Radiation 26, no. 5 (July 12, 2019): 1742–50. http://dx.doi.org/10.1107/s160057751900674x.

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Thorough investigation of the three-dimensional (3D) configuration of the vasculature of mouse brain remains technologically difficult because of its complex anatomical structure. In this study, a systematic analysis is developed to visualize the 3D angioarchitecture of mouse brain at ultrahigh resolution using synchrotron-radiation-based propagation phase-contrast imaging. This method provides detailed restoration of the intricate brain microvascular network in a precise 3D manner. In addition to depicting the delicate 3D arrangements of the vascular network, 3D virtual micro-endoscopy is also innovatively performed to visualize randomly a selected vessel within the brain for both external 3D micro-imaging and endoscopic visualization of any targeted microvessels, which improves the understanding of the intrinsic properties of the mouse brain angioarchitecture. Based on these data, hierarchical visualization has been established and a systematic assessment on the 3D configuration of the mouse brain microvascular network has been achieved at high resolution which will aid in advancing the understanding of the role of vasculature in the perspective of structure and function in depth. This holds great promise for wider application in various models of neurovascular diseases.

15

Tobon Vasquez, Jorge A., Rosa Scapaticci, Giovanna Turvani, Gennaro Bellizzi, David O. Rodriguez-Duarte, Nadine Joachimowicz, Bernard Duchêne, et al. "A Prototype Microwave System for 3D Brain Stroke Imaging." Sensors 20, no. 9 (May 3, 2020): 2607. http://dx.doi.org/10.3390/s20092607.

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This work focuses on brain stroke imaging via microwave technology. In particular, the open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period. In this paper, a novel prototype is presented and characterized. The device is based on a low-complexity architecture which makes use of a minimum number of properly positioned and designed antennas placed on a helmet. It exploits a differential imaging approach and provides 3D images of the stroke. Preliminary experiments involving a 3D phantom filled with brain tissue-mimicking liquid confirm the potential of the technology in imaging a spherical target mimicking a stroke of a radius equal to 1.25 cm.

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Sudarman, A. Gunawan Santoso, Fatimah, Rasyid, and Leny Latifah. "Volumetric Hippocampal Magnetic Resonance Imaging and Electroenchepalogram OF Epilepsy." International Journal of Advanced Technology and Social Sciences 2, no. 2 (February 29, 2024): 255–70. http://dx.doi.org/10.59890/ijatss.v2i2.1433.

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Hippocampal volumetry is a method of measuring the volume or size of hippocampal structures in the brain, can be used as a diagnostic aid and monitoring of disease progression conditions or neurological disorders as well as response to treatment. Analyze volumetric measurement of Hippocampus MRI examination Brain 3D T2 FSE with EEG study results in cases of Epilepsy. Patient data was obtained through MRI examination of Brain 3D T2 FSE to measure volumetric hippocampus. These volumetric results are compared with EEG interpretation in cases of epilepsy. Statistical analysis was performed to identify the correlation between volumetric changes in the hippocampus and EEG results. There was no difference in the volume of the left hippocampus smaller than the right based on MRI measurements of Brain 3D T2 FSE in cases of epilepsy. Most (77.27%) shrank right and left. Left lobe temporal brain wave images in all epilepsy patients with irregular ups and downs show abnormalities based on EEG measurements. Brain wave images of the right temporal lobe in epilepsy patients are all normal. Volumetric imaging for epileptic patients cannot establish the diagnosis of epilepsy, because it cannot show an sensibility between the left and right hemisper images

17

Gleave, Jacqueline A., Michael D. Wong, Jun Dazai, Maliha Altaf, R. Mark Henkelman, Jason P. Lerch, and Brian J. Nieman. "Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging." Physiological Genomics 44, no. 15 (August 1, 2012): 778–85. http://dx.doi.org/10.1152/physiolgenomics.00055.2012.

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The structural organization of the brain is important for normal brain function and is critical to understand in order to evaluate changes that occur during disease processes. Three-dimensional (3D) imaging of the mouse brain is necessary to appreciate the spatial context of structures within the brain. In addition, the small scale of many brain structures necessitates resolution at the ∼10 μm scale. 3D optical imaging techniques, such as optical projection tomography (OPT), have the ability to image intact large specimens (1 cm3) with ∼5 μm resolution. In this work we assessed the potential of autofluorescence optical imaging methods, and specifically OPT, for phenotyping the mouse brain. We found that both specimen size and fixation methods affected the quality of the OPT image. Based on these findings we developed a specimen preparation method to improve the images. Using this method we assessed the potential of optical imaging for phenotyping. Phenotypic differences between wild-type male and female mice were quantified using computer-automated methods. We found that optical imaging of the endogenous autofluorescence in the mouse brain allows for 3D characterization of neuroanatomy and detailed analysis of brain phenotypes. This will be a powerful tool for understanding mouse models of disease and development and is a technology that fits easily within the workflow of biology and neuroscience labs.

18

Li, Yao, Tianyao Wang, Tianxiao Zhang, Zengping Lin, Yudu Li, Rong Guo, Yibo Zhao, et al. "Fast high-resolution metabolic imaging of acute stroke with 3D magnetic resonance spectroscopy." Brain 143, no. 11 (November 2020): 3225–33. http://dx.doi.org/10.1093/brain/awaa264.

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Abstract Impaired oxygen and cellular metabolism is a hallmark of ischaemic injury in acute stroke. Magnetic resonance spectroscopic imaging (MRSI) has long been recognized as a potentially powerful tool for non-invasive metabolic imaging. Nonetheless, long acquisition time, poor spatial resolution, and narrow coverage have limited its clinical application. Here we investigated the feasibility and potential clinical utility of rapid, high spatial resolution, near whole-brain 3D metabolic imaging based on a novel MRSI technology. In an 8-min scan, we simultaneously obtained 3D maps of N-acetylaspartate and lactate at a nominal spatial resolution of 2.0 × 3.0 × 3.0 mm3 with near whole-brain coverage from a cohort of 18 patients with acute ischaemic stroke. Serial structural and perfusion MRI was used to define detailed spatial maps of tissue-level outcomes against which high-resolution metabolic changes were evaluated. Within hypoperfused tissue, the lactate signal was higher in areas that ultimately infarcted compared with those that recovered (P < 0.0001). Both lactate (P < 0.0001) and N-acetylaspartate (P < 0.001) differed between infarcted and other regions. Within the areas of diffusion-weighted abnormality, lactate was lower where recovery was observed compared with elsewhere (P < 0.001). This feasibility study supports further investigation of fast high-resolution MRSI in acute stroke.

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Mori, Koichi, Hisashi Yoshita, Syuici Tonami, Mamoru Nakamura, Makoto Kuranishi, Osamu Saito, Hirofumi Hagino, and Takashi Yotsutsuji. "Evaluation of brain MPR images using 3D-MR imaging." Japanese Journal of Radiological Technology 53, no. 7 (1997): 969. http://dx.doi.org/10.6009/jjrt.kj00001355986.

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20

Duijn, Jeff H., Gerald B. Matson, Andrew A. Maudsley, and Michael W. Weiner. "3D phase encoding 1H spectroscopic imaging of human brain." Magnetic Resonance Imaging 10, no. 2 (January 1992): 315–19. http://dx.doi.org/10.1016/0730-725x(92)90490-q.

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21

Sati, P., DM Thomasson, N. Li, DL Pham, NM Biassou, DS Reich, and JA Butman. "Rapid, high-resolution, whole-brain, susceptibility-based MRI of multiple sclerosis." Multiple Sclerosis Journal 20, no. 11 (March 17, 2014): 1464–70. http://dx.doi.org/10.1177/1352458514525868.

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Background: Susceptibility-based MRI offers a unique opportunity to study neurological diseases such as multiple sclerosis (MS). In this work, we assessed a three-dimensional segmented echo-planar-imaging (3D-EPI) sequence to rapidly acquire high-resolution T2*-weighted and phase contrast images of the whole brain. We also assessed if these images could depict important features of MS at clinical field strength, and we tested the effect of a gadolinium-based contrast agent (GBCA) on these images. Materials and methods: The 3D-EPI acquisition was performed on four healthy volunteers and 15 MS cases on a 3T scanner. The 3D sagittal images of the whole brain were acquired with a voxel size of 0.55 × 0.55 × 0.55 mm3 in less than 4 minutes. For the MS cases, the 3D-EPI acquisition was performed before, during, and after intravenous GBCA injection. Results: Both T2*-weighted and phase-contrast images from the 3D-EPI acquisition were sensitive to the presence of lesions, parenchymal veins, and tissue iron. Conspicuity of the veins was enhanced when images were obtained during injection of GBCA. Conclusions: We propose this rapid imaging sequence for investigating, in a clinical setting, the spatiotemporal relationship between small parenchymal veins, iron deposition, and lesions in MS patient brains.

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Samancı, Rumeysa, Hayri Oğul, Ayşe Gökçe, Abdulkadir Kaya, and Safinaz Ataoğlu. "Investigation of incidental findings of temporomandibular joint disorders on brain magnetic resonance imaging in three-dimensional T2-weighted SPACE sequence performed for brain imaging." Turkish Journal of Physical Medicine and Rehabilitation 70, no. 1 (February 1, 2024): 123–30. http://dx.doi.org/10.5606/tftrd.2024.12538.

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Objectives: The study aimed to determine the temporomandibular joint (TMJ) findings, to investigate the prevalence contribution of this sequence on cases in which cranial magnetic resonance examination was performed and three-dimensional (3D) T2-SPACE (T2-weighted sampling perfection with application-optimized contrasts using different flip-angle evolutions) sequence was used by retrospectively scanning the magnetic resonance imaging (MRI) archive of our hospital, and to reveal the advantages of the 3D-T2 SPACE sequence in patients with TMJ disorders. Patients and methods: The cross-sectional retrospective study was conducted with 499 patients (289 females, 210 males; mean age: 50.1±17.7 years; range, 8 to 92 years) who underwent brain MRI and had 3D-T2 SPACE between March 1, 2021 and March 1, 2022. Two radiologists analyzed the TMJs of the subjects included in the study in 3D-T2 SPACE sequences. Results: At least one incidental finding was detected in the TMJ in 37.1% (n=185) of the patients included in our study. In our study, the most common (13.6%) MRI findings were osteoarthritic changes and synovial cysts. Joint effusion (13.2%) and disc displacement (9%) were less frequent. When the relationship between the age of the patients and the presence of incidental findings, degeneration, effusion, disc displacement, and cyst was examined, the age of the patients with incidental findings (p=0.001) and osteoarthritic changes (p<0.001) was statistically significantly higher. Conclusion: Incidental findings, particularly osteoarthritic changes and synovial cysts, can be seen quite commonly in the TMJ in brain MRI using 3D T2-SPACE sequences in the general population. The 3D T2-SPACE sequence provides valuable information in the recognition of TMJ disorders.

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kotha, Apoorva, David L. Yang, Mariam Aboian, Usha D. Nagaraj, Aashim Bhatia, and Adam Ezra Goldman-Yassen. "IMG-27. ASSESSMENT OF VARIABILITY OF PEDIATRIC BRAIN TUMOR IMAGING PROTOCOLS ACROSS INSTITUTIONS: ARE WE FOLLOWING RECOMMENDATIONS?" Neuro-Oncology 26, Supplement_4 (June 18, 2024): 0. http://dx.doi.org/10.1093/neuonc/noae064.364.

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Abstract BACKGROUND Evaluating pediatric brain tumors requires imaging children with tailored MRI protocols. Considerable variation in pediatric brain tumor imaging protocols exist across institutions, which can cause inaccuracies in staging. Although recently consensus guidelines for pediatric brain tumor imaging protocols have been established, adherence to these guidelines across institutions is unknown. Institutions may perceive guidelines as applicable for research purposes rather than routine clinical practice. We aim to explore variability in pediatric brain tumor imaging protocols across institutions and determine the factors influencing guideline divergence. METHODS AND METHODOLOGY Faculty at institutions routinely imaging pediatric patients with brain tumors were invited to share brain tumor MRI protocols and complete a structured survey. The survey included multiple choice and open-ended queries concerning practice type, the presence of an institutional imaging protocol for pediatric brain tumors and if the protocol was based on specific consensus recommendations. We assessed if protocols included the 7 minimum recommended MRI sequences by the Children’s Oncology Group (COG) guidelines, including slice thickness and gap. RESULTS Twenty emails were sent and responses were received from 12 institutions (the data collection is still ongoing). 2 institutions did not have dedicated protocols for pediatric brain tumors. On average, institutions had 5.7 out of the 7 minimum COG-recommended sequences. All 10 institutions included 3D T1 IR-GRE/TSE, DWI or DTI, and SWI sequences in their protocols. 9 (90%) included post-contrast 3D T1 IR-GRE/TSE, 7 (70%) included T2 TSE/FSE, 7 (70%) included either 3D T2 FLAIR or T2 FLAIR TSE/FSE, and 4 (40%) included T1/TSE/FSE. Across all sequences in all protocols, adherence to recommended imaging parameters was 87% for plane, 71% for slice thickness, and 85% for gap. CONCLUSION Significant variability in pediatric brain tumor imaging protocols exists across institutions Standardizing imaging protocols through collaboration is vital in ensuring uniformity in care.

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Pintucci, Armando, FNU Vincenzo, D. Addario, Vincenzo Pinto, and Luca Di Cagno. "Three-dimensional Ultrasound of the Fetal Brain." Donald School Journal of Ultrasound in Obstetrics and Gynecology 1, no. 3 (2007): 17–25. http://dx.doi.org/10.5005/jp-journals-10009-1104.

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Abstract Three-dimensional ultrasound is the most innovating and attracting modality in the field of ultrasound imaging and represents a superb tool to perform an accurate fetal neuroscan. Once the fetal brain has been scanned, it is then possible to “navigate” in the stored volume choosing among the multiple scanning planes on the three orthogonal spatial axes. Last generation 3D equipments have multiple software facilities which are extremely useful to correctly evaluate the fetal brain such as the multiplanar view, the tomographic ultrasound imaging (TUI), the volume contrast imaging in the C plane (VCI-C plane), the volume calculation, the surface rendering, the 3D color and power Doppler. Thanks to these imaging modalities it is possible to evaluate the finest anatomical details of the developing brain and to increase the diagnostic accuracy when an abnormal sonographic finding of the fetal brain is recognized during the routine examination.

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Smith, Lauren C., and Adam Kimbrough. "Leveraging Neural Networks in Preclinical Alcohol Research." Brain Sciences 10, no. 9 (August 21, 2020): 578. http://dx.doi.org/10.3390/brainsci10090578.

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Alcohol use disorder is a pervasive healthcare issue with significant socioeconomic consequences. There is a plethora of neural imaging techniques available at the clinical and preclinical level, including magnetic resonance imaging and three-dimensional (3D) tissue imaging techniques. Network-based approaches can be applied to imaging data to create neural networks that model the functional and structural connectivity of the brain. These networks can be used to changes to brain-wide neural signaling caused by brain states associated with alcohol use. Neural networks can be further used to identify key brain regions or neural “hubs” involved in alcohol drinking. Here, we briefly review the current imaging and neurocircuit manipulation methods. Then, we discuss clinical and preclinical studies using network-based approaches related to substance use disorders and alcohol drinking. Finally, we discuss how preclinical 3D imaging in combination with network approaches can be applied alone and in combination with other approaches to better understand alcohol drinking.

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Wang, Lulu. "Three-Dimensional Holographic Electromagnetic Imaging for Accessing Brain Stroke." Sensors 18, no. 11 (November 9, 2018): 3852. http://dx.doi.org/10.3390/s18113852.

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The authors recently developed a two-dimensional (2D) holographic electromagnetic induction imaging (HEI) for biomedical imaging applications. However, this method was unable to detect small inclusions accurately. For example, only one of two inclusions can be detected in the reconstructed image if the two inclusions were located at the same XY plane but in different Z-directions. This paper provides a theoretical framework of three-dimensional (3D) HEI to accurately and effectively detect inclusions embedded in a biological object. A numerical system, including a realistic head phantom, a 16-element excitation sensor array, a 16-element receiving sensor array, and image processing model has been developed to evaluate the effectiveness of the proposed method for detecting small stroke. The achieved 3D HEI images have been compared with 2D HEI images. Simulation results show that the 3D HEI method can accurately and effectively identify small inclusions even when two inclusions are located at the same XY plane but in different Z-directions. This preliminary study shows that the proposed method has the potential to develop a useful imaging tool for the diagnosis of neurological diseases and injuries in the future.

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Kaufmann, Timothy J., Marion Smits, Jerrold Boxerman, Raymond Huang, Daniel P. Barboriak, Michael Weller, Caroline Chung, et al. "Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases." Neuro-Oncology 22, no. 6 (February 12, 2020): 757–72. http://dx.doi.org/10.1093/neuonc/noaa030.

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Abstract A recent meeting was held on March 22, 2019, among the FDA, clinical scientists, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocacy groups to discuss challenges and potential solutions for increasing development of therapeutics for central nervous system metastases. A key issue identified at this meeting was the need for consistent tumor measurement for reliable tumor response assessment, including the first step of standardized image acquisition with an MRI protocol that could be implemented in multicenter studies aimed at testing new therapeutics. This document builds upon previous consensus recommendations for a standardized brain tumor imaging protocol (BTIP) in high-grade gliomas and defines a protocol for brain metastases (BTIP-BM) that addresses unique challenges associated with assessment of CNS metastases. The “minimum standard” recommended pulse sequences include: (i) parameter matched pre- and post-contrast inversion recovery (IR)–prepared, isotropic 3D T1-weighted gradient echo (IR-GRE); (ii) axial 2D T2-weighted turbo spin echo acquired after injection of gadolinium-based contrast agent and before post-contrast 3D T1-weighted images; (iii) axial 2D or 3D T2-weighted fluid attenuated inversion recovery; (iv) axial 2D, 3-directional diffusion-weighted images; and (v) post-contrast 2D T1-weighted spin echo images for increased lesion conspicuity. Recommended sequence parameters are provided for both 1.5T and 3T MR systems. An “ideal” protocol is also provided, which replaces IR-GRE with 3D TSE T1-weighted imaging pre- and post-gadolinium, and is best performed at 3T, for which dynamic susceptibility contrast perfusion is included. Recommended perfusion parameters are given.

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Moraal, Bastiaan, Stefan D. Roosendaal, Petra J. W. Pouwels, Hugo Vrenken, Ronald A. van Schijndel, Dominik S. Meier, Charles R. G. Guttmann, Jeroen J. G. Geurts, and Frederik Barkhof. "Multi-Contrast, Isotropic, Single-Slab 3D MR Imaging in Multiple Sclerosis." Neuroradiology Journal 22, no. 1_suppl (September 2009): 33–42. http://dx.doi.org/10.1177/19714009090220s108.

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To describe signal and contrast properties of an isotropic, single-slab 3D dataset [double inversion-recovery (DIR), fluid-attenuated inversion recovery (FLAIR), T2, and T1-weighted magnetization prepared rapid acquisition gradient-echo (MPRAGE)] and to evaluate its performance in detecting multiple sclerosis (MS) brain lesions compared to 2D T2-weighted spin-echo (T2SE). All single-slab 3D sequences and 2D-T2SE were acquired in 16 MS patients and 9 age-matched healthy controls. Lesions were scored independently by two raters and characterized anatomically. Two-tailed Bonferroni-corrected Student's t-tests were used to detect differences in lesion detection between the various sequences per anatomical area after log-transformation. In general, signal and contrast properties of the 3D sequences enabled improved detection of MS brain lesions compared to 2D-T2SE. Specifically, 3D-DIR showed the highest detection of intracortical and mixed WM-GM lesions, whereas 3D-FLAIR showed the highest total number of WM lesions. Both 3D-DIR and 3D-FLAIR showed the highest number of infratentorial lesions. 3D-T2 and 3D-MPRAGE did not improve lesion detection compared to 2D-T2SE. Multi-contrast, isotropic, single-slab 3D MRI allowed an improved detection of both GM and WM lesions compared to 2D-T2SE. A selection of single-slab 3D contrasts, for example, 3D-FLAIR and 3D-DIR, could replace 2D sequences in the radiological practice.

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Liu, Sa, Jun Nie, Yusha Li, Tingting Yu, Dan Zhu, and Peng Fei. "Three-dimensional, isotropic imaging of mouse brain using multi-view deconvolution light sheet microscopy." Journal of Innovative Optical Health Sciences 10, no. 05 (September 2017): 1743006. http://dx.doi.org/10.1142/s1793545817430064.

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We present a three-dimensional (3D) isotropic imaging of mouse brain using light-sheet fluorescent microscopy (LSFM) in conjunction with a multi-view imaging computation. Unlike common single view LSFM is used for mouse brain imaging, the brain tissue is 3D imaged under eight views in our study, by a home-built selective plane illumination microscopy (SPIM). An output image containing complete structural information as well as significantly improved resolution ([Formula: see text]4 times) are then computed based on these eight views of data, using a bead-guided multi-view registration and deconvolution. With superior imaging quality, the astrocyte and pyramidal neurons together with their subcellular nerve fibers can be clearly visualized and segmented. With further including other computational methods, this study can be potentially scaled up to map the connectome of whole mouse brain with a simple light-sheet microscope.

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Kongpromsuk, Sutasinee, Nantaporn Pitakvej, Nutchawan Jittapiromsak, and Supada Prakkamakul. "Detection of brain metastases using alternative magnetic resonance imaging sequences: a comparison between SPACE and VIBE sequences." Asian Biomedicine 14, no. 1 (July 13, 2020): 27–35. http://dx.doi.org/10.1515/abm-2020-0005.

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AbstractBackgroundAccurate identification of brain metastases is crucial for cancer treatment.ObjectivesTo compare the ability to detect brain metastases of two alternative types of contrast-enhanced three-dimensional (3D) T1-weighted sequences called SPACE (Sampling Perfection with Application optimized Contrasts using different flip angle Evolutions) and VIBE (Volumetric Interpolated Brain Sequence) on magnetic resonance imaging (MRI) at 3 tesla.MethodsBetween April 2017 and February 2018, 27 consecutive adult Thai patients with a total number of 424 brain metastases were retrospectively included. The patients underwent both contrast-enhanced 3D T1-weighted SPACE and 3D T1-weighted VIBE MRI sequences at 3 tesla. Two neuroradiology experts independently reviewed the images to determine the number of enhancing lesions on each sequence. Wilcoxon signed rank test was used to compare the difference between the numbers of detectable parenchymal enhancing lesions. Interobserver reliability was calculated using intraclass correlation.Results3D T1-weighted SPACE detected more parenchymal enhancing lesions than 3D T1-weighted VIBE (424 vs. 378 lesions, median 6 vs. 5, P = 0.008). Fifteen patients (55.6%) had equal number of parenchymal enhancing lesions between two sequences. 3D T1-weighted SPACE detected more parenchymal enhancing lesions (up to 9 more lesions) in 10 patients (37%), while 3D T1-weighted VIBE detected more enhancing lesions (up to 2 more lesions) in 2 patients (7.4%). Interobserver reliability between the readers was excellent.ConclusionContrast-enhanced 3D T1-weighted SPACE sequence demonstrates a higher ability to detect brain metastases than contrast-enhanced 3D T1-weighted VIBE sequence at 3 tesla.

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Yan, Li, Cole W. Dwiggins, Udit Gupta, and Kimberly M. Stroka. "A Rapid-Patterning 3D Vessel-on-Chip for Imaging and Quantitatively Analyzing Cell–Cell Junction Phenotypes." Bioengineering 10, no. 9 (September 13, 2023): 1080. http://dx.doi.org/10.3390/bioengineering10091080.

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The blood-brain barrier (BBB) is a dynamic interface that regulates the molecular exchanges between the brain and peripheral blood. The permeability of the BBB is primarily regulated by the junction proteins on the brain endothelial cells. In vitro BBB models have shown great potential for the investigation of the mechanisms of physiological function, pathologies, and drug delivery in the brain. However, few studies have demonstrated the ability to monitor and evaluate the barrier integrity by quantitatively analyzing the junction presentation in 3D microvessels. This study aimed to fabricate a simple vessel-on-chip, which allows for a rigorous quantitative investigation of junction presentation in 3D microvessels. To this end, we developed a rapid protocol that creates 3D microvessels with polydimethylsiloxane and microneedles. We established a simple vessel-on-chip model lined with human iPSC-derived brain microvascular endothelial-like cells (iBMEC-like cells). The 3D image of the vessel structure can then be “unwrapped” and converted to 2D images for quantitative analysis of cell–cell junction phenotypes. Our findings revealed that 3D cylindrical structures altered the phenotype of tight junction proteins, along with the morphology of cells. Additionally, the cell–cell junction integrity in our 3D models was disrupted by the tumor necrosis factor α. This work presents a “quick and easy” 3D vessel-on-chip model and analysis pipeline, together allowing for the capability of screening and evaluating the cell–cell junction integrity of endothelial cells under various microenvironment conditions and treatments.

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Sadahiro, Hirokazu, Hisaharu Goto, Sadahiro Nomura, and Michiyasu Suzuki. "STMO-02 PREOPERATIVE FENCE-POST METHOD PLANNING WITH 3D-FUSION IMAGING." Neuro-Oncology Advances 1, Supplement_2 (December 2019): ii18. http://dx.doi.org/10.1093/noajnl/vdz039.082.

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Abstract The fence-post method has been used for removal of intra-axial tumors. Preoperative detailed planning with only navigation work system is sometimes difficult to identify actual brain surface, small feeding artery and passing artery. Recently, 3-dementional imaging is well developed to integrate various anatomical findings. The purpose of this study is pursuit of perfect preoperative planning for removal intra-axial tumors with 3D-fusion imaging. From May 2017 to June 2019, 21 patients with intra-axial tumor were included. The software “AZE” was used to create 3D-fusion imaging. The brain tumor, brain surface and tractography were built from MRI, artery from digital angiography and vein from subtraction enhanced computed tomography. Then detailed preoperative planning was planned including how many fence-posts, procedure of cutting feeder, making sulcotomy or corticotomy, and finally cutting drainer. The average bleeding volume was 101±129cc, and there were no patients who had transfusion. All patients did not show additional neurological impairment after surgery. Detailed and perfect preoperative planning with 3D-sufion imaging should be effective for secure neurosurgery.

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Sangeetha, S. K. B., V. Muthukumaran, K. Deeba, Hariharan Rajadurai, V. Maheshwari, and Gemmachis Teshite Dalu. "Multiconvolutional Transfer Learning for 3D Brain Tumor Magnetic Resonance Images." Computational Intelligence and Neuroscience 2022 (August 23, 2022): 1–9. http://dx.doi.org/10.1155/2022/8722476.

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The difficulty or cost of obtaining data or labels in applications like medical imaging has progressed less quickly. If deep learning techniques can be implemented reliably, automated workflows and more sophisticated analysis may be possible in previously unexplored areas of medical imaging. In addition, numerous characteristics of medical images, such as their high resolution, three-dimensional nature, and anatomical detail across multiple size scales, can increase the complexity of their analysis. This study employs multiconvolutional transfer learning (MCTL) for applying deep learning to small medical imaging datasets in an effort to address these issues. Multiconvolutional transfer learning is a model based on transfer learning that enables deep learning with small datasets. In order to learn new features on a smaller target dataset, an initial baseline is used in the transfer learning process. In this study, 3D MRI images of brain tumors are classified using a convolutional autoencoder method. In order to use unenhanced Magnetic Resonance Imaging (MRI) for clinical diagnosis, expensive and invasive contrast-enhancing procedures must be performed. MCTL has been shown to increase accuracy by 1.5%, indicating that small targets are more easily detected with MCTL. This research can be applied to a wide range of medical imaging and diagnostic procedures, including improving the accuracy of brain tumor severity diagnosis through the use of MRI.

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Rijkers, Kim, Yasin Temel, Veerle Visser-Vandewalle, Linda Vanormelingen, Marjan Vandersteen, Peter Adriaensens, Jan Gelan, and Emile A. M. Beuls. "The microanatomical environment of the subthalamic nucleus." Journal of Neurosurgery 107, no. 1 (July 2007): 198–201. http://dx.doi.org/10.3171/jns-07/07/0198.

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✓High-frequency stimulation of the subthalamic nucleus (STN) is a widely performed method to treat advanced Parkinson disease. Due to the limitations of current imaging techniques, the 3D microanatomy of the STN and its surrounding structures in the mesencephalon are not well known. Using images they obtained using a 9.4-tesla magnetic resonance (MR) imaging unit, the authors developed a 3D reconstruction of the STN and its immediate surroundings. During the postmortem investigation of a human brain, a sample of tissue in the area around the STN was isolated. This brain tissue was scanned in the three orthogonal planes at 1-mm slice thickness. The images generated were compared with photographs of conventionally stained brain tissue slices in different neuroanatomical books, and a 3D reconstruction was made. High-field MR imaging is an appropriate method for visualizing the microanatomy of the STN and its surroundings. The images allow an optimal analysis of the microenvironment of the STN in the three orthogonal planes and can be used for 3D reconstructions of this area with possible clinical applications in the future.

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E, Ashalatha M., Mallikarjun S. Holi, Shubha V. Patel, and Deepashri K. M. "Segmentation of Brain Tumor using Multiple Threshold Technique." International Journal of Health Technology and Innovation 2, no. 01 (April 12, 2023): 23–26. http://dx.doi.org/10.60142/ijhti.v2i01.79.

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Radiology use medical imaging techniques to comprehend the structure and physiological functions of the body in bothhealthy and diseased subjects. A non-invasive method for viewing internal body structures can be performed by using magneticresonance imaging (MRI). MRI characterizes soft tissue more accurately than other imaging methods like CT. In the currentstudy, space-occupying lesions are visualized using MRI imaging. Slices of MRI data are used to analyze lesions. Single sliceanalysis is inappropriate to determine the lesion’s size and volume. Hence, the MRI sequence is used to segment the lesions.Following segmentation, we view the MRI 2D image in 3D to look for lesions, or aberrant tissue, in the brain. The lesion isthen visualized by performing clipping. This research suggests segmenting brain tumors automatically and even provides a3D visualization for a more thorough study. Here, a space-occupying lesion is segmented from a T2 weighted Flair sequenceof MR images in DICOM format, and by employing the segmented volume, 3D rendering and clipping are made possible

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Foxley, Sean, Miriam Domowicz, Gregory S. Karczmar, and Nancy Schwartz. "3D high spectral and spatial resolution imaging ofex vivomouse brain." Medical Physics 42, no. 3 (March 2, 2015): 1463–72. http://dx.doi.org/10.1118/1.4908203.

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Deichmann, R., C. D. Good, O. Josephs, J. Ashburner, and R. Turner. "Optimization of 3D MP-RAGE sequences for structural brain imaging." NeuroImage 11, no. 5 (May 2000): S478. http://dx.doi.org/10.1016/s1053-8119(00)91409-5.

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Helmstaedter, Moritz, Kevin L. Briggman, and Winfried Denk. "3D structural imaging of the brain with photons and electrons." Current Opinion in Neurobiology 18, no. 6 (December 2008): 633–41. http://dx.doi.org/10.1016/j.conb.2009.03.005.

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Lazutkin, A. A., N. V. Komissarova, D. M. Toptunov, and K. V. Anokhin. "Brain Morphology Imaging by 3D Microscopy and Fluorescent Nissl Staining." Bulletin of Experimental Biology and Medicine 155, no. 3 (July 2013): 399–402. http://dx.doi.org/10.1007/s10517-013-2162-9.

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Makabe, Takeshi, Manami Nakamura, and Ryo Moriyama. "Applicability of the 3D-VIBE Sequence to Whole Brain Imaging." Japanese Journal of Radiological Technology 65, no. 7 (2009): 945–51. http://dx.doi.org/10.6009/jjrt.65.945.

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Karakas, Asli Beril, Figen Govsa, Mehmet Asım Ozer, and Cenk Eraslan. "3D Brain Imaging in Vascular Segmentation of Cerebral Venous Sinuses." Journal of Digital Imaging 32, no. 2 (September 21, 2018): 314–21. http://dx.doi.org/10.1007/s10278-018-0125-4.

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Ozhinsky, Eugene, Daniel B. Vigneron, Susan M. Chang, and Sarah J. Nelson. "Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging." Magnetic Resonance in Medicine 69, no. 4 (June 12, 2012): 920–30. http://dx.doi.org/10.1002/mrm.24339.

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Miraux, Sylvain, Philippe Massot, Emeline J. Ribot, Jean-Michel Franconi, and Eric Thiaudiere. "3D TrueFISP imaging of mouse brain at 4.7T and 9.4T." Journal of Magnetic Resonance Imaging 28, no. 2 (August 2008): 497–503. http://dx.doi.org/10.1002/jmri.21449.

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Cavallaro, Marco, Alessandra Coglitore, Agostino Tessitore, Karol Galletta, Luciano Frosina, Antonino Cuffari, Roberta Ingrassia, et al. "Three-Dimensional Constructive Interference in Steady State (3D CISS) Imaging and Clinical Applications in Brain Pathology." Biomedicines 10, no. 11 (November 21, 2022): 2997. http://dx.doi.org/10.3390/biomedicines10112997.

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Three-dimensional constructive interference in steady state (3D CISS) is a steady-state gradient-echo sequence in magnetic resonance imaging (MRI) that has been used in an increasing number of applications in the study of brain disease in recent years. Owing to the very high spatial resolution, the strong hyperintensity of the cerebrospinal fluid signal and the high contrast-to-noise ratio, 3D CISS can be employed in a wide range of scenarios, ranging from the traditional study of cranial nerves, the ventricular system, the subarachnoid cisterns and related pathology to more recently discussed applications, such as the fundamental role it can assume in the setting of acute ischemic stroke, vascular malformations, infections and several brain tumors. In this review, after briefly summarizing its fundamental physical principles, we examine in detail the various applications of 3D CISS in brain imaging, providing numerous representative cases, so as to help radiologists improve its use in imaging protocols in daily clinical practice.

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Nikolov, Nikolay, Sergiy Makeyev, Olga Korostynska, Tetyana Novikova, and Yelizaveta Kriukova. "Gaussian Filter for Brain SPECT Imaging." Innovative Biosystems and Bioengineering 6, no. 1 (February 16, 2022): 4–15. http://dx.doi.org/10.20535/ibb.2022.6.1.128475.

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Background. The presence of a noise component on 3D images of single-photon emission computed tomography (SPECT) of a brain significantly distorts the probability distribution function (PD) of the radioactive count rate in the images. The presence of noise and further filtering of the data, based on a subjective assessment of image quality, have a significant impact on the calculation of volumetric cerebral blood flow and the values of the uptake asymmetry of the radiopharmaceutical in a brain. Objective. We are aimed to develop a method for optimal SPECT filtering of brain images with lipophilic radiopharmaceuticals, based on a Gaussian filter (GF), for subsequent image segmentation by the threshold method. Methods. SPECT images of the water phantom and the brain of patients with 99mTc-HMPAO were used. We have developed a technique for artificial addition of speckle noise to conditionally flawless data in order to determine the optimal parameters for smoothing SPECT, based on a GF. The quantitative criterion for optimal smoothing was the standard deviation between the PD of radioactive count rate of the smoothed image and conditionally ideal one. Results. It was shown that the maximum radioactive count rate of the SPECT image has an extremum by changing the standard deviation of the GF in the range of 0.3–0.4 pixels. The greater the noise component in the SPECT image, the more quasi-linearly the corresponding rate changes. This dependence allows determining the optimal smoothing parameters. The application of the developed smoothing technique allows restoring the probability distribution function of the radioactive count rate (distribution histogram) with an accuracy up to 5–10%. This provides the possibility to standardize SPECT images of brain. Conclusions. The research results of work solve a specific applied problem: restoration of the histogram of a radiopharmaceuticals distribution in a brain for correct quantitative assessment of regional cerebral blood flow. In contrast to the well-known publications on the filtration of SPECT data, the work takes into account that the initial tomographic data are 3D, rather than 2D slices, and contain not only uniform random Gaussian noise, but also a pronounced speckle component.

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Shen, Guofang, Kayla Sanchez, Shirley Hu, Zhen Zhao, Lubo Zhang, and Qingyi Ma. "3D doppler ultrasound imaging of cerebral blood flow for assessment of neonatal hypoxic-ischemic brain injury in mice." PLOS ONE 18, no. 5 (May 9, 2023): e0285434. http://dx.doi.org/10.1371/journal.pone.0285434.

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Cerebral blood flow (CBF) acutely reduces in neonatal hypoxic-ischemic encephalopathy (HIE). Clinic studies have reported that severe CBF impairment can predict HIE outcomes in neonates. Herein, the present study uses a non-invasive 3D ultrasound imaging approach to evaluate the changes of CBF after HI insult, and explores the correlation between CBF alterations and HI-induced brain infarct in mouse pups. The neonatal HI brain injury was induced in postnatal day 7 mouse pups using the Rice-Vannucci model. Non-invasive 3D ultrasound imaging was conducted to image CBF changes with multiple frequencies on mouse pups before common carotid artery (CCA) ligation, immediately after ligation, and 0 or 24 hours after HI. Vascularity ratio of the ipsilateral hemisphere was acutely reduced after unilateral ligation of the CCA alone or in combination with hypoxia, and partially restored at 24 hours after HI. Moreover, regression analysis showed that the vascularity ratio of ipsilateral hemisphere was moderately correlated with brain infarct size 24 hours after HI, indicating that CBF reduction contributes to of HI brain injury. To further verify the association between CBF and HI-induced brain injury, a neuropeptide C-type natriuretic peptide (CNP) or PBS was intranasally administrated to the brain of mouse pups one hour after HI insult. Brain infarction, CBF imaging and long-term neurobehavioral tests were conducted. The result showed that intranasal administration of CNP preserved ipsilateral CBF, reduced the infarct size, and improved neurological function after HI brain injury. Our findings suggest that CBF alteration is an indicator for neonatal HI brain injury, and 3D ultrasound imaging is a useful non-invasive approach for assessment of HI brain injury in mouse model.

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Riyazudeen, K. A. Mohamed, and Mohamed Sathik. "Converting 2D magnetic resource imagining brain tumors to 3D structure using depth map machine learning techniques." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 1 (July 1, 2022): 513. http://dx.doi.org/10.11591/ijeecs.v27.i1.pp513-520.

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<span>The use <span>of medical imaging technology aids clinicians in recognizing and assessing patient problems, as well as improving treatment procedures. However, while conducting complex procedures such as the excision of brain tumors, the knowledge and biological research gathered from 2D images are insufficient. Converting 2D images to 3D images may assist doctors in determining the size, shape, and sharp area of tumor cells in the brain. The feasibility of translating 2D medical image data to a 3D model is described in this work. A suggested framework for predicting the size, shape, and location of a brain tumor using a minimized genetic machine learning method, and then converting the tumor information into 3D images using a depth map estimation approach after detecting the tumor information. When the tumor is located, the left and right view data are combined to form a 3D magnetic resonance imaging reconstruction. We used mixed reality methods to minimize file size while preserving the greatest quality of the model during a brain surgical operation.</span></span>

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Turcotte, Raphaël, Yajie Liang, Masashi Tanimoto, Qinrong Zhang, Ziwei Li, Minoru Koyama, Eric Betzig, and Na Ji. "Dynamic super-resolution structured illumination imaging in the living brain." Proceedings of the National Academy of Sciences 116, no. 19 (April 26, 2019): 9586–91. http://dx.doi.org/10.1073/pnas.1819965116.

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Cells in the brain act as components of extended networks. Therefore, to understand neurobiological processes in a physiological context, it is essential to study them in vivo. Super-resolution microscopy has spatial resolution beyond the diffraction limit, thus promising to provide structural and functional insights that are not accessible with conventional microscopy. However, to apply it to in vivo brain imaging, we must address the challenges of 3D imaging in an optically heterogeneous tissue that is constantly in motion. We optimized image acquisition and reconstruction to combat sample motion and applied adaptive optics to correcting sample-induced optical aberrations in super-resolution structured illumination microscopy (SIM) in vivo. We imaged the brains of live zebrafish larvae and mice and observed the dynamics of dendrites and dendritic spines at nanoscale resolution.

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Hadjidekov, George, Gleb Haynatzki, Petya Chaveeva, Miroslav Nikolov, Gabriele Masselli, and Andrea Rossi. "Concordance between US and MRI Two-Dimensional Measurement and Volumetric Segmentation in Fetal Ventriculomegaly." Diagnostics 13, no. 6 (March 20, 2023): 1183. http://dx.doi.org/10.3390/diagnostics13061183.

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We provide a study comparison between two-dimensional measurement and volumetric (3D) segmentation of the lateral ventricles and brain structures in fetuses with isolated and non-isolated ventriculomegaly with 3D virtual organ computer-aided analysis (VOCAL) ultrasonography vs. magnetic resonance imaging (MRI) analyzed with 3D-Slicer software. In this cross-sectional study, 40 fetuses between 20 and 38 gestational weeks with various degrees of ventriculomegaly were included. A total of 71 ventricles were measured with ultrasound (US) and with MRI. A total of 64 sonographic ventricular volumes, 80 ventricular and 40 fetal brain MR volumes were segmented and analyzed using both imaging modalities by three observers. Sizes and volumes of the ventricles and brain parenchyma were independently analyzed by two radiologists, and interobserver correlation of the results with 3D fetal ultrasound data was performed. The semiautomated rotational multiplanar 3D VOCAL technique was performed for ultrasound volumetric measurements. Results were compared to manually extracted ventricular and total brain volumes in 3D-Slicer. Segmentation of fetal brain structures (cerebral and cerebellar hemispheres, brainstem, ventricles) performed independently by two radiologists showed high interobserver agreement. An excellent agreement between VOCAL and MRI volumetric and two-dimensional measurements was established, taking into account the intraclass correlation coefficients (ICC), and a Bland–Altman plot was established. US and MRI are valuable tools for performing fetal brain and ventricular volumetry for clinical prognosis and patient counseling. Our datasets could provide the backbone for further construction of quantitative normative trajectories of fetal intracranial structures and support earlier detection of abnormal brain development and ventriculomegaly, its timing and progression during gestation.

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SANCHEZ, DANMARY, MALEK ADJOUADI, NOLAN R. ALTMAN, DANIEL SANCHEZ, and BYRON BERNAL. "COMPREHENSIVE 3D FIBER TRACKING AS A NEW VISUALIZATION SYSTEM IN BRAIN STUDIES." International Journal of Image and Graphics 07, no. 04 (October 2007): 749–65. http://dx.doi.org/10.1142/s0219467807002891.

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Comprehensive spatial visualization of fiber tracts from all perspectives is a highly desirable outcome in brain studies. To achieve this aim, this study establishes the foundation for a new 3D visual interface that integrates Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing accurate diagnosis of key brain dysfunctions, in terms of neuronal connectivity in the human brain. Two research fronts were explored: (1) the development of new image processing techniques resulting in comprehensive visualization mechanisms that accurately establish relational positioning of neuronal fiber tracts and key landmarks in semi-transparent 3D brain images, and (2) the design of key algorithms that do not tax the computational requirements of 3D rendering and feature extraction using 2D MRI and DTI frames, remaining within practical time constraints. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. The highly integrated and fully embedded fiber-tracking software system provides an optimal research environment for innovative visualization mechanisms of white matter fiber tracts. This 3D visualization system reached the implementation level that makes it ready for deployment at other clinical sites.

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