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Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14563
Abstract: PURPOSE To develop and validate a deep learning (DL)-based radiomics model to predict the response to chemotherapy in colorectal liver metastases (CRLM). METHODS In this retrospective study, we enrolled 192 patients diagnosed with CRLM who… read more here.
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Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15648
Abstract: PURPOSE To evaluate the efficacy of three-dimensional (3D) segmentation-based radiomics analysis of multiparametric MRI combined with proton magnetic resonance spectroscopy (1 H-MRS) and diffusion tensor imaging (DTI) in glioma grading. METHOD A total of 100… read more here.
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Published in 2020 at "Strahlentherapie und Onkologie"
DOI: 10.1007/s00066-020-01677-x
Abstract: The purpose of the reported study was to investigate the value of cone-beam computed tomography (CBCT)-based radiomics for risk stratification and prediction of biochemical relapse in prostate cancer. The study population consisted of 31 prostate… read more here.
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Published in 2017 at "Abdominal Radiology"
DOI: 10.1007/s00261-017-1072-0
Abstract: PurposeTo develop a CT-based radiomics signature and assess its ability for preoperatively predicting the early recurrence (≤1 year) of hepatocellular carcinoma (HCC).MethodsA total of 215 HCC patients who underwent partial hepatectomy were enrolled in this… read more here.
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Published in 2020 at "Abdominal Radiology"
DOI: 10.1007/s00261-020-02710-4
Abstract: To investigate whether pretreatment magnetic resonance (MR)-based radiomics nomogram can individualize prediction of perineural invasion (PNI) status in rectal cancer (RC). A total of 122 RC patients with pathologically confirmed were classified as training cohort… read more here.
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Published in 2018 at "European Radiology"
DOI: 10.1007/s00330-018-5509-9
Abstract: ObjectivesAdenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are assumed to be indolent lung adenocarcinoma with excellent prognosis. We aim to identify these lesions from invasive adenocarcinoma (IA) by a radiomics approach.MethodsThis retrospective study… read more here.
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Published in 2020 at "European Radiology"
DOI: 10.1007/s00330-019-06597-8
Abstract: Objectives Develop a CT-based radiomics model and combine it with frozen section (FS) and clinical data to distinguish invasive adenocarcinomas (IA) from preinvasive lesions/minimally invasive adenocarcinomas (PM). Methods This multicenter study cohort of 623 lung… read more here.
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Published in 2020 at "European Radiology"
DOI: 10.1007/s00330-020-06893-8
Abstract: To build a CT-based radiomics model to predict the pathological grade of bladder cancer (BCa) preliminarily. Patients with surgically resected and pathologically confirmed BCa and who received CT urography (CTU) in our institution from October… read more here.
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Published in 2020 at "European Radiology"
DOI: 10.1007/s00330-020-07246-1
Abstract: To construct a CT-based radiomics signature and assess its performance in predicting MYCN amplification (MNA) in pediatric patients with neuroblastoma. Seventy-eight pediatric patients with neuroblastoma were recruited (55 in training cohort and 23 in test… read more here.
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Published in 2021 at "European Radiology"
DOI: 10.1007/s00330-021-07914-w
Abstract: Our purpose was to differentiate between malignant from benign soft tissue neoplasms using a combination of MRI-based radiomics metrics and machine learning. Our retrospective study identified 128 histologically diagnosed benign (n = 36) and malignant… read more here.