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Objectives: To determine whether and how tumour size of resectable oesophageal squamous cell carcinoma (ESCC) measured with multidetector CT could predict regional lymph node metastasis (LNM) and N stage., Methods: Two hundred five patients with ESCC underwent radical oesophagectomy with three-field lymphadenectomy less than 3 weeks after contrast-enhanced CT. Tumour size of the ESCC (tumour length, maximal thickness and gross tumour volume, GTV) was measured on CT. Statistical analyses were performed to identify whether tumour size could predict regional LNM and N stage, and to determine how to use the size of ESCC to predict N stage., Results: Univariate analysis showed that tumour size could predict regional LNM (all P < 0.05). Logistic regression analysis revealed that GTV could independently predict regional LNM (P = 0.021, odds ratio = 1.813). Mann-Whitney tests showed that tumour size could distinguish grouped N stages (all P < 0.05). GTV might be a differentiating indicator between N0 and N1-3 stages (cutoff, 14.4 cm(3)), between N0-1 and N2-3 (cutoff, 15.9 cm(3)), and between N0-2 and N3 (cutoff, 26.1 cm(3)), with sensitivity of 76%, 63% or 75%, and specificity of 75%, 61% and 81%, respectively., Conclusions: The GTV of ESCC measured with CT could be an indicator for predicting regional LNM and grouped N stages., Key Points: • Multidetector computed tomography (MDCT) allows accurate assessment of oesophageal tumour size • For resectable squamous cell tumours, size helped predict regional lymph node involvement • Gross tumour volume may predict the N stage of oesophageal squamous cell carcinoma.

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]

Background: Lymph node metastasis (LNM) is a risk factor for poor long-term outcomes and a prognostic factor for disease-free survival in colon cancer. Preoperative lymph node status evaluation remains a challenge. The purpose of this study is to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to predict LNM and N stage in colon cancer. Material and methods: One hundred six patients with colon cancer who underwent radical surgery within 1 week of MDCT scan were enrolled. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), tumor maximum cross-sectional area (Tare), and tumor volume (Tvol) were measured to be correlated with pathologic LNM and N stage using univariate logistic regression analysis, multivariate logistic analysis, and receiver operating characteristic (ROC) curve analysis. Results: The inter- and intraobserver reproducibility of Tlen (intraclass correlation coefficient [ICC] = 0.94, 0.95, respectively), Tdia (ICC = 0.81, 0.93, respectively), Tare (ICC = 0.97, 0.91, respectively), and Tvol (ICC = 0.99, 0.99, respectively) parameters measurement are excellent. Univariate logistic regression analysis showed that there were significant differences in Tlen, Tdia, Tare, and Tvol between positive and negative LNM (p < 0.001, 0.001, < 0.001, < 0.001, respectively). Multivariate logistic regression analysis revealed that Tvol was independent risk factor for predicting LNM (odds ratio, 1.082; 95% confidence interval for odds ratio, 1.039, 1.127, p<0.001). Tlen, Tdia, Tare, and Tvol could distinguish N0 from N1 stage (p < 0.001, 0.041, < 0.001, < 0.001, respectively), N0 from N2 (all p < 0.001), N0 from N1-2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively), and N0-1 from N2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively). The area under the ROC curve (AUC) was higher for Tvol than that of Tlen, Tdia, and Tare in identifying LNM (AUC = 0.83, 0.82, 0.69, 0.79), and distinguishing N0 from N1 stage (AUC = 0.79, 0.78, 0.63, 0.74), N0 from N2 stage (AUC = 0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 stage (AUC = 0.84, 0.79, 0.76, 0.83, respectively). Conclusion: Tumor size was correlated with regional LNM in resectable colon cancer. In particularly, Tvol showed the most potential for noninvasive preoperative prediction of regional LNM and N stage. [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]

Objective: To assess the role of region of interest (ROI) selection of intravoxel incoherent motion (IVIM) for predicting lymph node metastases (LNM) and tumor response after chemoradiation therapy (CRT) in locally advanced rectal cancer.Materials and Methods: Seventy-nine patients with biopsy-proven rectal adenocarcinoma who underwent pre- and post-CRT MRI and surgery were prospectively enrolled. The exclusion criteria included nonresectable and/or metastatic disease and loss of follow-up. Pathological stage was determined using ypTNM stage and tumor regression grade. Slow diffusion coefficient (D), fast diffusion coefficient (D*), perfusion-related diffusion fraction (f), apparent diffusion coefficient (ADC) and their percentage changes (Δ%) were evaluated by two readers using whole-volume, single-slice and small samples ROI methods. Risk factors including carcinoembryonic antigen, post-CRT T-staging, extramural venous invasion and IVIM parameters were evaluated through multivariate analyses. Areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate diagnostic performance. Duration of follow-up was two-year. Recurrence-free survival of patients with LNM and tumor response was estimated using Kaplan-Meier analysis.Results: Interobserver agreement were good for pre- and post-CRT three ROI methods (intraclass correlation coefficient [ICC], 0.581-0.953). Whole-volume ROI-derived Δ%D was an independent risk factor for LNM, non-pathological complete response (non-pCR) and poor response (odds ratio, 0.940, 0.952, 0.805, respectively; all p < 0.001). Whole-volume ROI-derived Δ%D showed best AUC of 0.810, 0.851 and 0.903 for LNM, non-pCR and poor response (cutoff value, 31.8%, 54.5%, 52.8%, respectively). Patients with post-CRT LNM showed reduction in 2-year recurrence-free survival (hazard ratio, 3.253).Conclusions: Whole-volume ROI-derived Δ%D provided high diagnostic performance for evaluating post-CRT LNM and tumor response. Patients with post-CRT LNM showed earlier recurrence. [ABSTRACT FROM AUTHOR]