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Objective: To build T2WI-based multiregional radiomics for predicting tumor deposit (TD) and prognosis in patients with resectable rectal cancer. Materials and methods: A total of 208 patients with pathologically confirmed rectal cancer from two hospitals were prospectively enrolled. Intra- and peritumoral features were extracted separately from T2WI images and the least absolute shrinkage and selection operator was used to screen the most valuable radiomics features. Clinical-radiomics nomogram was developed by radiomics signatures and the most predictive clinical parameters. Prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis. Results: For TD, the area under the receiver operating characteristic curve (AUC) for intratumoral radiomics model was 0.956, 0.823, and 0.860 in the training cohort, test cohort, and external validation cohort, respectively. AUC for the peritumoral radiomics model was 0.929, 0.906, and 0.773 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for combined intra- and peritumoral radiomics model was 0.976, 0.918, and 0.874 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for clinical-radiomics nomogram was 0.989, 0.777, and 0.870 in the training cohort, test cohort, and external validation cohort, respectively. The prognostic model constructed by combining intra- and peritumoral radiomics signature score (radscore)–based TD and MRI-reported lymph nodes metastasis (LNM) indicated good performance for predicting 3-year RFS, with AUC of 0.824, 0.865, and 0.738 in the training cohort, test cohort and external validation cohort, respectively. Conclusion: Combined intra- and peritumoral radiomics model showed good performance for predicting TD. Combining intra- and peritumoral radscore-based TD and MRI-reported LNM indicated the recurrence risk. Clinical relevance statement: Combined intra- and peritumoral radiomics model could help accurately predict tumor deposits. Combining this predictive model-based tumor deposits with MRI-reported lymph node metastasis was associated with relapse risk of rectal cancer after surgery. Key Points: • Combined intra- and peritumoral radiomics model provided better diagnostic performance than that of intratumoral and peritumoral radiomics model alone for predicting TD in rectal cancer. • The predictive performance of the clinical-radiomics nomogram was not improved compared with the combined intra- and peritumoral radiomics model for predicting TD. • The prognostic model constructed by combining intra- and peritumoral radscore-based TD and MRI-reported LNM showed good performance for assessing 3-year RFS. [ABSTRACT FROM AUTHOR]

Purpose: To investigative the performance of MRI-radiomics analysis derived from T2WI and apparent diffusion coefficients (ADC) images before and after neoadjuvant chemoradiation therapy (nCRT) separately or simultaneously for predicting post-nCRT lymph node status in patients with locally advanced rectal cancer (LARC). Materials and Methods: Eighty-three patients (training cohort, n = 57; validation cohort, n = 26) with LARC between June 2017 and December 2022 were retrospectively enrolled. All the radiomics features were extracted from volume of interest on T2WI and ADC images from baseline and post-nCRT MRI. Delta-radiomics features were defined as the difference between radiomics features before and after nCRT. Seven clinical-radiomics models were constructed by combining the most predictive radiomics signatures and clinical parameters selected from support vector machine. Receiver operating characteristic curve (ROC) was used to evaluate the performance of models. The optimum model-based LNM was applied to assess 5-years disease-free survival (DFS) using Kaplan–Meier analysis. The end point was clinical or radiological locoregional recurrence or distant metastasis during postoperative follow-up. Results: Clinical-deltaADC radiomics combined model presented good performance for predicting post-CRT LNM in the training (AUC = 0.895,95%CI:0.838–0.953) and validation cohort (AUC = 0.900,95%CI:0.771–1.000). Clinical-deltaADC radiomics-postT2WI radiomics combined model also showed good performances (AUC = 0.913,95%CI:0.838–0.953) in the training and (AUC = 0.912,95%CI:0.771–1.000) validation cohort. As for subgroup analysis, clinical-deltaADC radiomics combined model showed good performance predicting LNM in ypT0-T2 (AUC = 0.827;95%CI:0.649–1.000) and ypT3-T4 stage (AUC = 0.934;95%CI:0.864–1.000). In ypT0-T2 stage, clinical-deltaADC radiomics combined model-based LNM could assess 5-years DFS (P = 0.030). Conclusion: Clinical-deltaADC radiomics combined model could predict post-nCRT LNM, and this combined model-based LNM was associated with 5-years DFS in ypT0-T2 stage. [ABSTRACT FROM AUTHOR]

Objective: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer. Materials and methods: One hundred forty-six patients with rectal cancer who underwent preoperative MRI were prospectively enrolled. Two radiologists independently placed free-hand regions of interest (ROIs) in the largest tumor cross section and three small ROIs on the peritumoral zone adjacent to the tumor contour. Maximum values of tumor ADC (ADCtmax), minimum values of tumor ADC (ADCtmin), mean values of tumor ADC (ADCtmean), mean values of peritumor ADC (ADCpmean), and ADCpmean/ADCtmean (ADC ratio) were obtained on ADC maps and correlated with prognostic factors using uni- and multivariate logistic regression, and receiver operating characteristic curve (ROC) analysis. Results: Interobserver agreement was excellent for ADCtmax and ADCtmean (intraclass correlation coefficient [ICC], 0.915–0.958), and were good for ADCtmin, ADCpmean, and ADC ratio (ICC, 0.774–0.878). The ADC ratio was significantly higher in the poor differentiation, T3–4 stage, lymph node metastasis (LNM)–positive, extranodal extension (ENE)–positive, tumor deposit (TD)–positive, and lymphovascular invasion (LVI)–positive groups than that in the well–moderate differentiation, T1–2 stage, LNM-negative, ENE-negative, TD-negative, and LVI-negative groups (p = 0.008, < 0.001, < 0.001, 0.001, < 0.001, and < 0.001, respectively). The area under the ROC curve (AUC) of the ADC ratio was the highest for assessing poor differentiation (0.700), T3–4 stage (0.707), LNM-positive (0.776), TD-positive (0.848), and LVI-positive (0.778). Both the ADC ratio (AUC = 0.677) and ADCpmean (AUC = 0.686) showed higher diagnostic performance for assessing ENE. Conclusion: The ADC ratio could provide better predictive performance for assessing preoperative prognostic factors in resectable rectal cancer. Key Points: • Both the peritumor/tumor ADC ratio and ADCpmeanare correlated with important prognostic factors of resectable rectal cancer. • Both peritumor ADC and peritumor/tumor ADC ratio had higher diagnostic performance than tumor ADC for assessment of prognostic factors in resectable rectal cancer. • Peritumor/tumor ADC ratio showed the most capability for the assessment of prognostic factors in resectable rectal cancer. [ABSTRACT FROM AUTHOR]

Objective: To determine diagnostic performance of diffusion-weighted (DW) magnetic resonance (MR) volume and apparent diffusion coefficient values (ADCs) for assessing lymph node metastases (LNM) and good response after chemoradiation therapy (CRT) in patients with locally advanced rectal cancer (LARC). Materials and methods: This retrospective study consisted of 61 patients with LARC who underwent pre- and post-CRT DW images. Two radiologists independently placed free-hand regions of interest in each tumor-containing section on DW images to calculate pre- and post-CRT tumor volume and tumor volume reduction rates (Δvolume). Regions of interest were drawn to include tumor on maximum cross-sectional slice to obtain ADCs. Areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate diagnostic performance in identifying LNM and good response after CRT using these parameters. Results: Inter-observer agreement and intra-observer agreement were excellent for pre- and post-CRT DW MR volume (intraclass correlation coefficient [ICC], 0.889–0.948) and moderate for pre- and post-CRT ADCs (ICC, 0.535–0.811). AUCs for identifying LNM were 0.508 for pre-CRT DW MR volume versus 0.705 for pre-CRT ADC, 0.855 for post-CRT DW MR volume versus 0.679 for post-CRT ADC, and 0.887 for Δvolume versus 0.533 for ΔADC. AUCs for identifying good response were 0.518 for pre-CRT volume versus 0.506 for pre-CRT ADC, 0.975 for post-CRT volume versus 0.723 for post-CRT ADC, and 0.987 for Δvolume versus 0.655 for ΔADC. Conclusion: DW MR Δvolume provided high diagnostic performance in discriminating LNM after CRT. DW MR Δvolume was equally as accurate as post-CRT DW MR volume for evaluating good response. Key Points: • Inter-observer agreement and intra-observer agreement were excellent for pre- and post-CRT DW MR volume (intraclass correlation coefficient [ICC], 0.889–0.948) and moderate for pre- and post-CRT ADCs (ICC, 0.535–0.811). • DW MR Δvolume provided high diagnostic performance in identifying LNM after CRT (AUC, 0.887) and good response (AUC, 0.987) and was significantly more accurate than pre-CRT DW MR volume (AUC, 0.508 and 0.518, respectively) and ADCs (AUC, 0.705 and 0.506, respectively). • DW MR Δvolume (AUC, 0.987) was equally as accurate as post-CRT DW MR volume (AUC, 0.975) for evaluating good response, while pre-CRT DW MR volume and ADCs were not reliable for evaluating LNM and good response after CRT (AUC, 0.506–0.723). [ABSTRACT FROM AUTHOR]