MRI-based radiomics predicts the pathologic response of colorectal liver metastases to systemic therapy: A multicenter study.

Background: Tumor response to preoperative chemotherapy is a key prognostic factor for colorectal liver metastases (CRLM), but an accurate non-invasive assessment remains an unmet need.

Objective: To assess the contribution of radiomic analysis of preoperative, post-chemotherapy, gadoxetic acid (Gd-EOB-DTPA)-enhanced MRI to the non-invasive prediction of the pathologic response to systemic therapy of CRLM.

Methods: This retrospective bi-institutional study included all consecutive patients undergoing resection for CRLM (2018-2021) after preoperative oxaliplatin/irinotecan-based chemotherapy.

Role of radiomics in predicting early disease recurrence in locally advanced breast cancer patients: integration of radiomic features and RECIST criteria.

Background: Breast cancer (BC) is a major global health issue with significant heterogeneity among its subtypes. Neoadjuvant treatment (NAT) has been extended to include early BC patients, particularly those with HER2 + and triple-negative subtypes, to achieve pathological complete response and improve long-term outcomes. However, disease recurrence remains a challenge, highlighting the need for predictive biomarkers.

Development and validation of a MRI-radiomics-based machine learning approach in High Grade Glioma to detect early recurrence.

Purpose: Patients diagnosed with High Grade Gliomas (HGG) generally tend to have a relatively negative prognosis with a high risk of early tumor recurrence (TR) after post-operative radio-chemotherapy. The assessment of the pre-operative risk of early versus delayed TR can be crucial to develop a personalized surgical approach. The purpose of this article is to predict TR using MRI radiomic analysis.

Response prediction for neoadjuvant treatment in locally advanced rectal cancer patients-improvement in decision-making: A systematic review.

Background: Predicting pathological complete response (pCR) from pre or post-treatment features could be significant in improving the process of making clinical decisions and providing a more personalized treatment approach for better treatment outcomes. However, the lack of external validation of predictive models, missing in several published articles, is a major issue that can potentially limit the reliability and applicability of predictive models in clinical settings. Therefore, this systematic review described different externally validated methods of predicting response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) patients and how they could improve clinical decision-making.

Coping with modesty during radiotherapy for breast cancer: a multicentric study.

Purpose: Breast cancer is the most frequently diagnosed tumour, representing nearly 30% of all new cases in women. Radiotherapy (RT) plays a crucial role in the management of breast cancer. The objective of this study is to assess modesty in patients undergoing RT for breast cancer and take their suggestions and ideas into consideration to enhance the quality of treatment in this regard.

AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients.

Purpose: To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification.

Material And Methods: In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT.

Myocardial Late Contrast Enhancement CT in Troponin-Positive Acute Chest Pain Syndrome.

Background Acute chest pain with mild troponin rise and inconclusive diagnosis after clinical evaluation represents a diagnostic challenge. Triple-rule-out (TRO) CT may exclude coronary artery disease (CAD), as well as acute aortic syndrome and pulmonary embolism, but cannot help identify other causes of myocardial injury. Purpose To investigate the diagnostic value of a comprehensive CT protocol including both an angiographic and a late contrast enhancement (LCE) scan in participants with troponin-positive acute chest pain.

Quantitative assessment of lung involvement on chest CT at admission: Impact on hypoxia and outcome in COVID-19 patients.

Background: The aim of this study was to quantify COVID-19 pneumonia features using CT performed at time of admission to emergency department in order to predict patients' hypoxia during the hospitalization and outcome.

Methods: Consecutive chest CT performed in the emergency department between March 1st and April 7th 2020 for COVID-19 pneumonia were analyzed. The three features of pneumonia (GGO, semi-consolidation and consolidation) and the percentage of well-aerated lung were quantified using a HU threshold based software.

Coronary and total thoracic calcium scores predict mortality and provides pathophysiologic insights in COVID-19 patients.

Background: Coronavirus disease 2019 (COVID-19) has spread worldwide determining dramatic impacts on healthcare systems. Early identification of high-risk parameters is required in order to provide the best therapeutic approach. Coronary, thoracic aorta and aortic valve calcium can be measured from a non-gated chest computer tomography (CT) and are validated predictors of cardiovascular events and all-cause mortality.

Early T1 Myocardial MRI Mapping: Value in Detecting Myocardial Hyperemia in Acute Myocarditis.

Background Hyperemia is a key component of acute myocarditis (AM). Early gadolinium uptake because of myocardial hyperemia may be quantified by using T1 mapping. Purpose To evaluate the value of early enhanced T1 shortening for the diagnosis of acute myocarditis.