Готові списки джерел за темами / Coefficient de Diffusion Apparent (ADC)

Добірка наукової літератури з теми "Coefficient de Diffusion Apparent (ADC)"

Автор: Grafiati

Опубліковано: 1 червня 2024

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Статті в журналах з теми "Coefficient de Diffusion Apparent (ADC)":

Chen, Haisong, Zengjie Wu, Wenjian Xu, Jing Pang, Meng Jia, Cheng Dong, and Xiaoli Li. "Evaluating the Scope of Malignant Bone Tumor Using ADC Measurement on ADC Map." Technology in Cancer Research & Treatment 18 (January 1, 2019): 153303381985326. http://dx.doi.org/10.1177/1533033819853267.

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Background: It is very important for surgeons to know the accurate borders of malignant bone tumors before they can precisely resect the tumors. The objective of the study is to investigate the usefulness of apparent diffusion coefficient value for estimating the extent of malignant bone tumor. Methods: VX2 tumor fragments were implanted into the tibiae of 30 rabbits. After 4 weeks, magnetic resonance plain scans were performed and then tumor specimens were cut into sagittal sections and partitioned into histology slices for dot-to-dot comparisons with microscopic findings. The sizes of the tumors measured separately on specimen, conventional magnetic resonance imaging sequences, and diffusion-weighted imaging (by measuring apparent diffusion coefficient value on apparent diffusion coefficient mapping) were compared statistically with each other. Results: The mean tumor sizes measured on specimen and apparent diffusion coefficient mapping (by calculating apparent diffusion coefficient value) were 5.20 ± 0.89 cm and 5.31 ± 0.87 cm, respectively; there was no significant difference between the 2 ( P > .05). The tumor sizes measured on T1WI, T2WI, T2WI with fat suppression were 4.82 ± 0.87 cm, 5.58 ± 0.87 cm, 5.63 ± 0.85 cm, respectively, and these values were significantly different from that measured on specimen (5.20 ± 0.89 cm, P < .05). Conclusion: The extent of the VX2 malignant bone tumor can be estimated accurately by measurement of apparent diffusion coefficient value.

Teixeira, Sara Reis, Paula Condé Lamparelli Elias, Andrea Farias de Melo Leite, Tatiane Mendes Gonçalves de Oliveira, Valdair Francisco Muglia, and Jorge Elias Junior. "Apparent diffusion coefficient of normal adrenal glands." Radiologia Brasileira 49, no. 6 (December 2016): 363–68. http://dx.doi.org/10.1590/0100-3984.2015.0045.

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Abstract Objective: To assess the feasibility and reliability of apparent diffusion coefficient (ADC) measurements of normal adrenal glands. Materials and methods: This was a retrospective study involving 32 healthy subjects, divided into two groups: prepubertal (PreP, n = 12), aged from 2 months to 12.5 years (4 males; 8 females); and postpubertal (PostP, n = 20), aged from 11.9 to 61 years (5 males; 15 females). Diffusion-weighted magnetic resonance imaging (DW-MRI) sequences were acquired at a 1.5 T scanner using b values of 0, 20, 500, and 1000 s/mm2. Two radiologists evaluated the images. ADC values were measured pixel-by-pixel on DW-MRI scans, and automatic co-registration with the ADC map was obtained. Results: Mean ADC values for the right adrenal glands were 1.44 × 10-3 mm2/s for the PreP group and 1.23 × 10-3 mm2/s for the PostP group, whereas they were 1.58 × 10-3 mm2/s and 1.32 × 10-3 mm2/s, respectively, for the left glands. ADC values were higher in the PreP group than in the PostP group (p < 0.05). Agreement between readers was almost perfect (intraclass correlation coefficient, 0.84-0.94; p < 0.05). Conclusion: Our results demonstrate the feasibility and reliability of performing DW-MRI measurements of normal adrenal glands. They could also support the feasibility of ADC measurements of small structures.

Verbanck, Sylvia, and Manuel Paiva. "Acinar determinants of the apparent diffusion coefficient for helium-3." Journal of Applied Physiology 108, no. 4 (April 2010): 793–99. http://dx.doi.org/10.1152/japplphysiol.01230.2009.

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The apparent diffusion coefficient (ADC) obtained by helium-3 magnetic resonance imaging over several seconds is thought to reflect diffusion impairment due to both intra- and interacinar structure. In this study, numerical simulations of intra-acinar gas mixing and effective diffusion were performed in a multiple-branch-point model of the human acinus. Using a previously described method, we computed the instantaneous effective diffusion resulting from the diffusive impairment imposed by intra-acinar branching for varying times up to 5 s. We also tested the influence on effective diffusion of intra-acinar collateral channels in the fully alveolated intra-acinar airways to mimic the effect of emphysema. Randomly connecting two or four pairs of airways per generation (in generations 19–25) led to a 40 and 142% increase, respectively, in effective diffusion coefficient cumulated over the time interval of 0.2–5 s. Finally, we also used a system of two coupled multiple branch-point models to simulate diffusive attenuation over a 50-s interval in cases of purely acinar tagging (i.e., the initial gas concentration = 1 in one acinus and 0 in the other) and of partial tagging astride on two acini. It is shown that, in the latter case, the decay rate cannot be approximated by a mono-exponential with a several-fold faster decay for times below 10 s due to intra-acinar diffusion. We conclude that both the characteristic biphasic time dependence of simulated effective diffusion and its sensitivity to intra-acinar structural change mimic experimental ADC behavior. Additional simulations of combined inter- and intra-acinar diffusion strongly suggest that neglecting intra-acinar branching would in fact lead to considerable error of simulated ADC.

Sumikawa, Tetsuo, Hidetake Yabuuchi, Chiharu Sumikawa, Yoshiteru Nakashima, and Gouji Miura. "Influence of blade width and magnetic field strength on the ADC on PROPELLER DWI in head and neck." Neuroradiology Journal 33, no. 1 (August 13, 2019): 39–47. http://dx.doi.org/10.1177/1971400919870178.

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Purpose The purpose of this study was to investigate the influence of blade width and magnetic field strength on apparent diffusion coefficient values of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) diffusion-weighted imaging in the head and neck at 1.5 and 3.0 T magnetic resonance imaging. Methods Fifteen healthy volunteers (eight men and seven women; mean age 36.4 ± 10.1 years) underwent PROPELLER diffusion-weighted imaging using four blade widths at 3.0 T and three blade widths at 1.5 T. For the multigroup comparison of apparent diffusion coefficient values, we performed analysis of variance and Tukey–Kramer tests. The apparent diffusion coefficient values in each organ were compared among the different blade widths and magnetic field strengths by a t test. Inter and intra-observer agreements regarding apparent diffusion coefficient value measurements were evaluated using the intraclass correlation coefficient. Results No significant differences were observed in apparent diffusion coefficient values of the cerebellum in each blade width at both field strengths. The apparent diffusion coefficient values of the right parotid glands were significantly lower for blade width 32 than for blade width 16 at 3.0 T (1.16 × 10–3 mm2/s vs. 1.01 × 10–3 mm2/s; P < 0.05). The apparent diffusion coefficient values of bilateral parotid glands were significantly higher at 1.5 T than at 3.0 T. Intraclass correlation coefficients were almost perfect to substantial in the cerebellum, whereas they showed moderate agreement in the parotid glands. Conclusion The largest blade width 32 at 3.0 T and high magnetic field strength lowered the apparent diffusion coefficient values of parotid glands of PROPELLER diffusion-weighted imaging. The apparent diffusion coefficient values in the parotid glands of PROPELLER diffusion-weighted imaging may be affected for blade width and magnetic field strength.

Ignjatovic, Jelena, Dragan Stojanov, Vladimir Zivkovic, Srdjan Ljubisavljevic, Nebojsa Stojanovic, Ivan Stefanovic, Daniela Benedeto-Stojanov, et al. "Apparent diffusion coefficient in the evaluation of cerebral gliomas malignancy." Vojnosanitetski pregled 72, no. 10 (2015): 870–75. http://dx.doi.org/10.2298/vsp140229073i.

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Background/Aim. Magnetic resonance imaging (MRI) is a key modality not only for lesion diagnosis, but also to evaluate the extension, type and grade of the tumor. Advanced MRI techniques provide physiologic information that complements the anatomic information available from conventional MRI. The aim of this study was to determine whether there is a correlation between apparent diffusion coefficient (ADC) maps of intracranial glial tumors and histopathologic findings and whether ADCs can reliably distinguish lowgrade from high-grade gliomas. Methods. This retrospective study included 25 patients with MRI examination up to seven days before surgery, according to the standard protocol with the following sequences: T1WI, T2WI, FLAIR, DWI and post contrast T1WI. Data obtained from DW MRI were presented by measuring the value of ADC. The ADC map was determined by utilizing Diffusion-Perfusion (DP) Tools software. All the patients underwent surgical resection of the tumor. Histological diagnosis of tumors was determined according to the World Health Organization (WHO) classification. The ADC values were compared with the histopathologic findings according to the WHO criteria. Results. The ADC values of astrocytomas grades I (0.000614 ? 0.000032 mm2/s) were significantly higher (< 0.001) than the ADC values of anaplastic astrocytomas (0.000436 ? 0.000016 mm2/s) and the ADC values of glioblastomas multiforme (0.000070 ? 0.000008 mm2/s). The ADC values of astrocytomas grades II (0.000530 ? 0.000114 mm2/s) were significantly higher (< 0.001) than the ADC values of anaplastic astrocytomas (0.000436 ? 0.000016 mm2/s) and glioblastomas multiforme (0.000070 ? 0.000008 mm2/s). The ADC values of anaplastic astrocytomas (0.000436 ? 0.000016 mm2/s) were significantly higher (< 0.001) than the ADC values of glioblastomas multiforme (0.000070 ? 0.000008 mm2/s). The ADC values in the cystic part of the tumor for astrocytomas grades I (0.000775 ? 0.000023 mm2/s) were significantly higher (< 0.001) than the ADC values of anaplastic astrocytomas (0.000119 ? 0.000246 mm2/s) and glioblastomas multiforme (0.000076 ? 0.000004 mm2/s). The ADC values astrocytomas grades II (0.000511 ? 0.000421 mm2/s) were significantly higher (< 0.001) than the ADC values of glioblastomas multiforme (0.000076 ? 0.000004 mm2/s). Concluson. DWI with calculation of ADC maps can be regarded as a reliable useful diagnostic tool, which indirectly reflects the proliferation and malignancy of gliomas. The ADCs maps can both predict the results of histopathological tumor and distinguish between low- and high-grade gliomas, and provide significant information for presurgical planning, treatment and prognosis for patients with highgrade astrocytomas.

Usuda, Katsuo, Shun Iwai, Aika Yamagata, Yoshihito Iijima, Nozomu Motono, Mariko Doai, Munetaka Matoba, Keiya Hirata, and Hidetaka Uramoto. "How to Discriminate Lung Cancer From Benign Pulmonary Nodules and Masses? Usefulness of Diffusion-Weighted Magnetic Resonance Imaging With Apparent Diffusion Coefficient and Inside/Wall Apparent Diffusion Coefficient Ratio." Clinical Medicine Insights: Oncology 15 (January 2021): 117955492110148. http://dx.doi.org/10.1177/11795549211014863.

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Background: Although diffusion-weighted imaging (DWI) is useful for differential diagnosis between lung cancers and benign pulmonary nodules and masses (BPNMs), it is difficult to differentiate pulmonary abscesses from lung cancers because pulmonary abscesses show restricted diffusion. With this research we will present how to assess the total apparent diffusion coefficient (ADC) and inside/wall ADC ratio for these pulmonary nodules and masses (PNMs). Methods: The pulmonary lesions were divided into next 3 groups. There were 40 lung cancers, 41 inflammatory benign PNMs (mycobacteria disease 13, pneumonia 12, pulmonary abscess 10, other 6) and 7 noninflammatory benign PNMs. Definitions were as follows: wall ADC = ADC value in outer one-third of the lesion; inside ADC = ADC value in central two-thirds of the lesion: inside/wall ADC ratio = ratio of inside ADC/wall ADC. Results: Mean total ADC (1.26 ± 0.32 × 10−3 mm2/s) of the lung cancers was remarkably lower than that (1.53 ± 0.53) of the BPNMs. The mean total ADC values were 1.26 ± 0.32 in lung cancer, 1.45 ± 0.47 in inflammatory BPNM and 2.04 ± 0.63 in noninflammatory BPNM, and there were significant differences among them. The mean inside ADC value (1.33 ± 0.32) of the lung cancers was remarkably higher than that (0.94 ± 0.42) of the pulmonary abscesses. The mean inside/wall ADC ratio (1.20 ± 0.28) of the lung cancers was remarkably higher than that (0.74 ± 0.14) of the pulmonary abscesses. Conclusions: Although ADC of DWI could differentiate lung cancer from BPNM, the inside/wall ADC ratio of DWI is efficient for differentiation between lung cancer and lung abscess. The inside/wall ADC ratio of DWI strengthens a weak point of DWI.

Wang, Rui, Weidong Liu, Fang Ren, and Jing Ren. "Comparative study of diagnostic value between IVIM and DWI for prostate cancer at 3.0 T magnetic resonance." Chinese Journal of Academic Radiology 4, no. 3 (August 19, 2021): 186–93. http://dx.doi.org/10.1007/s42058-021-00079-x.

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Abstract Objective To quantitatively compare the diagnostic and differential diagnostic value of intra-voxel incoherent motion imaging (IVIM) and diffusion weighted imaging (DWI) for prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Methods 68 cases of prostate confirmed by pathology, including 33 cases of PCa and 35 cases of BPH were analyzed retrospectively. All patients were underwent T1WI, T2WI, DWI and IVIM sequences to obtain the apparent diffusion coefficient (ADC), pure apparent diffusion coefficient (Pure-ADC/D), standard apparent diffusion coefficient (standard-ADC/Ds), fast apparent diffusion coefficient (fast-ADC/D*), fraction of fast apparent diffusion coefficient (f) values. All the multiple parameters were statistically analyzed for the differential diagnosis of BPH and PCa. P < 0.05 was considered as statistically significant. Results The differences in D, Ds, f and ADC values between BPH and PCa groups were statistically significant (all P values < 0.001), respectively. Among them, D value in the IVIM model had the highest diagnostic efficiency for PCa, the area under the curve (AUC) was 0.967, and the AUC combined with the ADC value and D value reaches 0.973. Conclusion The diagnostic efficacy of multiple parameters in the IVIM model for PCa was higher than the ADC value of the quantitative parameter of DWI. D value had the highest diagnostic efficiency. The combined diagnosis of ADC and D value was more effective, more advantageous in the diagnosis and differential diagnosis of PCa.

Kanamoto, Hirohito, Masaki Norimoto, Yawara Eguchi, Yasuhiro Oikawa, Sumihisa Orita, Kazuhide Inage, Koki Abe, et al. "Evaluating Spinal Canal Lesions Using Apparent Diffusion Coefficient Maps with Diffusion-Weighted Imaging." Asian Spine Journal 14, no. 3 (June 30, 2020): 312–19. http://dx.doi.org/10.31616/asj.2019.0266.

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Study Design: Observational study.Purpose: To evaluate healthy volunteers and patients with spinal canal lesions using apparent diffusion coefficient (ADC) maps with diffusion-weighted imaging.Overview of Literature: Decompression surgery for lumbar spinal stenosis (LSS) is selected on the basis of subjective assessment and cross-sectional magnetic resonance imaging (MRI). However, there is no objective standard for this procedure.Methods: We performed 3T MRI in 10 healthy volunteers and 13 patients with LSS. The ADC values in the spinal canal were evaluated at 46 vertebrae (L4/5 and L5/S1 for each participant), and the reduced and conventional fields of view were compared.Results: The ADC values were 2.72±0.12 at L4/5 in healthy volunteers, 2.76±0.19 at L5/S1 in healthy volunteers, 1.77±0.58 at L4/5 in patients with LSS, and 2.35±0.29 at L5/S1 in patients with LSS. The ADC value at L4/5 in patients with LSS was significantly lower than that at L5/S1 in patients with LSS and that at L4/5 and L5/S1 in healthy volunteers (<i>p</i> <0.05). With an ADC cutoff value of 2.46 to identify LSS, this approach provided an area under the curve of 0.81, sensitivity of 0.92, and specificity of 0.76 (<i>p</i> <0.05).Conclusions: Preoperative examination using ADC maps permits visualization and quantification of spinal canal lesions, thus proving the utility of ADC maps in the selection of decompression surgery for LSS.

Basirjafari, Sedigheh, Masoud Poureisa, Babak Shahhoseini, Mohammad Zarei, Saeideh Aghayari Sheikh Neshin, Sheida Anvari Aria, and Masoud Nouri-Vaskeh. "Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI." Acta Radiologica 61, no. 2 (July 2, 2019): 244–52. http://dx.doi.org/10.1177/0284185119856887.

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Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.

Sahoo, Prativa, Russell C. Rockne, Alexander Jung, Pradeep K. Gupta, Ram K. S. Rathore, and Rakesh K. Gupta. "Synthetic Apparent Diffusion Coefficient for High b-Value Diffusion-Weighted MRI in Prostate." Prostate Cancer 2020 (February 10, 2020): 1–7. http://dx.doi.org/10.1155/2020/5091218.

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Purpose. It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-values is challenging as it commonly suffers from low signal-to-noise ratio (SNR), distortion, and longer scan time. The aim of our study was to develop a technique for quantification of apparent diffusion coefficient (ADC) for higher b-values from lower b-value DW images. Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value was computed using a log-linear model. Contrast ratio (CR) between prostate lesion and normal tissue on synthetic DWI (sDWI) was computed and compared with original DWI and ADC images. Results. No significant difference was observed between actual ADC and sADC for b-2000 in all prostate lesions. However, CR increased significantly (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.0116, independent t-test). Mean (±standard deviation) of sADC of malignant lesions was 0.601 ± 0.06 and for benign lesions was 0.92 ± 0.09 (10−3 mm2/s). Discussion/Conclusion. Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.

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Дисертації з теми "Coefficient de Diffusion Apparent (ADC)":

Onishi, Natsuko. "Apparent Diffusion Coefficient as a Potential Surrogate Marker for Ki-67 Index in Mucinous Breast Carcinoma." 京都大学 (Kyoto University), 2017. http://hdl.handle.net/2433/225449.

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Kuwahara, Ryo. "A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient." Kyoto University, 2020. http://hdl.handle.net/2433/253483.

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Flötotto, Felix [Verfasser], and Christian [Akademischer Betreuer] Habermann. "Bestimmung des Einflusses von Alter und des Zigarettenkonsums auf die erhobenen ADC-Werte (apparent-diffusion-coefficient) der Glandula submandibularis / Felix Flötotto. Betreuer: Christian Habermann." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2013. http://d-nb.info/1045024112/34.

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Rabaszowski, Svenja [Verfasser], Gerald [Gutachter] Antoch, and Hans-Jürgen [Gutachter] Laws. "Diffusionswichtung und der Apparent Diffusion Coefficient (ADC) zur Diagnostik und Differenzierung von Bauchtumoren bei pädiatrischen Patienten / Svenja Rabaszowski ; Gutachter: Gerald Antoch, Hans-Jürgen Laws." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2021. http://d-nb.info/1239893736/34.

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Jaouen, Tristan. "Caractérisation du cancer de la prostate de haut grade à l’IRM multiparamétrique à l’aide d’un système de diagnostic assisté par ordinateur basé sur la radiomique et utilisé comme lecteur autonome ou comme second lecteur." Electronic Thesis or Diss., Lyon, 2022. http://www.theses.fr/2022LYSE1140.

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Nous avons développé un système de diagnostic assisté par ordinateur (CAD) basé sur des régions d'intérêt pour caractériser le cancer de la prostate avec un grade de l'International Society of Urological Pathology (ISUP) ≥2 lors d'une IRM multiparamétrique (IRM-mp). Les paramètres de l'image provenant de 2 jeux de données multi-constructeurs de 265 IRM pré-prostatectomie et 112 IRM pré-biopsie ont été combinés en utilisant la régression logistique. Les meilleurs modèles contenaient le 2e percentile d’ADC (ADC2) et le taux de rehaussement normalisé (WI) dans la zone périphérique (ZP) et le 25e percentile d'ADC (ADC25) dans la zone de transition (ZT). Ils ont été associés dans le système CAD. Le CAD a été évalué rétrospectivement sur 2 jeux de données multi-constructeurs contenant respectivement 158 et 105 IRM pré-biopsie de notre institution (test interne) et d'une autre institution (test externe). Deux radiologues ont indépendamment décrit les lésions ciblées par la biopsie. Le score PI-RADSv2 (Prostate Imaging-Reporting and Data System version 2) attribué prospectivement lors de la biopsie et le score CAD ont été comparés aux résultats de la biopsie. A l’échelle des patients, les aires sous la courbe Receiver Operating Characteristic (AUC) du score PI-RADSv2 étaient de 82% (IC 95% : 74-87) et 85% (IC 95% : 79-91) dans les jeux de données de test interne et externe respectivement. Pour les deux radiologues, le score CAD avait des AUC similaires dans les jeux de données interne (82%, IC 95% : 76-89, p=1 ; 84%, IC 95% : 78-91, p=1) et externe (82%, IC 95% : 76-89, p=0.82 ; 86%, IC 95% : 79-93, p=1). La combinaison du PI-RADSv2 et du CAD aurait pu éviter 41 à 52% des biopsies tout en manquant 6 à 10% des cancers ISUP≥2. Le système CAD a confirmé sa robustesse dans une étude multicentrique impliquant 22 scanners et des protocoles d'imagerie très hétérogènes. Dans l'analyse par patient, le CAD et le PI-RADSv2 avaient des performances similaires en termes d’AUC (76%, IC 95% : 70-82 contre 79%, IC 95% : 73-86 ; p=0.34) et de sensibilité (86%, IC 95% : 76-96 contre 89%, IC 95% : 79-98 pour le PI-RADSv2≥4). La spécificité du CAD (62%, IC 95% : 53-70 contre 49% ; IC 95% : 39-59 pour le PI-RADSv2≥4) permettait une complémentarité avec le score PI-RADSv2 pour potentiellement éviter 50% des biopsies, tout en manquant 13% des cancers ISUP≥2. Ces résultats étaient similaires à ceux rapportés dans les cohortes de test issues d’un unique centre et ont ouvert la voie à de nouvelles applications du CAD. Le CAD a d’abord permis une bonne discrimination des cancers ISUP≥2 chez des patients placés en surveillance active. Son AUC (80% ; IC 95% : 74-86) était similaire à celle du score PI-RADSv2 attribué prospectivement par des uro-radiologues spécialisés (81%, IC 95% : 74-87 ; p=0.96). Le CAD était plus spécifique que les scores PI-RADS≥3 (p<0.001) et PI-RADS≥4 (p<0.001). Il pourrait offrir une solution pour sélectionner les patients pouvant éviter sans risque une biopsie de confirmation ou de suivi dans le cadre de leur surveillance active (25%). Il manquerait alors 5% des cancers ISUP≥2. Le CAD a enfin été confronté aux IRM-mp pré-prostatectomie de 56 patients japonais, issus d’une population qui est géographiquement éloignée de sa population d’entraînement et qui intéresse de par ses faibles taux d’incidence et de mortalité du cancer de la prostate. Son AUC était alors similaire au score PI-RADSv2 attribué par un radiologue expérimenté dans la ZP (80%, IC 95% : 71-90 contre 80%, IC 95% : 71-89 ; p=0.886) et dans la ZT (79%, IC 95% : 66-90 contre 93%, 95%CI : 82-96 ; p=0.051). Ces résultats prometteurs et robustes sur des jeux de données hétérogènes suggèrent que le CAD pourrait être utilisée dans la routine clinique quotidienne comme un second lecteur pour aider à sélectionner les patients pouvant éviter la biopsie en toute sécurité. Ce CAD pourrait aider les lecteurs moins expérimentés à caractériser les lésions de la prostate
We developed a region of interest-based (ROIs) computer-aided diagnosis system (CAD) to characterize International Society of Urological Pathology grade (ISUP) ≥2 prostate cancers at multiparametric MRI (mp-MRI). Image parameters from two multi-vendor datasets of 265 pre-prostatectomy and 112 pre-biopsy MRIs were combined using logistic regression. The best models used the ADC 2nd percentile (ADC2) and normalized wash-in rate (WI) in the peripheral zone (PZ) and the ADC 25th percentile (ADC25) in the transition zone (TZ). They were combined in the CAD system. The CAD was retrospectively assessed on two multi-vendor datasets containing respectively 158 and 105 pre-biopsy MRIs from our institution (internal test dataset) and another institution (external test dataset). Two radiologists independently outlined lesions targeted at biopsy. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score prospectively assigned at biopsy and the CAD score were compared to biopsy findings. At patient level, the areas under the Receiver Operating Characteristic curve (AUC) of the PI-RADSv2 score were 82% (95% CI: 74-87) and 85% (95% CI: 79-91) in the internal and external test datasets respectively. For both radiologists, the CAD score had similar AUC results in the internal (82%, 95% CI: 76-89, p=1; 84%, 95% CI: 78-91, p=1) and external (82%, 95% CI: 76-89, p=0.82; 86%, 95% CI: 79-93, p=1) test datasets. Combining PI-RADSv2 and CAD findings could have avoided 41-52% of biopsies while missing 6-10% of ISUP≥2 cancers. The CAD system confirmed its robustness showing good discrimination of ISUP ≥2 cancers in a multicentric study involving 22 different scanners with highly heterogeneous image protocols. In per patient analysis, the CAD and the PI-RADSv2 had similar AUC values (76%, 95% CI: 70-82 vs 79%, 95% CI: 73-86; p=0.34) and sensitivities (86%, 95% CI: 76-96 vs 89%, 95% CI: 79-98 for PI-RADSv2 ≥4). The specificity of the CAD (62%, 95% CI: 53-70 vs 49%, 95% CI: 39-59 for PI-RADSv2 ≥4) could be used to complement the PI-RADSv2 score and potentially avoid 50% of biopsies, while missing 13% of ISUP ≥2 cancers. These findings were very similar to those reported in the single center test cohorts. Given its robustness, the CAD could then be exploited in more specific applications. The CAD first provided good discrimination of ISUP ≥2 cancers in patients under Active Surveillance. Its AUC (80%, 95% CI: 74-86) was similar to that of the PI-RADS score prospectively assigned by specialized uro-radiologists at the time of biopsy (81%, 95% CI: 74-87; p=0.96). After dichotomization, the CAD was more specific than the PI-RADS ≥3 (p<0.001) and the PI-RADS ≥4 scores (p<0.001). It could offer a solution to select patients who could safely avoid confirmatory or follow-up biopsy during Active Surveillance (25%), while missing 5% of ISUP≥2 cancers. Finally, the CAD was tested with the pre-prostatectomy mp-MRIs of 56 Japanese patients, from a population which is geographically distant from its training population and which is of interest because of its low prostate cancer incidence and mortality. The CAD obtained an AUC similar to the PI-RADSv2 score assigned by an experience radiologist in the PZ (80%, 95% CI: 71-90 vs 80%, 95% CI: 71-89; p=0.886) and in the TZ (79%, 95% CI: 66-90 vs 93%, 95%CI: 82-96; p=0.051). These promising and robust results across heterogeneous datasets suggest that the CAD could be used in clinical routine as a second opinion reader to help select the patients who could safely avoid biopsy. This CAD may assist less experience readers in the characterization of prostate lesions

Moraes, M?rcia Cristina Gon?alves de Oliveira. "O estudo da acur?cia da resson?ncia magn?tica multiparam?trica no diagn?stico do c?ncer de pr?stata." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2017. http://tede2.pucrs.br/tede2/handle/tede/8227.

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Abstract: Today, the incidence of prostate cancer is considered high, however, unlike other malignant tumours, there is an expressive number of cases in which prostate cancer does not progress to clinical disease. The management of patients with prostate cancer should be individually fitted due to the broad behaviour spectrum of this cancer, ranging from low grade tumours with low aggressive biological characteristics to high grade tumours with metastatic capacity. The possibility of predicting the future behavior of the disease allows the selection of the most appropriate conduct for each case. Studies have shown that mpMRI (multiparametric Magnetic Resonance Imaging) has a high negative predictive value for clinically significant prostate cancer, indicating that its application as a screening method and as assessment method of disease progression is promising. To standardize the protocols and reports of prostate mpMRI, the PI-RADS v2 (Prostate Imaging Reporting and Data System version 2) was launched in 2015. Multiparametric Magnetic Resonance Imaging standardized by PI-RADSv2 has been taking a prominent place in the management of prostate cancer, but the specificity and positive predictive value still need to be improved. Purpose: To assess whether the ADC (Apparent diffusion coefficient) value and tumour ADC ratio associated with PI-RADS v2 may increase accuracy in predicting clinically significant prostate cancer. Materials and methods: 91 individuals with suspected prostate cancer were retrospectively studied through mpMRI imaging standardized by PI-RADS v2, obtaining the ADC value from the tumour and the contralateral tissue. The findings were correlated to anatomopathological study (biopsy, prostatectomy or transurethral resection). Results: Accuracy, sensitivity, specificity, positive predictive value and negative predictive value for the consensus between the two reviewers using PI-RADS v2, category 3 associated with categories 4 and 5 for the detection of clinically significant cancer were 70.3%, 97.4%, 50.9%, 58.7% and 96.4% (p <0.001), respectively. The association of the ADC value (<0.795x10-3) to categories 3, 4 and 5 of the PI-RADSv2, in turn, demonstrated accuracy, specificity and positive predictive value of 78.9%, 84.9% and 76.5%; and the association with the tumour ADC ratio (<0.62) presented 77.5%, 86.5% and 77.4% of accuracy, specificity and positive predictive value, respectively. Conclusion: The association of the ADC value and the tumour ADC ratio to the PI-RADS v2 in mpMRI increases the accuracy, specificity and positive predictive value in the detection of aggressive prostate cancer, and may help in the screening of individuals who would undergo invasive procedures and radical therapy, or conservative management, as active surveillance or watchful waiting.
Introdu??o: ? considerada alta a incid?ncia de c?ncer de pr?stata na atualidade, contudo, diferentemente de outras neoplasias, existe um n?mero expressivo de casos em que o c?ncer de pr?stata n?o evolui para a doen?a cl?nica. Por este motivo, o manejo dos pacientes com neoplasia prost?tica deve ser moldado individualmente face ao amplo espectro que varia desde tumores de baixo grau, com caracter?sticas biol?gicas de baixa agressividade, a tumores de alto grau, com capacidade metast?tica. A possibilidade de prever o comportamento futuro da doen?a permite a sele??o da conduta mais adequada para cada caso. Estudos vem comprovando que a Resson?ncia Magn?tica multiparam?trica (RMmp) apresenta um alto valor preditivo negativo para o c?ncer de pr?stata com signific?ncia cl?nica, indicando que sua aplica??o como m?todo de triagem e na avalia??o da progress?o da doen?a ? promissora. Para padronizar os protocolos e os relat?rios da RMmp da pr?stata foi lan?ado em 2015 o PI-RADS v2 (?Prostate Imaging Reporting and Data System? vers?o 2). A RMmp padronizada pelo PI-RADS v2 vem assumindo um lugar de destaque no manejo do c?ncer de pr?stata, contudo, ainda s?o considerados baixos a Especificidade e o Valor Preditivo Positivo. Objetivos: Avaliar se o valor de ADC (?Apparent diffusion coefficient? = Coeficiente de Difus?o Aparente) e a raz?o tumoral do ADC associados ao PI-RADS v2 podem aumentar a acur?cia da RMmp na predi??o do c?ncer de pr?stata com signific?ncia clinica. Materiais e m?todos: Foram estudados retrospectivamente 91 indiv?duos com suspeita de c?ncer de pr?stata, submetidos a RMmp padronizada pelo PI-RADS v2, obtendo-se o ADC quantitativo da les?o e do tecido contralateral. Os achados foram correlacionados ao estudo anatomopatol?gico (bi?psia, prostatectomia ou ressec??o transuretral). Resultados: A acur?cia, sensibilidade, especificidade, valor preditivo positivo e valor preditivo negativo para o consenso entre os dois avaliadores utilizando a RMmp padronizada pelo PI-RADS v2, com a categoria 3 associada as categorias 4 e 5 para a detec??o do c?ncer com signific?ncia cl?nica foram 70,3%; 97,4%; 50,9%; 58,7% e 96,4% (p<0,001), respectivamente. A associa??o do valor do ADC (<0,795x10-3) ?s categorias 3, 4 e 5 do PI-RADS v2, por sua vez, demonstrou acur?cia, especificidade e valor preditivo positivo de 78,9%; 84,9% e 76,5%; e a associa??o com a raz?o tumoral do ADC (< 0,62), apresentou 77,5%; 86,5% e 77,4% de acur?cia, especificidade e valor preditivo positivo, respectivamente. Conclus?o: A associa??o do valor do ADC e da raz?o tumoral do ADC ao PI-RADS v2 na RMmp aumenta a acur?cia, especificidade e valor preditivo positivo na detec??o do c?ncer agressivo da pr?stata, podendo auxiliar na triagem dos indiv?duos e na decis?o entre a conduta agressiva, com procedimentos invasivos e terapia radical, ou a conduta conservadora, com vigil?ncia ativa ou observa??o.

Demir, Ayhan. "Apport de l'imagerie de diffusion avec calcul du coefficient apparent de diffusion et du tenseur de diffusion dans la myélopathie cervicarthrosique." Bordeaux 2, 2000. http://www.theses.fr/2000BOR23058.

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Silva, Matthew S. "NMR characterization of changes in the apparent diffusion coefficient of water following transient cerebral ischemia." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0327102-221251.

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Iima, Mami. "Apparent Diffusion Coefficient as an MR Imaging Biomarker of Low-Risk Ductal Carcinoma in Situ: A Pilot Study." Kyoto University, 2014. http://hdl.handle.net/2433/188640.

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Gauthier, Yvan. "Measurement of the apparent diffusion coefficient of water in white matter using magnetic resonance imaging, a phantom study." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0016/MQ48500.pdf.

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Частини книг з теми "Coefficient de Diffusion Apparent (ADC)":

Fiebach, J. B., P. D. Schellinger, S. Heiland, and K. Sartor. "Conventional MRI, Diffusion-weighted MRI (DWI) and Apparent Diffusion Coefficient (ADC)." In Stroke MRI, 13–21. Heidelberg: Steinkopff, 2003. http://dx.doi.org/10.1007/978-3-642-57387-3_4.

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Jerome, Neil Peter, and João S. Periquito. "Analysis of Renal Diffusion-Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) and Intravoxel Incoherent Motion (IVIM) Models." In Methods in Molecular Biology, 611–35. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_37.

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AbstractAnalysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.

Osawa, T., M. Mase, T. Miyati, H. Kan, K. Demura, H. Kasai, M. Hara, Y. Shibamoto, and K. Yamada. "Delta-ADC (Apparent Diffusion Coefficient) Analysis in Patients with Idiopathic Normal Pressure Hydrocephalus." In Acta Neurochirurgica Supplementum, 197–200. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0956-4_38.

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Ikezaki, Kiyonobu, M. Takahashi, H. Koga, J. Kawai, Z. Kovács, T. Inamura, and M. Fukui. "Apparent Diffusion Coefficient (ADC) and Magnetization Transfer Contrast (MTC) Mapping of Experimental Brain Tumor." In Brain Edema X, 170–72. Vienna: Springer Vienna, 1997. http://dx.doi.org/10.1007/978-3-7091-6837-0_52.

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Jerome, Neil Peter, Anna Caroli, and Alexandra Ljimani. "Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts." In Methods in Molecular Biology, 187–204. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_11.

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AbstractThe specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Chen, Y., W. Guo, Q. Zeng, X. Yan, M. Rao, and Y. Liu. "Apparent Diffusion Coefficient Approximation and Diffusion Anisotropy Characterization in DWI." In Lecture Notes in Computer Science, 246–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11505730_21.

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Yamasaki, Fumiyuki, Kazuhiko Sugiyama, and Kaoru Kurisu. "Brain Tumors: Apparent Diffusion Coefficient at Magnetic Resonance Imaging." In Methods of Cancer Diagnosis, Therapy, and Prognosis, 279–96. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8665-5_22.

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Kim, Yunho, Paul M. Thompson, Arthur W. Toga, Luminita Vese, and Liang Zhan. "HARDI Denoising: Variational Regularization of the Spherical Apparent Diffusion Coefficient sADC." In Lecture Notes in Computer Science, 515–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02498-6_43.

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Righini, A., C. Pierpaoli, J. R. Alger, M. Leonardi, and G. Di Chiro. "Apparent diffusion coefficient alterations associated with experimental complex partial status epilepticus." In Proceedings of the XV Symposium Neuroradiologicum, 259–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79434-6_124.

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Nakamura, Takashi, Misa Sumi, and Marc Van Cauteren. "Salivary Gland Tumors: Preoperative Tissue Characterization with Apparent Diffusion Coefficient Mapping." In Methods of Cancer Diagnosis, Therapy, and Prognosis, 255–69. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3186-0_18.

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Тези доповідей конференцій з теми "Coefficient de Diffusion Apparent (ADC)":

Tulipano, P. Karina, William S. Millar, Celina Imielinska, Xin Liu, Joel Rosiene, and Anthony L. D'Ambrosio. "Quantification of diffusion-weighted images (DWI) and apparent diffusion coefficient maps (ADC) in the detection of acute stroke." In Medical Imaging, edited by Armando Manduca and Amir A. Amini. SPIE, 2006. http://dx.doi.org/10.1117/12.653191.

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Hussein, Khaled, Marwan Nasr Eldin, Hisham Mostafa, and Ahmed Hamed. "Role of MRI Apparent Diffusion Coefficient (ADC) Quantification in the differentiation between benign and malignant pulmonary lesions." In ERS International Congress 2017 abstracts. European Respiratory Society, 2017. http://dx.doi.org/10.1183/1393003.congress-2017.pa3741.

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Wati, Retno, Kouichi Ujita, Ayako Taketomi Takahashi, and Yoshito Tsushima. "Effect of slice position on apparent diffusion coefficient (ADC) value of diffusion weighted whole-body imaging with background body signal suppression (DWIBS): A phantom study." In ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0140503.

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Dietzel, M., S. Ellmann, M. Hammon, M. Saake, R. Janker, M. Uder, and P. Baltzer. "Einsatz des Apparent Diffusion Coefficient (ADC) zur Differentialdiagnose von gutartigen und bösartigen fokalen Leberläsionen (FLL): Auswirkungen des Postprocessing auf die diagnostische Genauigkeit?" In 101. Deutscher Röntgenkongress und 9. Gemeinsamer Kongress der DRG und ÖRG. © Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1703143.

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Dietzel, M., B. Krug, P. Clauser, R. Schulz-Wendtland, M. Hellmich, H. Bickel, E. Wenkel, et al. "Clinical management of patients with suspected breast-cancer: A multicentric comparison of Apparent Diffusion Coefficient Mapping (ADC) and the Kaiser Score (KS)." In Wissenschaftliche Abstracts zur 40. Jahrestagung der Deutschen Gesellschaft für Senologie e.V. (DGS) Interdisziplinär. Kommunikativ. Digital. Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1730151.

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Dwihapsari, Yanurita, Dita Puspita Sari, and Darminto. "The assessment of consistency using penetrometer and apparent diffusion coefficient (ADC) value using diffusion weighted magnetic resonance imaging (DW-MRI) from polyvinyl alcohol (PVA) formed by freezing-thawing cycle." In INTERNATIONAL CONFERENCE ON PHYSICS AND ITS APPLICATIONS: (ICPAP 2011). AIP, 2012. http://dx.doi.org/10.1063/1.4730686.

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Martin, O., P. Heusch, J. Kirchner, N. Bruckmann, F. Nensa, L. Umutlu, G. Antoch, and L. Sawicki. "Gibt es einen Zusammenhang zwischen immunhistochemischen Markern und Grading bei Bronchial-Ca mit dem apparent diffusion coefficient (ADC) und standardized uptake values (SUV) im PET/MRT?" In 100. Deutscher Röntgenkongress. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0037-1682193.

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Diniz, Camila Leal, Rosemar Macedo Sousa Rahal, Ruffo de Freitas-Júnior, Ilse Franco de Oliveira, Cristina Pinto Naldi Ruiz, Paulinelly Messias de Almeida, Marcelo Vilela Lauar, and Lizzi Naldi Ruiz. "Magnetic resonance study of the breast: Diffusion sequence analysis." In Brazilian Breast Cancer Symposium 2023. Mastology, 2023. http://dx.doi.org/10.29289/259453942023v33s1071.

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Objective: The objective of this study was to evaluate the role of the diffusion sequence and respective apparent diffusion coefficient (ADC) map in the study of the breast by magnetic resonance imaging (MRI). Methodology: This is a retrospective cross-sectional study to evaluate additional breast MRI scan sequences. The study included exams of women with indication for MRI referred, by spontaneous demand, to a private supplementary health imaging diagnostic service in the city of Goiânia, GO, from July 2021 to January 2022. The sample was divided according to the BI-RADS® classification into two groups, one with low suspicion for classifications 1, 2, and 3 and another with high suspicion for classifications 0, 4, 5, and 6. The distribution of the sample profile in patients with BI-RADS® MRI low suspicion and high suspicion was tested by applying Pearson’s chi-square test, relative frequency, and absolute frequency. Data were analyzed using the Statistical Package for Social Science (IBM Corporation, Armonk, USA) version 26.0 with a significance level of 5% (p<0.05). This study was approved by the research ethics committee. Results: A total of 307 exams of women with indications for breast MRI participated in the study. Of the exams analyzed, the prevalent clinical indication (33.3%) on images with restriction was a breast lump. Fifty-seven (18.6%) of the exams presented restriction to diffusion with confirmation on the ADC map in the values of b50, b400, and b800. The distribution of the diffusion sequence result in relation to the BI-RADS® MRI low suspicion and high suspicion showed that water restriction was concordant (p<0.01), occurring in 82% of the cases of high suspicion. Conclusion: Diffusion contributes with additional data about images of high suspicion by standard MRI.

Adrada, Beatriz E., Abeer H. Abdelhafez, Benjamin C. Musall, Kenneth R. Hess, Jong Bum Son, Mark D. Pagel, Ken-Pin Hwang, et al. "Abstract P6-02-03: Quantitative apparent diffusion coefficient (ADC) radiomics of tumor and peritumoral regions as potential predictors of treatment response to neoadjuvant chemotherapy (NACT) in triple negative breast cancer (TNBC) patients." In Abstracts: 2019 San Antonio Breast Cancer Symposium; December 10-14, 2019; San Antonio, Texas. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.sabcs19-p6-02-03.

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Das, Saikat. "Low dose radiation and chemotherapy significantly reduces hypoxic cell population in locally advanced cervix cancer-results of a phase II study." In 16th Annual International Conference RGCON. Thieme Medical and Scientific Publishers Private Ltd., 2016. http://dx.doi.org/10.1055/s-0039-1685259.

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Introduction: Tumor hypoxia is one of the major causes of high incidence of treatment failures to chemoradiation which is the standard of care in locally advanced cervical cancer. The necessity of newer treatment options that can circumvent hypoxia is highly relevant in this group. Use of low dose radiation to enhance the efficacy of cell cycle specific chemotherapy by mechanism of chemopotentiation is one of the elegant approaches reported in the literature. We have already published the feasibility, efficacy and tolerance of low dose radiation and chemotherapy in neoadjuvant setting in cervical cancer. In this report we evaluated the role of this novel treatment regimen in reducing the hypoxic tumor cell population in cervical cancer. Methods: Total 24 patients with stage IIB-IIIB squamous cell carcinoma cervix were treated with initial 2 cycles of paclitaxel and carboplatin and concurrent low dose radiotherapy prior to standard chemoradiation. Response was assessed clinically, radiologically (by MRI) and pathologically (four quadrant representative punch biopsy from the cervix) after 3 weeks of neoadjuvant treatment prior to chemoradiation. Immunohistochemistry of HIF-1a was done in the biopsy samples to determine the proportion, intensity and scoring of hypoxic cells. Results: The proportion of positivity of base line HIF-1α was 42% (10 out of 24 patients). Low, moderate and high expressions were seen in 8%, 17% and 17% respectively. We observed nuclear positivity in 20%, and fine granular perinuclear cytoplasmic positivity in 80% cases. We failed to observe any association between expressions of HIF 1α in relation to the distance from blood vessels in tumor cord. The average age of patients in hypoxia positive and negative groups were 51.7 vs 48.36 yrs (p > 0.05). There was no difference of mean hemoglobin level (11.3 to 11.1, p > 0.05.) or MRI based tumor volume at baseline (57.1 vs. 52.4, p > 0.05) in HIF 1α positive and negative groups respectively. Low dose radiation and chemotherapy significantly reduced the tumor volume in bulky hypoxic tumors. The tumor volume reduction rate (TVRR) was significantly higher in hypoxic group (TVRR HIF_neg vs. TVRR HIF_pos 68.9 vs. 86.3, p = 0.02, t-test). There was significant improvement of diffusion MRI derived apparent diffusion coefficient (ADC) in hypoxic tumors with low dose radiation and chemotherapy (0.75 vs. 1.27, p = 0.12, Wilcoxon signed-rank test). Median score of percentage of hypoxic cells after neoadjuvant treatment were significantly higher in patients who developed subsequent local recurrence than the rest of the group (77% vs. 5% p = 0.009, Mann Whitney U test). Conclusion: Overall all HIF 1 positivity was 42% in the present study. A predominantly perinuclear pattern of HIF 1 staining was found in cervix cancer. Low dose radiation and chemotherapy significantly reduced the hypoxic tumor bulk in cervical cancer.

Звіти організацій з теми "Coefficient de Diffusion Apparent (ADC)":

MR (Diffusion-Weighted Imaging (DWI) of the Apparent Diffusion Coefficient (ADC), Clinically Feasible Profile. Chair Michael Boss, Dariya Malyarenko, and Daniel Margolis. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), December 2022. http://dx.doi.org/10.1148/qiba/20221215.

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The goal of a QIBA Profile is to help achieve a useful level of performance for a given biomarker. The Claim (Section 2) describes the biomarker performance and is derived from the body of scientific literature meeting specific requirements, in particular test-retest studies. The Activities (Section 3) contribute to generating the biomarker. Requirements are placed on the Actors that participate in those activities as necessary to achieve the Claim. Assessment Procedures (Section 4) for evaluating specific requirements are defined as needed to ensure acceptable performance. Diffusion-Weighted Imaging (DWI) and the Apparent Diffusion Coefficient (ADC) are being used clinically as qualitative (DWI) and quantitative (ADC) indicators of disease presence, progression or response to treatment. Use of ADC as a robust quantitative biomarker with finite confidence intervals places additional requirements on Sites, Acquisition Devices and Protocols, Field Engineers, Scanner Operators (MR Technologists, Radiologists, Physicists and other Scientists), Image Analysts, Reconstruction Software and Image Analysis Tools. Additionally, due to the intrinsic dependence of measured ADC values on biophysical tissue properties, both the Profile Claims and the associated scan protocols (Section 3.6.2) are organ-specific. All of these are considered Actors involved in Activities of Acquisition Device Pre-delivery and Installation, Subject Handling, Image Data Acquisition, Reconstruction, Registration, ADC map generation, Quality Assurance (QA), Distribution, Analysis, and Interpretation. The requirements addressed in this Profile are focused on achieving ADC values with minimal systematic bias and measurement variability. DISCLAIMER: Technical performance of the MRI system can be assessed using a phantom having known diffusion properties, such as the QIBA DWI phantom. The clinical performance target is to achieve a 95% confidence interval for measurement of ADC with a variable precision depending on the organ being imaged and assuming adequate technical performance requirements are met. While in vivo DWI/ADC measurements have been performed throughout the human body, this Profile focused on four organ systems, namely brain, liver, prostate, and breast as having high clinical utilization of ADC with a sufficient level of statistical evidence to support the Profile Claims derived from the current peer-reviewed literature. In due time, new DWI technologies with proven greater performance levels, as well as more organ systems will be incorporated in future Profiles. This document is intended to help a variety of users: clinicians using this biomarker to aid patient management; imaging staff generating this biomarker; MRI system architects developing related products; purchasers of such products; and investigators designing clinical trials utilizing quantitative diffusion-based imaging endpoints. Note that this document only states requirements specific to DWI to achieve the claim, not requirements that pertain to clinical standard of care. Conforming to this Profile is secondary to proper patient care.