An unusual spontaneous recanalization by multiple palmar arteriovenous connections of a chronically occluded radiocephalic hemodialysis fistula

Preservation of a vascular access is crucial in the management of hemodialysis patients. In this regard, percutaneous transluminal angioplasty (PTA) is an effective tool if performed after an adequate understanding of preliminary fistulograms. The present case showed a chronic dysfunction of a radial-cephalic arteriovenous fistula (AVF) due to arterial occlusion and partially relieved by the spontaneous development of multiple small arteriovenous connections in the palmar region of the hand. This dense network had been so far able to ensure a sufficient retrograde blood flow for an effective hemodialytic performance. The angioplasty of the post-anastomotic stenotic segment of the radial artery was effective in restoring this neoformed AVF patency

An unusual spontaneous recanalization by multiple palmar arteriovenous connections of a chronically occluded radiocephalic hemodialysis fistula

Preservation of a vascular access is crucial in the management of hemodialysis patients. In this regard, percutaneous transluminal angioplasty (PTA) is an effective tool if performed after an adequate understanding of preliminary fistulograms. The present case showed a chronic dysfunction of a radial-cephalic arteriovenous fistula (AVF) due to arterial occlusion and partially relieved by the spontaneous development of multiple small arteriovenous connections in the palmar region of the hand. This dense network had been so far able to ensure a sufficient retrograde blood flow for an effective hemodialytic performance. The angioplasty of the post-anastomotic stenotic segment of the radial artery was effective in restoring this neoformed AVF patency

Automatically extracted machine learning features from preoperative CT to early predict microvascular invasion in HCC: the role of the Zone of Transition (ZOT)

open12noMicrovascular invasion (MVI) is a consolidated predictor of hepatocellular carcinoma (HCC) recurrence after treatments. No reliable radiological imaging findings are available for preoperatively diagnosing MVI, despite some progresses of radiomic analysis. Furthermore, current MVI radiomic studies have not been designed for small HCC nodules, for which a plethora of treatments exists. This study aimed to identify radiomic MVI predictors in nodules ≤3.0 cm by analysing the zone of transition (ZOT), crossing tumour and peritumour, automatically detected to face the uncertainties of radiologist’s tumour segmentation. Methods: The study considered 117 patients imaged by contrast-enhanced computed tomography; 78 patients were finally enrolled in the radiomic analysis. Radiomic features were extracted from the tumour and the ZOT, detected using an adaptive procedure based on local image contrast variations. After data oversampling, a support vector machine classifier was developed and validated. Classifier performance was assessed using receiver operating characteristic (ROC) curve analysis and related metrics. Results: The original 89 HCC nodules (32 MVI+ and 57 MVI−) became 169 (62 MVI+ and 107 MVI−) after oversampling. Of the four features within the signature, three are ZOT heterogeneity measures regarding both arterial and venous phases. On the test set (19MVI+ and 33MVI−), the classifier predicts MVI+ with area under the curve of 0.86 (95%CI (0.70–0.93), p∼10^−5), sensitivity = 79% and specificity = 82%. The classifier showed negative and positive predictive values of 87% and 71%, respectively. Conclusions: The classifier showed the highest diagnostic performance in the literature, disclosing the role of ZOT heterogeneity in predicting the MVI+ status.noneMatteo Renzulli, Margherita Mottola, Francesca Coppola, Maria Adriana Cocozza, Silvia Malavasi, Arrigo Cattabriga, Giulio Vara, Matteo Ravaioli, Matteo Cescon, Francesco Vasuri, Rita Golfieri, Alessandro BevilacquaMatteo Renzulli, Margherita Mottola, Francesca Coppola, Maria Adriana Cocozza, Silvia Malavasi, Arrigo Cattabriga, Giulio Vara, Matteo Ravaioli, Matteo Cescon, Francesco Vasuri, Rita Golfieri, Alessandro Bevilacqu

Radiomic Features from Post-Operative 18F-FDG PET/CT and CT Imaging Associated with Locally Recurrent Rectal Cancer: Preliminary Findings

Locally Recurrent Rectal Cancer (LRRC) remains a major clinical concern, it rapidly invades pelvic organs and nerve roots, causing severe symptoms. Curative-intent salvage therapy offers the only potential for cure but it has a higher chance of success when LRRC is diagnosed at an early stage. Imaging diagnosis of LRRC is very challenging due to fibrosis and inflammatory pelvic tissue which can mislead even the most expert reader. This study exploited a radiomic analysis to enrich, through quantitative features, the characterization of tissue properties, thus favouring an accurate detection of LRRC by Computed Tomography (CT) and 18F-FDG-Positron Emission Tomography/CT (PET/CT). Of 563 eligible patients, undergoing radical resection (R0) of primary RC, 57 patients with suspected LRRC were included, 33 of which histologically confirmed. After manually segmenting suspected LRRC in CT and PET/CT, 144 radiomic features (RFs) were generated, and RFs were investigated for univariate significant discriminations (Wilcoxon rank-sum test, p<0.050) of LRRC from NO LRRC. Five RFs in PET/CT (p<0.017) and 2 in CT (p<0.022) enabled, individually, a clear distinction of the groups, and one RF was shared by PET/CT and CT. Besides confirming the potential role of radiomics to advance LRRC diagnosis, the aforementioned shared RF describes LRRC as tissues having high local inhomogeneity due to evolving tissue’s properties

Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice

While cross-sectional imaging has seen continuous progress and plays an undiscussedpivotal role in the diagnostic management and treatment planning of patients with rectal cancer, alargely unmet need remains for improved staging accuracy, assessment of treatment response andprediction of individual patient outcome. Moreover, the increasing availability of target therapies hascalled for developing reliable diagnostic tools for identifying potential responders and optimizingoverall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fullyevolving research topic, which could harness the power of modern computer technology to generatequantitative information from imaging datasets based on advanced data-driven biomathematicalmodels, potentially providing an added value to conventional imaging for improved patient manage-ment. The present study aimed to illustrate the contribution that current radiomics methods appliedto magnetic resonance imaging can offer to managing patients with rectal cancer

Interventional Radiological Management and Prevention of Complications after Pancreatic Surgery: Drainage, Embolization and Islet Auto-Transplantation

Pancreatic surgery still remains burdened by high levels of morbidity and mortality with a relevant incidence of complications, even in high volume centers. This review highlights the interventional radiological management of complications after pancreatic surgery. The current literature regarding the percutaneous drainage of fluid collections due to pancreatic fistulas, percutaneous transhepatic biliary drainage due to biliary leaks and transcatheter embolization (or stent–graft) due to arterial bleeding is analyzed. Moreover, also, percutaneous intra-portal islet auto-transplantation for the prevention of pancreatogenic diabetes in case of extended pancreatic resection is also examined. Moreover, a topic not usually treated in other similar reviewsas percutaneous intra-portal islet autotransplantation for the prevention of pancreatogenic diabetes in case of extended pancreatic resection is also one of our areas of focus. In islet auto-transplantation, the patient is simultaneously donor and recipient. Differently from islet allo-transplantation, it does not require immunosuppression, has no risk of rejection and is usually efficient with a small number of transplanted islets

The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

Our study aimed to investigate whether radiomics on MRI sequences can differentiate responder (R) and non-responder (NR) patients based on the tumour regression grade (TRG) assigned after surgical resection in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT). Eighty-five patients undergoing primary staging with MRI were retrospectively evaluated, and 40 patients were finally selected. The ROIs were manually outlined in the tumour site on T2w sequences in the oblique-axial plane. Based on the TRG, patients were grouped as having either a complete or a partial response (TRG = (0,1), n = 15). NR patients had a minimal or poor nCRT response (TRG = (2,3), n = 25). Eighty-four local first-order radiomic features (RFs) were extracted from tumour ROIs. Only single RFs were investigated. Each feature was selected using univariate analysis guided by a one-tailed Wilcoxon rank-sum. ROC curve analysis was performed, using AUC computation and the Youden index (YI) for sensitivity and specificity. The RF measuring the heterogeneity of local skewness of T2w values from tumour ROIs differentiated Rs and NRs with a p-value ≈ 10−5; AUC = 0.90 (95%CI, 0.73–0.96); and YI = 0.68, corresponding to 80% sensitivity and 88% specificity. In conclusion, higher heterogeneity in skewness maps of the baseline tumour correlated with a greater benefit from nCR

Automated Prediction of the Response to Neoadjuvant Chemoradiotherapy in Patients Affected by Rectal Cancer

Simple Summary Colorectal cancer is the second most malignant tumor per number of deaths after lung cancer and the third per number of new cases after breast and lung cancer. The correct and rapid identification (i.e., segmentation of the cancer regions) is a fundamental task for correct patient diagnosis. In this study, we propose a novel automated pipeline for the segmentation of MRI scans of patients with LARC in order to predict the response to nCRT using radiomic features. This study involved the retrospective analysis of T-2-weighted MRI scans of 43 patients affected by LARC. The segmentation of tumor areas was on par or better than the state-of-the-art results, but required smaller sample sizes. The analysis of radiomic features allowed us to predict the TRG score, which agreed with the state-of-the-art results. Background: Rectal cancer is a malignant neoplasm of the large intestine resulting from the uncontrolled proliferation of the rectal tract. Predicting the pathologic response of neoadjuvant chemoradiotherapy at an MRI primary staging scan in patients affected by locally advanced rectal cancer (LARC) could lead to significant improvement in the survival and quality of life of the patients. In this study, the possibility of automatizing this estimation from a primary staging MRI scan, using a fully automated artificial intelligence-based model for the segmentation and consequent characterization of the tumor areas using radiomic features was evaluated. The TRG score was used to evaluate the clinical outcome. Methods: Forty-three patients under treatment in the IRCCS Sant'Orsola-Malpighi Polyclinic were retrospectively selected for the study; a U-Net model was trained for the automated segmentation of the tumor areas; the radiomic features were collected and used to predict the tumor regression grade (TRG) score. Results: The segmentation of tumor areas outperformed the state-of-the-art results in terms of the Dice score coefficient or was comparable to them but with the advantage of considering mucinous cases. Analysis of the radiomic features extracted from the lesion areas allowed us to predict the TRG score, with the results agreeing with the state-of-the-art results. Conclusions: The results obtained regarding TRG prediction using the proposed fully automated pipeline prove its possible usage as a viable decision support system for radiologists in clinical practice

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Locally advanced rectal cancer: T2w-MRI-based radiomics may detect responder patients undergoing neoadjuvant chemoradiotherapy

Purpose or Learning Objective To investigate whether in locally advanced rectal cancer (LARC) treated with neo-adjuvant chemoradiotherapy (nCRT), radiomics on T2 weighted (T2w) MRI sequences can discriminate responder (R) and non-responder (NR) patients based on the Tumour Regression Grade (TRG) assigned after surgical resection Methods or Background This study retrospectively enrols 40 patients undergoing pre-therapy 1.5T-MRI. Regions of Interest (ROIs) are manually outlined in all slices of the tumour\u2019s site on T2w sequences in the oblique-axial plane, acquired with 3 mm slice thickness. Based on TRG, R patients have complete and partial nCRT response (TRG=[0,1], n\ub015) while NR patients have a minimal and poor nCRT response (TRG=[2,3], n\ub025). Eighty-four local first-order radiomic features (RFs) are extracted from tumour ROIs. To prevent overfitting, only single RFs are investigated to discriminate Rs and NRs. The most performing feature is selected through a univariate analysis guided by one-tail Wilcoxon rank-sum test (p=0.05 significance level). To assess the feature discrimination capability, ROC curve analysis is performed, through AUC computation, Youden Index (YI) for sensitivity and specificity. Results or Findings One RF measuring the local heterogeneity of T2w values within tumour ROIs discriminates Rs and NRs with p~10-5, AUC=0.90 (95%CI, 0.73-0.96), with YI=0.68 corresponding to sensitivity=80% and specificity=88%. The separation achieved highlights 3 false positives and 3 false negatives. Conclusion Pre-therapy baseline tumour heterogeneity measured from T2w-MR images has a very promising role in predicting the TRG histological classification. Patients with lower tumour heterogeneity at pre-therapy show a better response to nCRT. Limitations This study involves a small number of patients. However, one-only feature is considered and such a strong discrimination stresses the future role of the feature in a classification study