Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients' treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the "Radiomics Quality Score" and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.
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http://dx.doi.org/10.3390/jimaging8020045 | DOI Listing |
Clin Proteomics
January 2025
Ophthalmology Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Largo A. Gemelli, 1, 00168, Rome, Italy.
Our objective is to determine the protein and complements constituents of Cord blood Platelet-rich plasma (CB-PRP), based on the hypothesis that it contains beneficial components capable of arresting or potentially decelerating the advancement of atrophic age-related macular degeneration (dry-AMD), with the support of radiomics. Two distinct pools of CB-PRP were assessed, each pool obtained from a total of 15 umbilical cord-blood donors. One aliquot of each pool respectively was subjected to proteomic analysis in order to enhance the significance of our findings, by identifying proteins that are shared between the two sample pools and gaining insights into the pathways they are associated with.
View Article and Find Full Text PDFSci Rep
January 2025
Department of MRI, Zhongshan City People's Hospital, No. 2, Sunwen East Road, Shiqi District, Zhongshan, 528403, Guangdong, China.
To investigate the potential of an MRI-based radiomic model in distinguishing malignant prostate cancer (PCa) nodules from benign prostatic hyperplasia (BPH)-, as well as determining the incremental value of radiomic features to clinical variables, such as prostate-specific antigen (PSA) level and Prostate Imaging Reporting and Data System (PI-RADS) score. A restrospective analysis was performed on a total of 251 patients (training cohort, n = 119; internal validation cohort, n = 52; and external validation cohort, n = 80) with prostatic nodules who underwent biparametric MRI at two hospitals between January 2018 and December 2020. A total of 1130 radiomic features were extracted from each MRI sequence, including shape-based features, gray-level histogram-based features, texture features, and wavelet features.
View Article and Find Full Text PDFAcad Radiol
January 2025
Guangxi Medical University, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Department of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China (D.H., X.W.). Electronic address:
Rationale And Objectives: Accurate preoperative pathological staging of gastric cancer is crucial for optimal treatment selection and improved patient outcomes. Traditional imaging methods such as CT and endoscopy have limitations in staging accuracy.
Methods: This retrospective study included 691 gastric cancer patients treated from March 2017 to March 2024.
Acad Radiol
January 2025
Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China (B.Z., F.M., X.S., S.L., Q.W.); Department of Urology, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, Guangdong 510080, China (Q.W.). Electronic address:
Rationale And Objectives: To develop an automatic deep-radiomics framework that diagnoses and stratifies prostate cancer in patients with prostate-specific antigen (PSA) levels between 4 and 10 ng/mL.
Materials And Methods: A total of 1124 patients with histological results and PSA levels between 4 and 10 ng/mL were enrolled from one public dataset and two local institutions. An nnUNet was trained for prostate masks, and a feature extraction module identified suspicious lesion masks.
Transl Oncol
January 2025
Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China; Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China. Electronic address:
Background And Objective: Though several clinicopathological features are identified as prognostic indicators, potentially prognostic radiomic models are expected to preoperatively and noninvasively predict survival for HCC. Traditional radiomic models are lacking in a consideration for intratumoral regional heterogeneity. The study aimed to establish and validate the predictive power of multiple habitat radiomic models in predicting prognosis of hepatocellular carcinoma (HCC).
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