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Radiomics neoadjuvant

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https://www.readbyqxmd.com/read/29533721/prediction-of-response-to-neoadjuvant-chemotherapy-and-radiation-therapy-with-baseline-and-restaging-18-f-fdg-pet-imaging-biomarkers-in-patients-with-esophageal-cancer
#1
Roelof J Beukinga, Jan Binne Hulshoff, Véronique E M Mul, Walter Noordzij, Gursah Kats-Ugurlu, Riemer H J A Slart, John T M Plukker
Purpose To assess the value of baseline and restaging fluorine 18 (18 F) fluorodeoxyglucose (FDG) positron emission tomography (PET) radiomics in predicting pathologic complete response to neoadjuvant chemotherapy and radiation therapy (NCRT) in patients with locally advanced esophageal cancer. Materials and Methods In this retrospective study, 73 patients with histologic analysis-confirmed T1/N1-3/M0 or T2-4a/N0-3/M0 esophageal cancer were treated with NCRT followed by surgery (Chemoradiotherapy for Esophageal Cancer followed by Surgery Study regimen) between October 2014 and August 2017...
June 2018: Radiology
https://www.readbyqxmd.com/read/29514017/mr-imaging-of-rectal-cancer-radiomics-analysis-to-assess-treatment-response-after-neoadjuvant-therapy
#2
Natally Horvat, Harini Veeraraghavan, Monika Khan, Ivana Blazic, Junting Zheng, Marinela Capanu, Evis Sala, Julio Garcia-Aguilar, Marc J Gollub, Iva Petkovska
Purpose To investigate the value of T2-weighted-based radiomics compared with qualitative assessment at T2-weighted imaging and diffusion-weighted (DW) imaging for diagnosis of clinical complete response in patients with rectal cancer after neoadjuvant chemotherapy-radiation therapy (CRT). Materials and Methods This retrospective study included 114 patients with rectal cancer who underwent magnetic resonance (MR) imaging after CRT between March 2012 and February 2016. Median age among women (47 of 114, 41%) was 55...
June 2018: Radiology
https://www.readbyqxmd.com/read/29437271/novel-radiomic-signature-as-a-prognostic-biomarker-for-locally-advanced-rectal-cancer
#3
Yankai Meng, Yuchen Zhang, Di Dong, Chunming Li, Xiao Liang, Chongda Zhang, Lijuan Wan, Xinming Zhao, Kai Xu, Chunwu Zhou, Jie Tian, Hongmei Zhang
BACKGROUND: Locally advanced rectal cancer (LARC) patient stratification by clinicoradiologic factors may yield variable results. Therefore, more efficient prognostic biomarkers are needed for improved risk stratification of LARC patients, personalized treatment, and prognostication. PURPOSE/HYPOTHESIS: To compare the ability of a radiomic signature to predict disease-free survival (DFS) with that of a clinicoradiologic risk model in individual patients with LARC...
February 13, 2018: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/29046927/fdg-pet-ct-radiomics-for-predicting-the-outcome-of-locally-advanced-rectal-cancer
#4
Pierre Lovinfosse, Marc Polus, Daniel Van Daele, Philippe Martinive, Frédéric Daenen, Mathieu Hatt, Dimitris Visvikis, Benjamin Koopmansch, Frédéric Lambert, Carla Coimbra, Laurence Seidel, Adelin Albert, Philippe Delvenne, Roland Hustinx
PURPOSE: The aim of this study was to investigate the prognostic value of baseline 18 F-FDG PET/CT textural analysis in locally-advanced rectal cancer (LARC). METHODS: Eighty-six patients with LARC underwent 18 F-FDG PET/CT before treatment. Maximum and mean standard uptake values (SUVmax and SUVmean), metabolic tumoral volume (MTV), total lesion glycolysis (TLG), histogram-intensity features, as well as 11 local and regional textural features, were evaluated. The relationships of clinical, pathological and PET-derived metabolic parameters with disease-specific survival (DSS), disease-free survival (DFS) and overall survival (OS) were assessed by Cox regression analysis...
March 2018: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/28939744/radiomics-analysis-for-evaluation-of-pathological-complete-response-to-neoadjuvant-chemoradiotherapy-in-locally-advanced-rectal-cancer
#5
Zhenyu Liu, Xiao-Yan Zhang, Yan-Jie Shi, Lin Wang, Hai-Tao Zhu, Zhenchao Tang, Shuo Wang, Xiao-Ting Li, Jie Tian, Ying-Shi Sun
Purpose: To develop and validate a radiomics model for evaluating pathologic complete response (pCR) to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer (LARC). Experimental Design: We enrolled 222 patients (152 in the primary cohort and 70 in the validation cohort) with clinicopathologically confirmed LARC who received chemoradiotherapy before surgery. All patients underwent T2-weighted and diffusion-weighted imaging before and after chemoradiotherapy; 2,252 radiomic features were extracted from each patient before and after treatment imaging...
December 1, 2017: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/28712700/radiomic-analysis-of-dce-mri-for-prediction-of-response-to-neoadjuvant-chemotherapy-in-breast-cancer-patients
#6
Ming Fan, Guolin Wu, Hu Cheng, Juan Zhang, Guoliang Shao, Lihua Li
OBJECTIVES: To enhance the accurate prediction of the response to neoadjuvant chemotherapy (NAC) in breast cancer patients by using a quantitative analysis of dynamic enhancement magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: A dataset of 57 cancer patients with breast DCE-MR images acquired before NAC was used. Among them, 47 patients were Responders, and 10 patients were non-Responders based on the RECIST criteria. The breast regions were segmented on the MR images, and a total of 158 radiomic features were computed to represent the morphologic, dynamic, and the texture of the tumors as well as the background parenchymal features...
September 2017: European Journal of Radiology
https://www.readbyqxmd.com/read/28693537/erratum-to-intratumoral-and-peritumoral-radiomics-for-the-pretreatment-prediction-of-pathological-complete-response-to-neoadjuvant-chemotherapy-based-on-breast-dce-mri
#7
Nathaniel M Braman, Maryam Etesami, Prateek Prasanna, Christina Dubchuk, Hannah Gilmore, Pallavi Tiwari, Donna Plecha, Anant Madabhushi
No abstract text is available yet for this article.
July 10, 2017: Breast Cancer Research: BCR
https://www.readbyqxmd.com/read/28521821/intratumoral-and-peritumoral-radiomics-for-the-pretreatment-prediction-of-pathological-complete-response-to-neoadjuvant-chemotherapy-based-on-breast-dce-mri
#8
Nathaniel M Braman, Maryam Etesami, Prateek Prasanna, Christina Dubchuk, Hannah Gilmore, Pallavi Tiwari, Donna Plecha, Anant Madabhushi
BACKGROUND: In this study, we evaluated the ability of radiomic textural analysis of intratumoral and peritumoral regions on pretreatment breast cancer dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). METHODS: A total of 117 patients who had received NAC were retrospectively analyzed. Within the intratumoral and peritumoral regions of T1-weighted contrast-enhanced MRI scans, a total of 99 radiomic textural features were computed at multiple phases...
May 18, 2017: Breast Cancer Research: BCR
https://www.readbyqxmd.com/read/28484211/metabolic-radiomics-for-pretreatment-18-f-fdg-pet-ct-to-characterize-locally-advanced-breast-cancer-histopathologic-characteristics-response-to-neoadjuvant-chemotherapy-and-prognosis
#9
Seunggyun Ha, Sohyun Park, Ji-In Bang, Eun-Kyu Kim, Ho-Young Lee
Radiomics has been spotlighted as imaging biomarker for estimation of intratumoral heterogeneity (ITH) which is regarded as the main reason for resistance to tumor treatment. Although a number of studies has shown clinical evidences that separate measurement of metabolic ITH by texture features (TFs) on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG PET/CT) has prognostic ability in various tumors, there has been no consensus regarding the best parameter representing ITH...
May 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/27903462/radiomic-based-pathological-response-prediction-from-primary-tumors-and-lymph-nodes-in-nsclc
#10
Thibaud P Coroller, Vishesh Agrawal, Elizabeth Huynh, Vivek Narayan, Stephanie W Lee, Raymond H Mak, Hugo J W L Aerts
INTRODUCTION: Noninvasive biomarkers that capture the total tumor burden could provide important complementary information for precision medicine to aid clinical decision making. We investigated the value of radiomic data extracted from pretreatment computed tomography images of the primary tumor and lymph nodes in predicting pathological response after neoadjuvant chemoradiation before surgery. METHODS: A total of 85 patients with resectable locally advanced (stage II-III) NSCLC (median age 60...
March 2017: Journal of Thoracic Oncology
https://www.readbyqxmd.com/read/27185368/rectal-cancer-assessment-of-neoadjuvant-chemoradiation-outcome-based-on-radiomics-of-multiparametric-mri
#11
Ke Nie, Liming Shi, Qin Chen, Xi Hu, Salma K Jabbour, Ning Yue, Tianye Niu, Xiaonan Sun
PURPOSE: To evaluate multiparametric MRI features in predicting pathologic response after preoperative chemoradiation therapy (CRT) for locally advanced rectal cancer (LARC). EXPERIMENTAL DESIGN: Forty-eight consecutive patients (January 2012-November 2014) receiving neoadjuvant CRT were enrolled. All underwent anatomical T1/T2, diffusion-weighted MRI (DWI) and dynamic contrast-enhanced (DCE) MRI before CRT. A total of 103 imaging features, analyzed using both volume-averaged and voxelized methods, were extracted for each patient...
November 1, 2016: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/27085484/radiomic-phenotype-features-predict-pathological-response-in-non-small-cell-lung-cancer
#12
Thibaud P Coroller, Vishesh Agrawal, Vivek Narayan, Ying Hou, Patrick Grossmann, Stephanie W Lee, Raymond H Mak, Hugo J W L Aerts
BACKGROUND AND PURPOSE: Radiomics can quantify tumor phenotype characteristics non-invasively by applying advanced imaging feature algorithms. In this study we assessed if pre-treatment radiomics data are able to predict pathological response after neoadjuvant chemoradiation in patients with locally advanced non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: 127 NSCLC patients were included in this study. Fifteen radiomic features selected based on stability and variance were evaluated for its power to predict pathological response...
June 2016: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology
https://www.readbyqxmd.com/read/26355298/predicting-response-to-neoadjuvant-chemotherapy-with-pet-imaging-using-convolutional-neural-networks
#13
Petros-Pavlos Ypsilantis, Musib Siddique, Hyon-Mok Sohn, Andrew Davies, Gary Cook, Vicky Goh, Giovanni Montana
Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy. In this article we investigate the challenging problem of predicting a patient's response to neoadjuvant chemotherapy from a single 18F-FDG PET scan taken prior to treatment. We take a "radiomics" approach whereby a large amount of quantitative features is automatically extracted from pretherapy PET images in order to build a comprehensive quantification of the tumor phenotype...
2015: PloS One
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