Готові списки джерел за темами / Lungs Cancer Imaging

Добірка наукової літератури з теми "Lungs Cancer Imaging"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Зміст

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Lungs Cancer Imaging".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Статті в журналах з теми "Lungs Cancer Imaging"

1

Principe, Daniel R., Nisha A. Mohindra, Hidayatullah G. Munshi, and Suneel D. Kamath. "Alveolar soft part sarcoma mimics prostate cancer metastasis." Oxford Medical Case Reports 2019, no. 12 (December 2019): 507–9. http://dx.doi.org/10.1093/omcr/omz122.

Повний текст джерела
Анотація:
Abstract A 61-year-old man presented to the oncology clinic with Gleason 9 (4 + 5) prostate cancer. Staging CT showed multiple nodules in both lungs. Since the lung lesions were too small for biopsy, he was started on anti-androgen therapy for suspected metastatic, hormone-sensitive prostate cancer. While his prostate-specific antigen decreased from 32 to <0.1 ng/ml, the multiple lung lesions showed no response on subsequent imaging. The patient presented during follow-up with severe right leg pain, at which time magnetic resonance imaging revealed a large, hyperintense mass in the femur. The mass was resected along with two lung nodules, with pathology demonstrating metastatic alveolar soft part sarcoma. This serves as an important reminder that lesions suspicious for metastases may be due to cancers of multiple primary origins, particularly if the pattern of metastasis is atypical or there is varied response to therapy.
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Bak, So Hyeon, Chohee Kim, Chu Hyun Kim, Yoshiharu Ohno, and Ho Yun Lee. "Magnetic resonance imaging for lung cancer: a state-of-the-art review." Precision and Future Medicine 6, no. 1 (March 31, 2022): 49–77. http://dx.doi.org/10.23838/pfm.2021.00170.

Повний текст джерела
Анотація:
Lung cancer is the leading cause of cancer-related deaths worldwide, and imaging techniques such as chest radiography, computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) play an important role in its diagnosis, staging, treatment planning, post-operative surveillance, and treatment response evaluation. Pulmonary MRI can non-invasively visualize structural and functional abnormalities in the lungs without using ionizing radiation, although it has been suggested that it has less clinical utility than chest radiography, CT, and PET/CT for thoracic diseases, especially lung diseases. With recent advances related to MRI pulse sequences, pulmonary MRI has become practicable in an expanding number of clinical situations. This review article focuses on recent advances in MRI and discusses its clinical applications in the detection, diagnosis, staging, pre-operative evaluation, post-operative surveillance, and treatment response evaluation of lung cancer.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Mohammed, Saara, and Atiba Akii Bua. "Metastatic Breast Cancer to the Urinary Bladder in the Caribbean." Case Reports in Oncology 14, no. 3 (November 8, 2021): 1586–90. http://dx.doi.org/10.1159/000519971.

Повний текст джерела
Анотація:
One of the most common cancers amongst women is breast cancer. The most common metastatic sites are the lymph nodes, lungs, liver, and bone. Metastatic spread to the urinary bladder is rare, and this case, as far as we are aware, is the first reported in the Caribbean. This patient developed urinary symptoms 4 years after her diagnosis of breast cancer. CT imaging showed thickening of the bladder wall, and histology confirmed metastatic breast cancer. As imaging modalities and cancer treatment improve, patients live longer with metastatic disease, and we will potentially see more unusual presentations of metastatic disease.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Jiang, Wenfa, Ganhua Zeng, Shuo Wang, Xiaofeng Wu, and Chenyang Xu. "Application of Deep Learning in Lung Cancer Imaging Diagnosis." Journal of Healthcare Engineering 2022 (January 3, 2022): 1–12. http://dx.doi.org/10.1155/2022/6107940.

Повний текст джерела
Анотація:
Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. It poses a great threat to human health and it mainly occurs in smokers. In our country, with the acceleration of industrialization, environmental pollution, and population aging, the cancer burden of lung cancer is increasing day by day. In the diagnosis of lung cancer, Computed Tomography (CT) images are a fairly common visualization tool. CT images visualize all tissues based on the absorption of X-rays. The diseased parts of the lung are collectively referred to as pulmonary nodules, the shape of nodules is different, and the risk of cancer will vary with the shape of nodules. Computer-aided diagnosis (CAD) is a very suitable method to solve this problem because the computer vision model can quickly scan every part of the CT image of the same quality for analysis and will not be affected by fatigue and emotion. The latest advances in deep learning enable computer vision models to help doctors diagnose various diseases, and in some cases, models have shown greater competitiveness than doctors. Based on the opportunity of technological development, the application of computer vision in medical imaging diagnosis of diseases has important research significance and value. In this paper, we have used a deep learning-based model on CT images of lung cancer and verified its effectiveness in the timely and accurate prediction of lungs disease. The proposed model has three parts: (i) detection of lung nodules, (ii) False Positive Reduction of the detected nodules to filter out “false nodules,” and (iii) classification of benign and malignant lung nodules. Furthermore, different network structures and loss functions were designed and realized at different stages. Additionally, to fine-tune the proposed deep learning-based mode and improve its accuracy in the detection Lung Nodule Detection, Noudule-Net, which is a detection network structure that combines U-Net and RPN, is proposed. Experimental observations have verified that the proposed scheme has exceptionally improved the expected accuracy and precision ratio of the underlined disease.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Khan, Sajad, Shahid Ali, and Muhammad. "Exhaustive Review on Lung Cancers: Novel Technologies." Current Medical Imaging Formerly Current Medical Imaging Reviews 15, no. 9 (October 16, 2019): 873–83. http://dx.doi.org/10.2174/1573405615666181128124528.

Повний текст джерела
Анотація:
Background:Lung cancers or (Bronchogenic-Carcinomas) are the disease in certain parts of the lungs in which irresistible multiplication of abnormal cells leads to the inception of a tumor. Lung cancers consisting of two substantial forms based on the microscopic appearance of tumor cells are: Non-Small-Cell-Lung-Cancer (NSCLC) (80 to 85%) and Small-Cell-Lung-Cancer (SCLC) (15 to 20%).Discussion:Lung cancers are existing luxuriantly across the globe and the most prominent cause of death in advanced countries (USA & UK). There are many causes of lung cancers in which the utmost imperative aspect is the cigarette smoking. During the early stage, there is no perspicuous sign/symptoms but later many symptoms emerge in the infected individual such as insomnia, headache, pain, loss of appetite, fatigue, coughing etc. Lung cancers can be diagnosed in many ways, such as history, physical examination, chest X-rays and biopsy. However, after the diagnosis and confirmation of lung carcinoma, various treatment approaches are existing for curing of cancer in different stages such as surgery, radiation therapy, chemotherapy, and immune therapy. Currently, novel techniques merged that revealed advancements in detection and curing of lung cancer in which mainly includes: microarray analysis, gene expression profiling.Conclusion:Consequently, the purpose of the current analysis is to specify and epitomize the novel literature pertaining to the development of cancerous cells in different parts of the lung, various preeminent approaches of prevention, efficient diagnostic procedure, and treatments along with novel technologies for inhibition of cancerous cell growth in advance stages.
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Chrabaszcz, Karolina, Katarzyna Kaminska, Cai Li Song, Junko Morikawa, Monika Kujdowicz, Ewelina Michalczyk, Marta Smeda, et al. "Fourier Transform Infrared Polarization Contrast Imaging Recognizes Proteins Degradation in Lungs upon Metastasis from Breast Cancer." Cancers 13, no. 2 (January 6, 2021): 162. http://dx.doi.org/10.3390/cancers13020162.

Повний текст джерела
Анотація:
The current understanding of mechanisms underlying the formation of metastatic tumors has required multi-parametric methods. The tissue micro-environment in secondary organs is not easily evaluated due to complex interpretation with existing tools. Here, we demonstrate the detection of structural modifications in proteins using emerging Fourier Transform Infrared (FTIR) imaging combined with light polarization. We investigated lungs affected by breast cancer metastasis in the orthotopic murine model from the pre-metastatic phase, through early micro-metastasis, up to an advanced phase, in which solid tumors are developed in lung parenchyma. The two IR-light polarization techniques revealed, for the first time, the orientational ordering of proteins upon the progression of pulmonary metastasis of breast cancer. Their distribution was complemented by detailed histological examination. Polarized contrast imaging recognised tissue structures of lungs and showed deformations in protein scaffolds induced by inflammatory infiltration, fibrosis, and tumor growth. This effect was recognised by not only changes in absorbance of the spectral bands but also by the band shifts and the appearance of new signals. Therefore, we proposed this approach as a useful tool for evaluation of progressive and irreversible molecular changes that occur sequentially in the metastatic process.
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Kaur, Pawandeep, and Rekha Bhatia. "Development of a Novel Lung Cancer Detection Technique based upon Micro Vessel Density Analysis." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 7 (July 30, 2017): 157. http://dx.doi.org/10.23956/ijarcsse/v7i7/0170.

Повний текст джерела
Анотація:
In the medical field, Image processing methods are widely used. It is a method for the improvement of image, the image which is obtained after processing is useful for earlier detection and various stages of cancer. In cancer tumors such as lung cancer time factor is the important key point because in the targated images of lung cancer time factor is use to discover the abnormality. Basically the development of numerous uncontrolled cells in the tissues create abnormality which later on leads to tumor in lungs. It is necessary to detect lung cancer in earlier stages, if left untreated its growth may spread into other nearby parts of body. For diagnosis, Patients may undergo several imaging tests such as CT scan, Chest X-ray and PET scan.In the existing recognition and detection techniques the Micro vessel density (MVD) analysis is used from which geometrical features are extracted to detect the tumorin lungs. In alternate to this the Gray level co-occurrence matrix (GLCM) may also be used with the geometrical features of the image to obtain more accurate result of lung cancer detection. GLCM features such as image contrast, homogeneity, dissimilarity, energy and correlation is beneficial to obtain results with higher accuracy. On the basis of significant instrument, novel lung cancer prediction framework will be developed.
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Subramanian, Shraddha, Alexes C. Daquinag, Solmaz AghaAmiri, Sukhen C. Ghosh, Ali Azhdarinia, and Mikhail G. Kolonin. "Characterization of Peptides Targeting Metastatic Tumor Cells as Probes for Cancer Detection and Vehicles for Therapy Delivery." Cancer Research 81, no. 22 (October 4, 2021): 5756–64. http://dx.doi.org/10.1158/0008-5472.can-21-1015.

Повний текст джерела
Анотація:
Abstract Metastasis is the leading cause of cancer-related deaths, and metastatic cancers remain largely incurable due to chemoresistance. Biomarkers of metastatic cells are lacking, and probes that could be used to detect and target metastases would be highly valuable. Here we hypothesize that metastatic cancer cells express cell-surface receptors that can be harnessed for identification of molecules homing to metastases. Screening a combinatorial library in a mouse mammary tumor model of spontaneous metastasis identified cyclic peptides with tropism for cancer cells disseminated to the lungs. Two lead peptides, CLRHSSKIC and CRAGVGRGC, bound murine and human cells derived from breast carcinoma and melanoma in culture and were selective for metastatic cells in vivo. In mice, peptide CRAGVGRGC radiolabeled with 67Ga for biodistribution analysis demonstrated selective probe homing to lung metastases. Moreover, systemic administration of 68Ga-labeled CRAGVGRGC enabled noninvasive imaging of lung metastases in mice by PET. A CRAGVGRGC-derived peptide induced apoptosis upon cell internalization in vitro and suppressed metastatic burden in vivo. Colocalization of CLRHSSKIC and CRAGVGRGC with N-cadherin+/E-cadherin− cells indicated that both peptides are selective for cancer cells that have undergone the epithelial-to-mesenchymal transition. We conclude that CRAGVGRGC is useful as a probe to facilitate the development of imaging modalities and therapies targeting metastases. Significance: This study identifies new molecules that bind metastatic cells and demonstrates their application as noninvasive imaging probes and vehicles for cytotoxic therapy delivery in preclinical cancer models.
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Aurélia, Alati, Clavère Pierre, and Leobon Sophie. "Bronchiolitis Obliterans Organizing Pneumonia after Breast Cancer Radiotherapy and letrozole: A Case Report and Literature Review." Archives of Medical Case Reports and Case Study 4, no. 3 (July 21, 2021): 01–05. http://dx.doi.org/10.31579/2694-0248/049.

Повний текст джерела
Анотація:
Objectives: Bronchiolitis obliterans organizing pneumonia occurs with prevalence rate 1–3% after breast conservative treatment in series. In response to radiation of a lung or surrounding tissues, an inflammatory reaction can affect both lungs and is located within the radiation field. Characteristic imaging features include multiple alveolar opacities and diffuse ground-glass shadows. Letrozole may induce iatrogenic organizing pneumonia. Materials and methods: we report the case of a 76-year-old female who underwent conservative treatment for an invasive ductal carcinoma of the left breast. Hypofractionated radiotherapy was delivered with a total dose of 42.5 Gy in 16 sessions of 2.65 Gy using a three-dimensional technique. After the radiotherapy ended letrozole was indicated. Results: Several weeks after the radiotherapy ended and letrozole was introduced, she described a flu-like syndrome. Samples were negative, and there was no improvement after four courses of antibiotics. Imaging suggested bronchiolitis obliterans organizing pneumonia. Her symptomatology lessened after the letrozole was discontinued, and 11 months after radiotherapy finished, her imaging results were clear. Conclusion: Physicians must consider bronchiolitis obliterans organizing pneumonia. Cases may increase with hypofractionated radiation treatment and new drugs. Letrozole may potentiate the risk. Dosimetry may be adapted to the lung and subpleural areas for patients with risk factors and taking adjuvant or concurrent drugs with potential pneumotoxicity.
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Aurélia, Alati, Clavère Pierre, and Leobon Sophie. "Bronchiolitis Obliterans Organizing Pneumonia after Breast Cancer Radiotherapy and letrozole: A Case Report and Literature Review." Archives of Medical Case Reports and Case Study 4, no. 3 (July 21, 2021): 01–05. http://dx.doi.org/10.31579/2692-9392/049.

Повний текст джерела
Анотація:
Objectives: Bronchiolitis obliterans organizing pneumonia occurs with prevalence rate 1–3% after breast conservative treatment in series. In response to radiation of a lung or surrounding tissues, an inflammatory reaction can affect both lungs and is located within the radiation field. Characteristic imaging features include multiple alveolar opacities and diffuse ground-glass shadows. Letrozole may induce iatrogenic organizing pneumonia. Materials and methods: we report the case of a 76-year-old female who underwent conservative treatment for an invasive ductal carcinoma of the left breast. Hypofractionated radiotherapy was delivered with a total dose of 42.5 Gy in 16 sessions of 2.65 Gy using a three-dimensional technique. After the radiotherapy ended letrozole was indicated. Results: Several weeks after the radiotherapy ended and letrozole was introduced, she described a flu-like syndrome. Samples were negative, and there was no improvement after four courses of antibiotics. Imaging suggested bronchiolitis obliterans organizing pneumonia. Her symptomatology lessened after the letrozole was discontinued, and 11 months after radiotherapy finished, her imaging results were clear. Conclusion: Physicians must consider bronchiolitis obliterans organizing pneumonia. Cases may increase with hypofractionated radiation treatment and new drugs. Letrozole may potentiate the risk. Dosimetry may be adapted to the lung and subpleural areas for patients with risk factors and taking adjuvant or concurrent drugs with potential pneumotoxicity.
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Дисертації з теми "Lungs Cancer Imaging"

1

Almeida, Taynná Vernalha Rocha. "Impacto da PET/CT no câncer de pulmão não-pequenas células: contribuição no delineamento tumoral." Universidade Tecnológica Federal do Paraná, 2013. http://repositorio.utfpr.edu.br/jspui/handle/1/679.

Повний текст джерела
Анотація:
Introdução: A definição do volume-alvo macroscópico, principalmente referente a casos de câncer de pulmão, exige o maior número de informações possíveis no que diz respeito à localização, extensão e mobilidade tumoral. A literatura demonstra um importante avanço quando utilizada imagens metabólicas como é o caso da tomografia por emissão de pósitron/tomografia computadorizada (PET/CT), porém a sua aplicação nos planejamentos radioterápicos ainda é muito discutida devido ao seu grau de complexidade. Objetivos: Avaliar o impacto da PET/CT no delineamento tumoral em casos de câncer de pulmão não-pequenas células (CPNPC) e linfonodos regionais. Materiais e Métodos: Foram selecionados retrospectivamente estudos de PET/CT de 26 casos de câncer de pulmão. Todos foram confirmados por biópsia, sendo em sua totalidade CPNPC. Todos os estudos foram realizados em um equipamento de PET/CT dedicado com parâmetros de aquisição idênticos. A interpretação das imagens e posterior delineamento foram realizados por dois médicos experientes, um radioterapeuta e um nuclear/radiologista. Os parâmetros ótimos de visualização foram pré-definidos, sendo mandatórios para os delineamentos. Os delineamentos foram realizados em duas etapas principais. A primeira relacionada ao desenho tumoral somente pela CT e a segunda, após no mínimo duas semanas de descanso visual, referindo-se ao desenho tumoral pela PET/CT. Somente o volume tumoral macroscópico (GTV) e os linfonodos regionais aumentados ou PET positivos foram delineados. Índices de conformidades (IC) foram calculados, tanto interobservadores (11 casos), quanto intra-observador (26 casos). Para a comparação entre observadores e entre delineamentos em relação ao volume, foi considerado o teste não-paramétrico de Wilcoxon. As comparações em relação ao IC foram feitas usando-se o teste t de Student para amostras pareadas. Em todos os testes, valores de p <0,05 indicaram significância estatística. Os dados foram analisados com o programa computacional SPSS® Statistics 17.0 (EUA). Resultados: A análise dos dados demonstrou diferença significativa entre os volumes médios delineados na CT e na PET/CT (p = 0,02), com evidente redução volumétrica no delineamnto por PET/CT. Houve diferença significativa entre os volumes CT delineados pelos dois observadores (p = 0,03) e uma tendência a apresentar diferença significativa entre volumes PET/CT (p = 0,05). A avaliação volumétrica intraobservador foi significativa (p < 0,01) apenas para o médico nuclear/radiologista, com redução de até 51% do volume CT e uma relação entre modalidades de 2,11 ± 0,22. Na análise dos IC, não houveram diferenças significativas entre as duas modalidades de imagem (p = 0,598). A análise dos IC intra-observadores demonstrou que para o radioterapeuta a PET/CT apresenta um impacto de 46% (IC médio = 0,54 ± 0,06), já para o nuclear/radiologista, o impacto foi de 65% (IC médio = 0,35 ± 0,06), representando uma diferença significativa (p = 0,03) em relação ao IC entre o médicos observadores. Para a análise linfonodal a PET/CT apresentou importante diferença na visualização de linfonodos, alterando 10 dos 26 casos, sendo 9 para a positividade apenas na fusão. Conclusão: A PET/CT apresentou significativo impacto no desenho do GTV e linfonodos regionais para casos de CPNPC.
Introduction: The definition of gross target volume, especially concerning cases of lung cancer, requires the greatest amount of information possible with regard to location, tumor size and tumor mobility. The literature demonstrates an important advancement using metabolic images such as PET/CT, however, its application in radiotherapy planning is still controversial due to its complexity. Objectives: To assess the impact of PET/CT in tumor delineation in cases of non-small cell lung cancer and regional lymph nodes as additional findings. Materials and Methods: Retrospectively studies of PET/CT of 26 lung cancer cases were selected. All were confirmed by biopsy, in its entirety NSCLC. All studies were performed on a PET/CT with dedicated acquisition identical parameters. Image interpretation and subsequent delineation were performed by two experienced physicians, one radiotherapist and the another nuclear/radiologist. The optimal parameters display were pre-defined, being mandatory for the designs. Each case received an identification of three random letters to access the medical images to be analyzed. The delineation was made in two main steps. The first reference to the drawing only in tumor CT and the second, after two weeks of visual rest, referring to the drawing on tumor PET/CT. Only the gross tumor volume (GTV) and regional lymph nodes were enlarged or PET + outlined. Conformity index (CI) were calculated both interobserver (11 cases), and intra-observer (26 cases). For comparison between observers and between designs in relation to the volume, was considered the nonparametric Wilcoxon test. Comparisons regarding the conformity index were made using the Student t test for paired samples. To assess the degree of agreement regarding positive lymph nodes were estimated with kappa coefficients of agreement. In all tests, p values <0.05 were considered statistically significant. Data were analyzed with the software SPSS Statistics 17.0 (USA). Results: Data analysis showed significant difference between the average volumes delineated on CT and PET/CT (p = 0.02), with obvious volume reduction. Significant difference between the volumes delineated by CT observars medical distinct classes (p = 0.03) and a tendency to present significant difference between volumes PET / CT (p = 0.05). The intraobserver volumetric evaluation was significant (p <0.001) only for observer 2, being the nuclear medicine physician / radiologist, reducing up to 51% of the volume CT and a relationship between methods of 2.11 ± 0.22. In the analysis of CI, there were no significant differences between the two imaging modalities (p = 0.598).CI analysis showed that intra-observer to observer 1 PET / CT has an impact of 46% (average CI = 0.54 ± 0.06). The viewer 2, the impact was greater, 46% (average IC = 0.39 ± 0.03), representing a difference of opinion regarding the CI (p = 0.03) between the medical classes. To regional lymph nodes with PET/CT revealed an important difference in the visualization of lymph nodes, changing 10 of the 26 cases, 9 to positivity only in the image fusion.Conclusion: PET/CT has a significant impact on the design of the GTV and regional lymph nodes in cases of NSCLC.
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Hochstenbag, Monique. "Imaging in clinical lung cancer staging." [Maastricht] : Maastricht : UPM, Universitaire Pers Maastricht ; University Library, Maastricht University [Host], 2003. http://arno.unimaas.nl/show.cgi?fid=8287.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Al-Ghamdi, Ahmad Hamoud. "Staging of lung cancer by magnetic resonance imaging." Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326783.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Bosmans, Geert. "CT-PET imaging of lung cancer patients for radiotherapy." Maastricht : Maastricht : Universiteit Maastricht ; University Library, Universiteit Maastricht [host], 2007. http://arno.unimaas.nl/show.cgi?fid=9450.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Agrawal, Vishesh. "Quantitative Imaging Analysis of Non-Small Cell Lung Cancer." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:27007763.

Повний текст джерела
Анотація:
Quantitative imaging is a rapidly growing area of interest within the field of bioinformatics and biomarker discovery. Due to the routine nature of medical imaging, there is an abundance of high-quality imaging linked to clinical and genetic data. This data is particularly relevant for cancer patients who receive routine CT imaging for staging and treatment purposes. However, current analysis of tumor imaging is generally limited to two-dimensional diameter measurements and assessment of anatomic disease spread. This conventional tumor-node-metastasis (TNM) staging system stratifies patients to treatment protocols including decisions regarding adjuvant therapy. Recently there have been several studies suggesting that these images contain additional unique information regarding tumor phenotype that can further aid clinical decision-making. In this study I aimed to develop the predictive capability of medical imaging. I employed the principles of quantitative imaging and applied them to patients with non-small cell lung cancer (NSCLC). Quantitative imaging, also termed radiomics, seeks to extract thousands of imaging data points related to tumor shape, size and texture. These data points can potentially be consolidated to develop a tumor signature in the same way that a tumor might contain a genetic signature corresponding to mutational burden. To accomplish this I applied radiomics analyses to patients with early and late stage NSCLC and tested these for correlation with both histopathological data as well as clinical outcomes. Patients with both early and late stage NSCLC were assessed. For locally advanced NSCLC (LA-NSCLC), I analyzed patients treated with preoperative chemoradiation followed by surgical resection. To assess early stage NSCLC, I analyzed patients treated with stereotactic body radiation therapy (SBRT). Quantitative imaging features were extracted from CT imaging obtained prior to chemoradiation and post-chemoradiation prior to surgical resection. For patients who underwent SBRT, quantitative features were extracted from cone-beam CTs (CBCT) at multiple time points during therapy. Univariate and multivariate logistic regression were used to determine association with pathologic response. Concordance-index and Kaplan-Meier analyses were applied to time dependent endpoints of overall survival, locoregional recurrence-free and distant metastasis. In this study, 127 LA-NSCLC patients were identified and treated with preoperative chemoradiation and surgical resection. 99 SBRT patients were identified in a separate aim of this study. Reduction of CT-defined tumor volume (OR 1.06 [1.02-1.09], p=0.002) as continuous variables per percentage point was associated with pathologic complete response (pCR) and locoregional recurrence (LRR). Conventional response assessment determined by diameter (p=0.213) was not associated with pCR or any survival endpoints. Seven texture features on pre-treatment tumor imaging were associated with worse pathologic outcome (AUC 0.61-0.66). Quantitative assessment of lymph node burden demonstrated that pre-treatment and post-treatment volumes are significantly associated with both OS and LRR (CI 0.62-0.72). Textural analyses of these lymph nodes further identified 3 unique pre-treatment and 7 unique post-treatment features significantly associated with either LRR, DM or OS. Finally early volume change showed associated with overall survival in CBCT scans of early NSCLC. Quantitative assessment of NSCLC is thus strongly associated with pathologic response and survival endpoints. In contrast, conventional imaging response assessment was not predictive of pathologic response or survival endpoints. This study demonstrates the novel application of radiomics to lymph node texture, CBCT volume and patients undergoing neoadjuvant therapy for NSCLC. These examples highlight the potential within the rapidly growing field of quantitative imaging to better describe tumor phenotype. These results provide evidence to the growing radioimics literature that there is significant association between imaging, pathology and clinical outcomes. Further exploration will allow for more complete models describing tumor imaging phoentype with clinical outcomes.
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Bianchi, Andrea. "Magnetic resonance imaging techniques for pre-clinical lung imaging." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0060/document.

Повний текст джерела
Анотація:
Dans ce travail, les s´séquences Imagerie par Résonance Magnétique (IRM) radiales à temps d’écho ultra-court (UTE) sont analysées pour évaluer leur potentiel dans l’étude non-invasive de différents modèles expérimentaux de maladies pulmonaires chez la souris. Chez le petit animal, les séquences radiales UTE peuvent efficacement limiter l’impact négatif sur la qualité de l’image dû au déphasage rapide des spins causé par les nombreuses interfaces air/tissu. En plus, les séquences radiales UTE sont moins sensibles aux artefacts de mouvement par rapport aux séquences Cartésiennes classiques. En conséquence, chez le petit animal, les séquences radiales UTE peuvent permettre d’obtenir des images du poumon avec une résolution bien inférieure au millimètre avec des rapports signal/bruit importants dans le parenchyme pulmonaire, tout en travaillant en conditions physiologiques (animaux en respiration spontanée). Dans cette thèse, il sera démontré que les séquences d’IRM protonique UTE sont outils efficaces dans l’étude quantitative et non-invasive de différents marqueurs distinctifs de certaines pathologies pulmonaires d’intérêt général. Les protocoles développés serontsimples, rapides et non-invasifs, faciles à implémenter, avec une interférence minimale sur la pathologie pulmonaire étudiée et, en définitive, potentiellement applicables chez l’homme. Il sera ainsi démontré que l’emploi des agents de contraste, administrés via les voies aériennes, permet d’augmenter la sensibilité des protocoles développés. Parallèlement, dans cette thèse des protocoles suffisamment flexibles seront implémentés afin de permettre l’étude d’un agent de contraste paramagnétique générique pour des applications aux poumons
In this work, ultra-short echo time (UTE) Magnetic Resonance Imaging (MRI) sequences are investigated as flexible tools for the noninvasive study of experimental models of lung diseases in mice. In small animals radial UTE sequences can indeed efficiently limit the negative impact on lung image quality due to the fast spin dephasing caused by the multiple air/tissue interfaces. In addition, radial UTE sequences are less sensitive to motion artifacts compared to standard Cartesian acquisitions. As a result, radial UTE acquisitions can provide lung images in small animals at sub-millimetric resolution with significant signal to noise ratio in the lung parenchyma, while working with physiological conditions (freely-breathing animals). In this thesis, UTE proton MRI sequences were shown to be efficient instruments to quantitatively investigate a number of hallmarks in longitudinal models of relevant lung diseases with minimal interference with the lung pathophysiology, employing easilyimplementable fast protocols. The synergic use of positive contrast agents, along with anadvantageous administration modality, was shown to be a valuable help in the increase of sensitivity of UTE MRI. At the same time, UTE MRI was shown to be an extremely useful and efficacious sequence for studying positive contrast agents in lungs
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Hellström, Terese. "Deep-learning based prediction model for dose distributions in lung cancer patients." Thesis, Stockholms universitet, Fysikum, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-196891.

Повний текст джерела
Анотація:
Background To combat one of the leading causes of death worldwide, lung cancer treatment techniques and modalities are advancing, and the treatment options are becoming increasingly individualized. Modern cancer treatment includes the option for the patient to be treated with proton therapy, which can in some cases spare healthy tissue from excessive dose better than conventional photon radiotherapy. However, to assess the benefit of proton therapy compared to photon therapy, it is necessary to make both treatment plans to get information about the Tumour Control Probability (TCP) and the Normal Tissue Complication Probability (NTCP). This requires excessive treatment planning time and increases the workload for planners.  Aim This project aims to investigate the possibility for automated prediction of the treatment dose distribution using a deep learning network for lung cancer patients treated with photon radiotherapy. This is an initial step towards decreasing the overall planning time and would allow for efficient estimation of the NTCP for each treatment plan and lower the workload of treatment planning technicians. The purpose of the current work was also to understand which features of the input data and training specifics were essential for producing accurate predictions.  Methods Three different deep learning networks were developed to assess the difference in performance based on the complexity of the input for the network. The deep learning models were applied for predictions of the dose distribution of lung cancer treatment and used data from 95 patient treatments. The networks were trained with a U-net architecture using input data from the planning Computed Tomography (CT) and volume contours to produce an output of the dose distribution of the same image size. The network performance was evaluated based on the error of the predicted mean dose to Organs At Risk (OAR) as well as the shape of the predicted Dose-Volume Histogram (DVH) and individual dose distributions.  Results  The optimal input combination was the CT scan and lung, mediastinum envelope and Planning Target Volume (PTV) contours. The model predictions showed a homogenous dose distribution over the PTV with a steep fall-off seen in the DVH. However, the dose distributions had a blurred appearance and the predictions of the doses to the OARs were therefore not as accurate as of the doses to the PTV compared to the manual treatment plans. The performance of the network trained with the Houndsfield Unit input of the CT scan had similar performance as the network trained without it.  Conclusions As one of the novel attempts to assess the potential for a deep learning-based prediction model for the dose distribution based on minimal input, this study shows promising results. To develop this kind of model further a larger data set would be needed and the training method could be expanded as a generative adversarial network or as a more developed U-net network.
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Wang, Jiali. "Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images." FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/96.

Повний текст джерела
Анотація:
Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Trigonis, Ioannis. "Imaging tumour proliferation with [F-18]fluorothymidine PET in patients with non-small cell lung cancer in response to radiotherapy." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/imaging-tumour-proliferation-with-f18fluorothymidine-pet-in-patients-with-nonsmall-cell-lung-cancer-in-response-to-radiotherapy(8d342eac-55fb-4fc0-95e6-ebe11ffd319f).html.

Повний текст джерела
Анотація:
Improved radiotherapy (RT) outcomes may be facilitated through monitoring of physiological processes implicated in radio-resistance such as proliferation. To this end, we studied 16 patients with non-small cell lung cancer with dynamic 3'-deoxy-3'-fluorothymidine (FLT) PET-CT before and after a week of radical RT. In absence of changes in primary tumour volume manually delineated on CT, RT induced a significant, moderately variable decrease in maximum and mean standard uptake values (SUVmax and SUVmean) of the order of 25%. Metastatic nodes showed a larger relative decrease in uptake approximating 40% associated with volumetric regression and only partially accountable by partial volume effect. Implementation of different segmentation approaches including manual delineation by a second operator and PET-based semi-automatic algorithms [two fixed thresholds, 2/3-cluster Fuzzy C-means (FCM-2, FCM-3) and 2/3-cluster fuzzy locally adaptive Bayesian algorithm (FLAB-2, FLAB-3)] yielded substantially different volumes and SUVs but consistent SUV responses. Reproducibility comparison favoured manual delineation, while thresholding delivered poor volumetric robustness and no apparent SUV reproducibility advantage over SUVmax or SUVpeak. FCM-2/FLAB-2 demonstrated intermediate reproducibility. In contrast to anatomical volumes, metabolic volumes exhibited significant increases with treatment, which for FLAB-2 correlated with changes of intratumoural uptake heterogeneity quantified by the coefficient of variation. Normal tissue analysis revealed an anterior-posterior gradient of lung uptake and an association of baseline marrow SUV with type/timing of neo-adjuvant chemotherapy. RT induced a dramatic (≈-76%), sharply demarcated marrow SUV decline in response to a minimum of 5Gy and a small (≈-20%), consistent decline in normal lung SUV. Kinetic analysis revealed a significant increase in the tumour delivery constant K1 (+32%) and a decrease in Ki/K1, larger (-36%) and more variable than the Ki (-26%) and SUV responses. Furthermore, despite baseline independence, we found a strong negative correlation between Ki/K1 and K1 at the response level. Kinetic analysis of the most uptake-avid tumour cluster extracted with FCM-3 yielded similar results with attenuated changes in delivery and retention. Overall, we found that RT induces early measurable changes in lung tumour FLT uptake. Spatial analysis indicated a variable dissociation of anatomical and metabolic volumes, while temporal analysis showed a variable antagonistic effect on delivery and phosphorylation, indicating that SUV analysis may misrepresent the magnitude and variability of RT anti-proliferative effect.
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Perrin, Rosalind Lucy. "The application of PET/CT imaging data to external beam radiotherapy planning in lung cancer." Thesis, Institute of Cancer Research (University Of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538270.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Книги з теми "Lungs Cancer Imaging"

1

Ravenel, James G., ed. Lung Cancer Imaging. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

1948-, Müller Nestor Luiz, and Naidich David P, eds. High-resolution CT of the lung. 2nd ed. Philadelphia: Lippincott-Raven, 1996.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

1948-, Müller Nestor Luiz, and Naidich David P, eds. High-resolution CT of the lung. New York: Raven Press, 1992.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

1948-, Müller Nestor Luiz, and Naidich David P, eds. High-resolution CT of the lung. 3rd ed. Philadelphia: Lippincott Williams & Wilkins, 2001.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

1948-, Müller Nestor Luiz, and Naidich David P, eds. High-resolution CT of the lung. 4th ed. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins Health, 2008.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Medical tests sourcebook: Basic consumer health information about preventive care guidelines, routine health screenings, home-use tests, blood, stool, and urine tests, genetic testing, biopsies, endoscopic exams, and imaging tests, such as X-ray, ultrasound, computed tomography (ct), and nuclear and magnetic resonance imaging (MRI) exams; along with facts about diagnostic tests for allergies, cancer, diabetes, heart and lung disease, infertility, osteoporosis, sleep problems, and other specific conditions, a glossary of related terms, and directories of additional resources. 4th ed. Detroit, MI: Omnigraphics, 2011.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Medical tests sourcebook: Basic consumer health information about preventive care guidelines, routine health screenings, home-use tests, blood, stool, and urine tests, genetic testing, biopsies, endoscopic exams, and imaging tests, such as X-ray, ultrasound, computed tomography (CT), and nuclear and magnetic resonance imaging (MRI) exams; along with facts about diagnostic tests for allergies, cancer, diabetes, heart and lung disease, infertility, osteoporosis, sleep problems, and other specific conditions, a glossary of related terms, and directories of additional resources. Detroit, MI: Omnigraphics, Inc., 2015.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Ravenel, James G. Lung Cancer Imaging. Humana, 2016.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Ravenel, James G. Lung Cancer Imaging. Humana, 2013.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Ravenel, James G. Lung Cancer Imaging. Humana Press, 2013.

Знайти повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел

Частини книг з теми "Lungs Cancer Imaging"

1

Cuellar, Sonia L. Betancourt, Edith M. Marom, and Jeremy J. Erasmus. "Imaging Lung Cancer." In Lung Cancer, 191–201. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118468791.ch11.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Hazelton, Todd R., and Frank W. Walsh. "Lung Cancer." In Clinically Oriented Pulmonary Imaging, 29–39. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-542-8_3.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Kosmidis, Paris A. "Lung Cancer." In Imaging in Clinical Oncology, 231. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-68873-2_28.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Kim, E. E. "Lung Cancer." In Nuclear Imaging of the Chest, 197–212. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-80387-1_8.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Bellomi, Massimo, Tommaso De Pas, Adele Tessitore, and Lorenzo Preda. "Lung Cancer." In Imaging Tumor Response to Therapy, 109–25. Milano: Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2613-1_7.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Wheless, Lee, James Brashears, and Anthony J. Alberg. "Epidemiology of Lung Cancer." In Lung Cancer Imaging, 1–15. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_1.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Cooper, S. Lewis, and Anand Sharma. "Radiotherapy in Lung Cancer." In Lung Cancer Imaging, 137–52. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_12.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Ravenel, James G. "Screening for Lung Cancer." In Lung Cancer Imaging, 23–38. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_3.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Scalzetti, Ernest M. "Radiofrequency Ablation of Primary Lung Cancer." In Lung Cancer Imaging, 111–23. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_10.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Shirai, Keisuke, George R. Simon, and Carol A. Sherman. "Systemic Therapy for Lung Cancer." In Lung Cancer Imaging, 125–35. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-60761-620-7_11.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Lungs Cancer Imaging"

1

Svanberg, Emilie Krite, Patrik Lundin, Marcus Larsson, Jonas Åkeson, Katarina Svanberg, Sune Svanberg, Vineta Fellman, and Stefan Andersson-Engels. "Non-invasive monitoring of oxygen in the lungs of newborn infants using diode laser spectroscopy." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jtu3a.53.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Wang, Lulu, and Hu Peng. "A Feasibility Study of Lung Cancer Detection Using Holographic Microwave Imaging." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70062.

Повний текст джерела
Анотація:
This paper presents the feasibility of using holographic microwave imaging (HMI) method for diagnosing lung tumour. A numerical imaging system is developed to evaluate the working principle, which includes a realistic CT-based thorax model. Results show that various small lung tumours with arbitrary shapes, sizes and locations can be identified in the reconstructed images. The HMI approach has a potential for lung cancer detection.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Salvador, Anna Dias, Gabriela Ramos Alves, Enaldo Melo Lima, Bernardo Ferreira Paula Ricardo, and Henrique Moraes Salvador Silva. "METASTATIC THYMOMA OF THE BREAST – CASE REPORT." In Scientifc papers of XXIII Brazilian Breast Congress - 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s1018.

Повний текст джерела
Анотація:
Introduction: Thymomas are rare malignant epithelial neoplasms arising in the thymus. These tumors are commonly located in the prevascular mediastinum but can also be found in other regions of the mediastinum, neck, pulmonary hilum, thyroid gland, lungs, pleura, or pericardium. This disease could be suspected as an incidental finding identified on imaging, local thoracic symptoms or due to a paraneoplastic syndrome. Pleural or pericardial effusions are the most common manifestations of more disseminated disease and may also cause thoracic symptoms. Extrathoracic metastases are seen in fewer than seven percent of patients at presentation, most commonly in the kidneys, extrathoracic lymph nodes, liver, brain, adrenals, thyroid, and bone. Case report: A 66-year-old, white female patient, with previous left mastectomy due to a phyllodes sarcoma in 1997. Diagnosed with malignant thymoma in 2013 and pleural involvement, undergoing systemic chemotherapy and surgery with complete remission of the disease at that time. Two years after, in 2015, presented with disease recurrence in the diaphragm, pleura and lymph nodes, undergoing new surgery, radiotherapy and a second line chemotherapy regimen. Over the years, the disease progressed despite the cancer treatment instituted. In December 2020, the patient presented nodulation in the right breast, with core biopsy suspicion of ductal carcinoma. Undergoing quadrantectomy with lymph node biopsy, with the surgical pathological report finding of thymoma metastasis, resected with free margins. The patient is currently at the 31st pembrolizumab cycle, in good clinical condition.
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Jatobá, Anthony E. A., Marcelo C. Oliveira, Marcel Koenigkam-Santos, and Paulo de Azevedo-Marques. "Feasibility Study of MRI and Multimodality CT/MRI Radiomics for Lung Nodule Classification." In Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sbcas.2021.16065.

Повний текст джерела
Анотація:
Lung cancer is the most common and lethal form of cancer, and its early diagnosis is key to the patient's survival. CT is the reference imaging scan for lung cancer screening; however, it presents the drawback of exposing the patient to ionizing radiation. Recent studies have shown the relevance of MRI in lung nodules diagnosis. In this work, we aimed to evaluate whether radiomics features from MRI are well-suited for lung nodules characterization and if the combination of CT and MRI features can yield better results than the features from the individual modalities. For such, we segmented paired CT and MRI nodules from 33 lung nodules patients, extracted 89 radiomics features from each modality, and combined it into a multimodality feature set. Those features were then used for classifying the nodules into benign and malignant by a set of machine learning algorithms, assessing the AUC across 30 trials. Our results show that MRI radiomics features are suitable for characterizing lung lesions, yielding AUC values up to 17% higher than their CT counterparts, and shedding light on MRI as a viable image modality for decision support systems. Conversely, our multimodality approach did not improve performance compared to the single-modality models, suggesting that the direct combination of multimodality features might not be an adequate strategy for dealing with multimodality medical images.
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Rohrbach, Daniel J., Kassem Harris, Jeremy Kress, and Ulas Sunar. "Characterization of lung lesions using diffuse optical spectroscopy: preliminary results." In Cancer Imaging and Therapy. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/cancer.2016.jtu3a.36.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Šuráňová, Markéta, Daniel Zicha, Pavel Veselý, Jan Brábek, Veronika Jůzová, and Radim Chmelík. "In Vitro Screening with Holographic Incoherent Quantitative Phase Imaging Focuses on Finding Medicaments for Repurposing as Anti-Metastatic Agents Designated as Migrastatics." In European Conference on Biomedical Optics. Washington, D.C.: Optica Publishing Group, 2021. http://dx.doi.org/10.1364/ecbo.2021.em1a.38.

Повний текст джерела
Анотація:
Live lung cancer cells in vitro were exposed to selected medicaments with putative anti- metastatic potential and examined by time-lapse hiQPI, providing simultaneous measurements of the effect on cell growth and motility with unprecedented accuracy.
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Lam, Stephen, Calum E. MacAulay, Jean C. Le Riche, Norihiko Ikeda, and Branko Palcic. "Fluorescence imaging of early lung cancer." In International Symposium on Biomedical Optics Europe '94, edited by Rinaldo Cubeddu, Renato Marchesini, Serge R. Mordon, Katarina Svanberg, Herbert H. Rinneberg, and Georges A. Wagnieres. SPIE, 1995. http://dx.doi.org/10.1117/12.198716.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Takeda, Yuya, Masatsugu Tamaru, Yoshiki Kawata, Mitsuru Kubo, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, et al. "CAD system for lung cancer CT screening." In Medical Imaging 2004, edited by J. Michael Fitzpatrick and Milan Sonka. SPIE, 2004. http://dx.doi.org/10.1117/12.535040.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Takeda, Yuya, Masaaki Tamaru, Yoshiki Kawata, Mitsuru Kubo, Noboru Niki, Hironobu Ohmatsu, Ryutaro Kakinuma, et al. "CAD system for lung cancer CT screening." In Medical Imaging 2003, edited by Milan Sonka and J. Michael Fitzpatrick. SPIE, 2003. http://dx.doi.org/10.1117/12.483546.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Giakos, George C., Stefanie Marotta, Suman Shrestha, Aditi Deshpande, Tannaz Farrahi, Lin Zhang, Thomas Cambria, et al. "Bioinformatics of Lung Cancer." In 2015 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2015. http://dx.doi.org/10.1109/ist.2015.7294524.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Звіти організацій з теми "Lungs Cancer Imaging"

1

Deng, Chun, Zhenyu Zhang, Zhi Guo, Hengduo Qi, Yang Liu, Haimin Xiao, and Xiaojun Li. Assessment of intraoperative use of indocyanine green fluorescence imaging on the number of lymph node dissection during minimally invasive gastrectomy: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0062.

Повний текст джерела
Анотація:
Review question / Objective: Whether is indocyanine green fluorescence imaging-guided lymphadenectomy feasible to improve the number of lymph node dissections during radical gastrectomy in patients with gastric cancer undergoing curative resection? Condition being studied: Gastric cancer was the sixth most common malignant tumor and the fourth leading cause of cancer-related death in the world. Radical lymphadenectomy was a standard procedure in radical gastrectomy for gastric cancer. The retrieval of more lymph nodes was beneficial for improving the accuracy of tumor staging and the long-term survival of patients with gastric cancer. Indocyanine green(ICG) near-infrared fluorescent imaging has been found to provide surgeons with effective visualization of the lymphatic anatomy. As a new surgical navigation technique, ICG near-infrared fluorescent imaging was a hot spot and had already demonstrated promising results in the localization of lymph nodes during surgery in patients with breast cancer, non–small cell lung cancer, and gastric cancer. In addition, ICG had increasingly been reported in the localization of tumor, lymph node dissection, and the evaluation of anastomotic blood supply during radical gastrectomy for gastric cancer. However, it remained unclear whether ICG fluorescence imaging would assist surgeons in performing safe and sufficient lymphadenectomy.
Стилі APA, Harvard, Vancouver, ISO та ін.
2

ZHAO, JIE, LIANHUA YE, WEI WANG, YANTAO YANG, ZHENGHAI SHEN, and SUNYIN RAO. Surgical Prognostic Factors of Second Primary Lung Cancer: A Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0047.

Повний текст джерела
Анотація:
Review question / Objective: The objective of this study was to explore the effects of different surgical strategies and potential prognostic factors on the prognosis of patients with SPLC through a systematic review and meta-analysis.Prognostic factors included surgical approach, type of SPLC(Synchronous and metachronous),histology,disease-free interval (DFI),tumor size,CT morphology, lymph node metastasis status, smoking status, gender. Condition being studied: With the development of imaging technology and better survival after primary lung cancer, the detection rate of second primary lung cancer (SPLC) has been increasing. At present, the staging and treatment of the second primary lung cancer are still controversial. Although surgery is widely accepted as the main treatment method, there is no unified diagnostic criteria and diagnosis and treatment strategy. The objective of this study was to explore the effects of different surgical strategies and potential prognostic factors on the prognosis of patients with SPLC through a systematic review and meta-analysis.
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Kozower, Benjamin, Jennifer Phillips, Amanda Francescatti, Caprice Greenberg, David Winchester, George Chang, Timothy McMurray, and George Stukenborg,. How Often Should Patients with Lung Cancer Have Imaging Tests after Surgery? Patient-Centered Outcomes Research Institute® (PCORI), November 2019. http://dx.doi.org/10.25302/10.2019.cer.130600727.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Hong, Waun K., and Roy Herbst. Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets, Complementary/Innovative Treatment, and Therapeutic Modalities. Fort Belvoir, VA: Defense Technical Information Center, February 2011. http://dx.doi.org/10.21236/ada548594.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Hong, Waun Ki, and Roy Herbst. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities). Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada485809.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Hong, Waun K., and Roy Herbst. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities). Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada504658.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Hong, Waun K. IMPACT: Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets, Complementary/Innovative Treatments, and Therapeutic Modalities. Fort Belvoir, VA: Defense Technical Information Center, February 2013. http://dx.doi.org/10.21236/ada579142.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Loo, Jr, and Billy W. EF5 PET of Tumor Hypoxia: A Predictive Imaging Biomarker of Response to Stereotactic Ablative Radiotherapy (SABR) for Early Lung Cancer. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada594308.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Hong, Waun K. IMPACT: Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets, Complementary/Innovative Treatments, and Therapeutic Modalities. Fort Belvoir, VA: Defense Technical Information Center, February 2014. http://dx.doi.org/10.21236/ada602577.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Hong, Waun K., and Roy Herbst. IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities). Fort Belvoir, VA: Defense Technical Information Center, March 2007. http://dx.doi.org/10.21236/ada468009.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Також вас можуть зацікавити розширені добірки на тему "Lungs Cancer Imaging" для конкретних типів джерел:
Статті в журналах Дисертації Книги
Ми пропонуємо знижки на всі преміум-плани для авторів, чиї праці увійшли до тематичних добірок літератури. Зв'яжіться з нами, щоб отримати унікальний промокод!

До бібліографії