Magnetic resonance imaging for assessment of rectal cancer nodes after chemoradiotherapy: A single center experience.

BACKGROUND: Accurate nodal restaging is becoming clinically more important in patients with locally advanced rectal cancer (LARC) with the emergence of organ-preserving treatment after a good response to neoadjuvant chemoradiotherapy (nCRT). PURPOSE: To evaluate the accuracy of MRI in identifying negative N status (ypN0 patients) in LARC after nCRT. MATERIAL AND METHODS: 191 patients with LARC underwent MRI before and 6-8 weeks after nCRT and subsequent total mesorectal excision. Short-axis diameter of mesorectal lymph nodes was evaluated on the high resolution T2-weighted images to compare MRI restaging with histopathology.. RESULTS: 146 and 45 patients had a negative N status (ypN0) and positive N status (ypN + ), respectively. On restaging MRI, the 70 % reduction in size of the largest node was associated with an area under the curve (AUC) of 0.818 to predict ypN0 stage, with a sensitivity of 93.3 % and a negative predictive value (NPV) of 95.4 %. No nodes were observed in 38 pts (37 pts ypN0 and 1 patient ypN + ), with sensitivity and NPV of nodes disappearance for ypN0 stage of 93.3 % and 92.5 % respectively. A 2.2 mm cut-off in short-axis diameter was associated with an AUC of 0.83 for the prediction of ypN0 nodal stage, with sensitivity and NPV of 79,5% and 91.1 % respectively. CONCLUSION: A reduction in size of 70 % of the largest limph-node on MRI at rectal cancer restaging has high sensitivity and NPV for prediction of ypN0 stage after nCRT. The high NPV of node disappearance and of a ≤ 2.2 mm short-axis diameter is confirmed.

Delta Radiomic Analysis of Mesorectum to Predict Treatment Response and Prognosis in Locally Advanced Rectal Cancer.

BACKGROUND: The aim of this study is to evaluate the delta radiomics approach based on mesorectal radiomic features to develop a model for predicting pathological complete response (pCR) and 2-year disease-free survival (2yDFS) in locally advanced rectal cancer (LARC) patients undergoing neoadjuvant chemoradiotherapy (nCRT). METHODS: Pre- and post-nCRT MRIs of LARC patients treated at a single institution from May 2008 to November 2016 were retrospectively collected. Radiomic features were extracted from the GTV and mesorectum. The Wilcoxon-Mann-Whitney test and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the features in predicting pCR and 2yDFS. RESULTS: Out of 203 LARC patients, a total of 565 variables were evaluated. The best performing pCR prediction model was based on two GTV features with an AUC of 0.80 in the training set and 0.69 in the validation set. The best performing 2yDFS prediction model was based on one GTV and two mesorectal features with an AUC of 0.79 in the training set and 0.70 in the validation set. CONCLUSIONS: The results of this study suggest a possible role for delta radiomics based on mesorectal features in the prediction of 2yDFS in patients with LARC.

Preoperative Assessment of Skeletal Muscle Mass and Muscle Quality Using Computed Tomography: Incidence of Sarcopenia in Patients with Intrahepatic Cholangiocarcinoma Selected for Liver Resection.

Background: Sarcopenia is considered a predictor of poor postoperative and long-term results following liver resection for intrahepatic cholangiocarcinoma (ICC). The aim of our study was to assess the incidence of sarcopenia in patients resected for ICC and its relation to preoperative clinical factors. Methods: Patients resected for ICC in our unit, with available preoperative CT scans within one month before operation, were enrolled in the study. Skeletal muscle index (SMI) and skeletal muscle radiodensity (SMD) were assessed for each patient. Results: Thirty patients matched all inclusion criteria. Low SMI values were documented in 15 patients (50.0%), and low SMD values were documented in 10 patients (33.3%). SMI was significantly greater in males (p < 0.001). In patients who were underweight, the incidence of low SMI was significantly higher than that of high SMI (p = 0.031). In patients who were overweight/obese, the incidence of high SMI was significantly higher than that of low SMI (p = 0.003) and the incidence of low SMD was significantly higher than that of high SMD (p = 0.038). In the univariate analysis, no preoperative factors (clinical and tumor-related factors), in particular BMI, were found to be independent predictors of low SMI. Conclusions: The incidence of sarcopenia was 50.0% in patients selected for liver resection for ICC and was not related to the preoperative clinical factors. A multidisciplinary evaluation of the nutritional status is fundamental before liver resection in patients.

Does restaging MRI radiomics analysis improve pathological complete response prediction in rectal cancer patients? A prognostic model development.

PURPOSE: Our study investigated the contribution that the application of radiomics analysis on post-treatment magnetic resonance imaging can add to the assessments performed by an experienced disease-specific multidisciplinary tumor board (MTB) for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). MATERIALS AND METHODS: This analysis included consecutively retrospective LARC patients who obtained a complete or near-complete response after nCRT and/or a pCR after surgery between January 2010 and September 2019. A three-step radiomics features selection was performed and three models were generated: a radiomics model (rRM), a multidisciplinary tumor board model (yMTB) and a combined model (CM). The predictive performance of models was quantified using the receiver operating characteristic (ROC) curve, evaluating the area under curve (AUC). RESULTS: The analysis involved 144 LARC patients; a total of 232 radiomics features were extracted from the MR images acquired post-nCRT. The yMTB, rRM and CM predicted pCR with an AUC of 0.82, 0.73 and 0.84, respectively. ROC comparison was not significant (p = 0.6) between yMTB and CM. CONCLUSION: Radiomics analysis showed good performance in identifying complete responders, which increased when combined with standard clinical evaluation; this increase was not statistically significant but did improve the prediction of clinical response.

Delta Radiomics Can Predict Distant Metastasis in Locally Advanced Rectal Cancer: The Challenge to Personalize the Cure.

PURPOSE: Distant metastases are currently the main cause of treatment failure in locally advanced rectal cancer (LARC) patients. The aim of this research is to investigate a correlation between the variation of radiomics features using pre- and post-neoadjuvant chemoradiation (nCRT) magnetic resonance imaging (MRI) with 2 years distant metastasis (2yDM) rate in LARC patients. METHODS AND MATERIALS: Diagnostic pre- and post- nCRT MRI of LARC patients, treated in a single institution from May 2008 to June 2015 with an adequate follow-up time, were retrospectively collected. Gross tumor volumes (GTV) were contoured by an abdominal radiologist and blindly reviewed by a radiation oncologist expert in rectal cancer. The dataset was firstly randomly split into 90% training data, for features selection, and 10% testing data, for the validation. The final set of features after the selection was used to train 15 different classifiers using accuracy as target metric. The models' performance was then assessed on the testing data and the best performing classifier was then selected, maximising the confusion matrix balanced accuracy (BA). RESULTS: Data regarding 213 LARC patients (36% female, 64% male) were collected. Overall 2yDM was 17%. A total of 2,606 features extracted from the pre- and post- nCRT GTV were tested and 4 features were selected after features selection process. Among the 15 tested classifiers, logistic regression proved to be the best performing one with a testing set BA, sensitivity and specificity of 78.5%, 71.4% and 85.7%, respectively. CONCLUSIONS: This study supports a possible role of delta radiomics in predicting following occurrence of distant metastasis. Further studies including a consistent external validation are needed to confirm these results and allows to translate radiomics model in clinical practice. Future integration with clinical and molecular data will be mandatory to fully personalized treatment and follow-up approaches.

An evaluation of morphological and functional multi-parametric MRI sequences in classifying non-muscle and muscle invasive bladder cancer.

OBJECTIVES: Our goal is to determine the ability of multi-parametric magnetic resonance imaging (mpMRI) to differentiate muscle invasive bladder cancer (MIBC) from non-muscle invasive bladder cancer (NMIBC). METHODS: Patients underwent mpMRI before tumour resection. Four MRI sets, i.e. T2-weighted (T2W) + perfusion-weighted imaging (PWI), T2W plus diffusion-weighted imaging (DWI), T2W + DWI + PWI, and T2W + DWI + PWI + dif-fusion tensor imaging (DTI) were interpreted qualitatively by two radiologists, blinded to histology results. PWI, DWI and DTI were also analysed quantitatively. Accuracy was determined using histopathology as the reference standard. RESULTS: A total of 82 tumours were analysed. Ninety-six percent of T1-labeled tumours by the T2W + DWI + PWI image set were confirmed to be NMIBC at histopathology. Overall accuracy of the complete mpMRI protocol was 94% in differentiating NMIBC from MIBC. PWI, DWI and DTI quantitative parameters were shown to be significantly different in cancerous versus non-cancerous areas within the bladder wall in T2-labelled lesions. CONCLUSIONS: MpMRI with DWI and DTI appears a reliable staging tool for bladder cancer. If our data are validated, then mpMRI could precede cystoscopic resection to allow a faster recognition of MIBC and accelerated treatment pathways. KEY POINTS: • A critical step in BCa staging is to differentiate NMIBC from MIBC. • Morphological and functional sequences are reliable techniques in differentiating NMIBC from MIBC. • Diffusion tensor imaging could be an additional tool in BCa staging.