Purpose: The objective of this study was to build and validate a radiomic signature to predict early a poor outcome using baseline and 2-month evaluation CT and to compare it to the RECIST1·1 and morphological criteria defined by changes in homogeneity and borders.
Methods: This study is an ancillary study from the PRODIGE-9 multicentre prospective study for which 491 patients with metastatic colorectal cancer (mCRC) treated by 5-fluorouracil, leucovorin and irinotecan (FOLFIRI) and bevacizumab had been analysed. In 230 patients, computed texture analysis was performed on the dominant liver lesion (DLL) at baseline and 2 months after chemotherapy. RECIST1·1 evaluation was performed at 6 months. A radiomic signature (Survival PrEdiction in patients treated by FOLFIRI and bevacizumab for mCRC using contrast-enhanced CT TextuRe Analysis (SPECTRA) Score) combining the significant predictive features was built using multivariable Cox analysis in 120 patients, then locked, and validated in 110 patients. Overall survival (OS) was estimated with the Kaplan-Meier method and compared between groups with the logrank test. An external validation was performed in another cohort of 40 patients from the PRODIGE 20 Trial.
Results: In the training cohort, the significant predictive features for OS were: decrease in sum of the target liver lesions (STL), (adjusted hasard-ratio(aHR)=13·7, p=1·93×10), decrease in kurtosis (ssf=4) (aHR=1·08, p=0·001) and high baseline density of DLL, (aHR=0·98, p<0·001). Patients with a SPECTRA Score >0·02 had a lower OS in the training cohort (p<0·0001), in the validation cohort (p<0·0008) and in the external validation cohort (p=0·0027). SPECTRA Score at 2 months had the same prognostic value as RECIST at 6 months, while non-response according to RECIST1·1 at 2 months was not associated with a lower OS in the validation cohort (p=0·238). Morphological response was not associated with OS (p=0·41).
Conclusion: A radiomic signature (combining decrease in STL, density and computed texture analysis of the DLL) at baseline and 2-month CT was able to predict OS, and identify good responders better than RECIST1.1 criteria in patients with mCRC treated by FOLFIRI and bevacizumab as a first-line treatment. This tool should now be validated by further prospective studies.
Trial Registration: Clinicaltrial.gov identifier of the PRODIGE 9 study: NCT00952029.Clinicaltrial.gov identifier of the PRODIGE 20 study: NCT01900717.
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http://dx.doi.org/10.1136/gutjnl-2018-316407 | DOI Listing |
Acad Radiol
December 2024
Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, China (B.W., X.H., Z.Z., Z.L., S.L.). Electronic address:
Rationale And Objectives: To develop and validate a radiomics signature, utilizing baseline and restaging CT, for preoperatively predicting progression-free survival (PFS) after neoadjuvant chemotherapy (NAC) in locally advanced gastric cancer (LAGC).
Methods: A total of 316 patients with LAGC who received NAC followed by gastrectomy were retrospectively included in this single-center study; these patients were split into two cohorts, one for training (n = 243) and the other for validation (n = 73), based on the different districts of our hospital. A total of 1316 radiomics features were extracted from the volume of interest of the gastric-cancer lesion on venous phase CT images.
J Gastroenterol Hepatol
December 2024
Department of Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Background And Aim: In this study, a transfer learning (TL) algorithm was used to predict postoperative recurrence of advanced gastric cancer (AGC) and to evaluate its value in a small-sample clinical study.
Methods: A total of 431 cases of AGC from three centers were included in this retrospective study. First, TL signatures (TLSs) were constructed based on different source domains, including whole slide images (TLS-WSIs) and natural images (TLS-ImageNet).
Front Cardiovasc Med
December 2024
Cardiovascular Medicine Department, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Objective: To explore whether radiomics analysis of pericoronary adipose tissue (PCAT) captured by coronary computed tomography angiography (CCTA) could discriminate unstable angina (UA) from stable angina (SA).
Methods: In this single-center retrospective case-control study, coronary CT images and clinical data from 240 angina patients were collected and analyzed. Patients with unstable angina ( = 120) were well-matched with those having stable angina ( = 120).
J Comput Assist Tomogr
December 2024
Department of radiology, Shaoxing People's Hospital (Zhejiang University Shaoxing Hospital), Shaoxing, Zhejiang, China.
Objective: Inflammatory characteristics in pericoronary adipose tissue (PCAT) may enhance the diagnostic capability of radiomics techniques for identifying vulnerable plaques. This study aimed to evaluate the incremental value of PCAT radiomics scores in identifying vulnerable plaques defined by intravascular ultrasound imaging (IVUS).
Methods: In this retrospective study, a PCAT radiomics model was established and validated using IVUS as the reference standard.
Front Oncol
December 2024
Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Background: Accurate identification of pathologic grade before operation is helpful for guiding clinical treatment decisions and improving the prognosis for soft tissue sarcoma (STS).
Purpose: To construct and assess a magnetic resonance imaging (MRI)-based radiomics nomogram incorporating intratumoral habitats (subregions of clusters of voxels containing similar features) and peritumoral features for the preoperative prediction of the pathological grade of STS.
Methods: The MRI data of 145 patients with STS (74 low-grade and 71 high-grade) from 4 hospitals were retrospectively collected, including enhanced T1-weighted and fat-suppressed-T2-weighted sequences.
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