Predictive role of diffusion-weighted MRI in the assessment of response to total neoadjuvant therapy in locally advanced rectal cancer.

OBJECTIVE: To investigate the predictive role of diffusion-weighted magnetic resonance imaging (DW-MRI) in the assessment of response to total neoadjuvant therapy (TNT) in patients with locally advanced rectal cancer (LARC). METHODS: In this single-center retrospective study, patients with LARC who underwent staging MRI and TNT were enrolled. MRI-based staging, tumor volume, and DWI-ADC values were analyzed. Patients were classified as complete responders (pCR) and non-complete responders (non-pCR), according to post-surgical outcome. Pre-treatment ADC values were compared to pathological outcome, post-treatment downstaging, and reduction of tumor volume. The diagnostic accuracy of DWI-ADC in differentiating between pCR and non-pCR groups was calculated with receiver operating characteristic (ROC) analysis. RESULTS: A total of 36 patients were evaluated (pCR, n = 20; non-pCR, n = 16). Pre-treatment ADC values were significantly different between the two groups (p = 0.034), while no association was found between pre-TNT tumor volume and pathological response. ADC values showed significant correlations with loco-regional downstaging after therapy (r = -0.537, p = 0.022), and with the reduction of tumor volume (r = -0.480, p = 0.044). ADC values were able to differentiate pCR from non-pCR patients with a sensitivity of 75% and specificity of 70%. CONCLUSIONS: ADC values on pre-treatment MRI were strongly associated with the outcome in patients with LARC, both in terms of pathological response and in loco-regional downstaging after TNT, suggesting the use of DW-MRI as a potential predictive tool of response to therapy. KEY POINTS: • ADC values of pre-TNT MRI examinations of patients with LARC were significantly associated with a pathological complete response (pCR) and with post-treatment regression of TNM staging. • An ADC value of 1.042 ×10-3 mm2/s was found to be the optimal cutoff value for discriminating between pCR and non-pCR patients, with a sensitivity of 75% and specificity of 70%. • DW-MRI proved to have a potential predictive role in the assessment of response to therapy in patients with LARC, throughout the analysis of ADC map values.

Chest CT features of COVID-19 in vaccinated versus unvaccinated patients: use of CT severity score and outcome analysis.

OBJECTIVES: To evaluate the impact of vaccination on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and moreover on coronavirus disease 2019 (COVID-19) pneumonia, by assessing the extent of lung disease using the CT severity score (CTSS). METHODS: Between September 2021 and February 2022, SARS-CoV-2 positive patients who underwent chest CT were retrospectively enrolled. Anamnestic and clinical data, including vaccination status, were obtained. All CT scans were evaluated by two readers using the CTSS, based on a 25-point scale. Univariate and multivariate logistic regression analyses were performed to evaluate the associations between CTSS and clinical or demographic variables. An outcome analysis was used to differentiate clinical outcome between vaccinated and unvaccinated patients. RESULTS: Of the 1040 patients (537 males, 503 females; median age 58 years), 678 (65.2%) were vaccinated and 362 (34.8%) unvaccinated. Vaccinated patients showed significantly lower CTSS compared to unvaccinated patients (p < 0.001), also when patients without lung involvement (CTSS = 0) were excluded (p < 0.001). Older age, male gender and lower number of doses administered were associated with higher CTSS, however, in the multivariate analysis, vaccination status resulted to be the variable with the strongest association with CTSS. Clinical outcomes were significantly worse in unvaccinated patients, including higher number of ICU admissions and higher mortality rates. CONCLUSIONS: Lung involvement during COVID-19 was significantly less severe in vaccinated patients compared with unvaccinated patients, who also showed worse clinical outcomes. Vaccination status was the strongest variable associated to the severity of COVID-related, more than age, gender, and number of doses administered.

Role of CT texture analysis for predicting peritoneal metastases in patients with gastric cancer.

PURPOSE: Aim of the study was to perform CT texture analysis in patients with gastric cancer (GC) to investigate potential role of radiomics for predicting the occurrence of peritoneal metastases (PM). MATERIALS AND METHODS: In this single-centre retrospective study, patients with gastric adenocarcinoma and surgically confirmed presence or absence of PM were, respectively, enrolled in group PM and group non-PM. Patients with T1-staging, previous treatment or presence of imaging artifacts were excluded from the study. Pre-operative CT examinations were evaluated. Acquisition protocol consisted of gastric distension with water, pre-contrast and arterial phases on upper abdomen and portal phase on thorax and whole abdomen. Texture analysis was performed on portal phase images: the region of interest was manually drawn along the margins of the primitive lesion on each slice and the volume of interest of the whole tumour was obtained. A total of 38 texture parameters were extracted and analysed. ROC curves were performed on significant texture features (p < 0.05). Multiple logistic regression was conducted on features with the best AUC to identify differentiating variables for both groups. RESULTS: A total of 90 patients were evaluated (group PM, n = 45; group non-PM, n = 45). T2/T3 tumours were prevalent in group non-PM, T4 was significantly associated with group PM. Significant differences between the two groups were observed for 22/38 texture parameters. Volume and GLRLM_LRHGE showed the greatest AUC in ROC curve analysis (0.737 and 0.734, respectively) and were found to be independent differentiating variables of group PM in the multiple regression analysis (OR 8.44, [95% CI, 1.52-46.8] and OR 18.99 [95% CI, 84-195.31], respectively). CONCLUSIONS: Our preliminary results suggest the potential value of CT texture analysis for predicting the risk of PM from GC, which may be helpful to stratify patients and address them to the most appropriate treatment.

Tocilizumab effects in COVID-19 pneumonia: role of CT texture analysis in quantitative assessment of response to therapy.

PURPOSE: To evaluate CT and laboratory changes in COVID-19 patients treated with tocilizumab, compared to a control group, throughout a combined semiquantitative and texture analysis of images. MATERIALS AND METHODS: From March 11 to April 20, 2020, 57 SARS-CoV-2 positive patients were retrospectively compared: group T (n = 30) receiving tocilizumab and group non-T (n = 27) undergoing only antivirals/antimalarials. Chest-CT and laboratory findings were analyzed before and after treatment. CT evaluation included both semiquantitative scoring and texture analysis of all parenchymal lesions. Survival and recovery analyses were also provided with Kaplan-Meier method. RESULTS: In group T, no significant differences were found for CT score after treatment, while several texture features significantly changed, including mean attenuation (p < 0.0001), skewness (p < 0.0001), entropy (p = 0.0146) and higher-order parameters, suggesting considerable fading of parenchymal lesions. PaO2/FiO2 mean value significantly increased after treatment, from 240 ± 93 to 363 ± 107 (p = 0.0003), with parallel decrease in inflammatory biomarkers (CRP, D-dimer and LDH). In group non-T, CT scoring, texture and laboratory parameters showed significant worsening at follow-up. Findings were clinically associated with opposite trends between two groups, with reduction of severe cases in group T (from 21/30 to 5/30; p < 0.0001) as compared to a significant worsening in group non-T (severe cases increasing from 6/27 to 14/27; p = 0.0473). Probability of discharge was significantly higher in group T (p < 0.0001), as well as survival rate, although not statistically significant. CONCLUSIONS: Our results suggest the potential role of CT texture analysis for assessing response to treatment in COVID-19 pneumonia, using Tocilizumab, as compared to semiquantitative evaluation, providing insight into the intrinsic parenchymal changes.

Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis.

OBJECTIVES: To correlate a CT-based semi-quantitative score of pulmonary involvement in COVID-19 pneumonia with clinical staging of disease and laboratory findings. We also aimed to investigate whether CT findings may be predictive of patients' outcome. METHODS: From March 6 to March 22, 2020, 130 symptomatic SARS-CoV-2 patients were enrolled for this single-center analysis and chest CT examinations were retrospectively evaluated. A semi-quantitative CT score was calculated based on the extent of lobar involvement (0:0%; 1, < 5%; 2:5-25%; 3:26-50%; 4:51-75%; 5, > 75%; range 0-5; global score 0-25). Data were matched with clinical stages and laboratory findings. Survival curves and univariate and multivariate analyses were performed to evaluate the role of CT score as a predictor of patients' outcome. RESULTS: Ground glass opacities were predominant in early-phase (≤ 7 days since symptoms' onset), while crazy-paving pattern, consolidation, and fibrosis characterized late-phase disease (> 7 days). CT score was significantly higher in critical and severe than in mild stage (p < 0.0001), and among late-phase than early-phase patients (p < 0.0001). CT score was significantly correlated with CRP (p < 0.0001, r = 0.6204) and D-dimer (p < 0.0001, r = 0.6625) levels. A CT score of ≥ 18 was associated with an increased mortality risk and was found to be predictive of death both in univariate (HR, 8.33; 95% CI, 3.19-21.73; p < 0.0001) and multivariate analysis (HR, 3.74; 95% CI, 1.10-12.77; p = 0.0348). CONCLUSIONS: Our preliminary data suggest the potential role of CT score for predicting the outcome of SARS-CoV-2 patients. CT score is highly correlated with laboratory findings and disease severity and might be beneficial to speed-up diagnostic workflow in symptomatic cases. KEY POINTS: • CT score is positively correlated with age, inflammatory biomarkers, severity of clinical categories, and disease phases. • A CT score ≥ 18 has shown to be highly predictive of patient's mortality in short-term follow-up. • Our multivariate analysis demonstrated that CT parenchymal assessment may more accurately reflect short-term outcome, providing a direct visualization of anatomic injury compared with non-specific inflammatory biomarkers.

Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients.

OBJECTIVES: To evaluate the performance of artificial intelligence (AI) in the preoperative detection of lung metastases on CT. MATERIALS AND METHODS: Patients who underwent lung metastasectomy in our institution between 2016 and 2020 were enrolled, their preoperative CT reports having been performed before an AI solution (Veye Lung Nodules, version 3.9.2, Aidence) became available as a second reader in our department. All CT scans were retrospectively processed by AI. The sensitivities of unassisted radiologists (original CT radiology reports), AI reports alone and both combined were compared. Ground truth was established by a consensus reading of two radiologists, who analyzed whether the nodules mentioned in the pathology report were retrospectively visible on CT. Multivariate analysis was performed to identify nodule characteristics associated with detectability. RESULTS: A total of 167 patients (men: 62.9 %; median age, 59 years [47-68]) with 475 resected nodules were included. AI detected an average of 4 nodules (0-17) per CT, of which 97 % were true nodules. The combination of radiologist plus AI (92.4 %) had significantly higher sensitivity than unassisted radiologists (80.4 %) (p < 0.001). In 27/57 (47.4 %) patients who had multiple preoperative CT scans, AI detected lung nodules earlier than the radiologist. Vascular contact was associated with non-detection by radiologists (OR:0.32[0.19, 0.54], p < 0.001), whilst the presence of cavitation (OR:0.26[0.13, 0.54], p < 0.001) or pleural contact (OR:0.10[0.04, 0.22], p < 0.001) was associated with non-detection by AI. CONCLUSION: AI significantly increases the sensitivity of preoperative detection of lung metastases and enables earlier detection, with a significant potential benefit for patient management.

Insights into Long COVID: Unraveling Risk Factors, Clinical Features, Radiological Findings, Functional Sequelae and Correlations: A Retrospective Cohort Study.

BACKGROUND: The long-term symptomatology of COVID-19 has yet to be comprehensively described. The aim of the study was to describe persistent COVID-19 symptoms in a cohort of hospitalized and home-isolated patients. METHODS: A retrospective cohort study was conducted on long COVID patients. Long COVID symptoms were identified, and patients were divided into hospitalized (in-patients) and home-isolated (out-patients) as well as according to the number of symptoms. Patients were examined by a multydisciplinary medical team. Blood tests, high resolution chest computed tomography (CT), physical and infectious examination were performed. Finally, in-patients were evaluated at two time-points: on hospital admission (T0) and after three months from discharge (Tpost). RESULTS: Three hundred and sixty-four COVID-19 patients were enrolled. 82% of patients reported at least one or more symptoms. The most reported symptom was fatigue. Chest CT showed alteration in 76% of patients and pulmonary function alterations were observed in 44.7% of patients. A higher risk of presenting at least one symptom was seen in patients treated with corticosteroid and a higher risk of presenting chest CT residual lesion was observed in hospitalized patients and in patients that received hydroxychloroquine treatment. Moreover, a higher risk of altered pulmonary function was observed in older patients. CONCLUSION: Long-term sequelae are present in a remarkable number of long COVID patients and pose a new challenge to the healthcare system to identify long-lasting effects and improve patients' wellbeing. Multi-disciplinary teams are crucial to develop preventive measures, and clinical management strategies.

Tissue Inhibitor of Matrix Metalloproteinases-1 (TIMP-1) and Pulmonary Involvement in COVID-19 Pneumonia.

Background: The aim of the study was to longitudinally evaluate the association between MMP-2, MMP-9, TIMP-1 and chest radiological findings in COVID-19 patients. Methods: COVID-19 patients were evaluated based on their hospital admission (baseline) and three months after hospital discharge (T post) and were stratified into ARDS and non-ARDS groups. As a control group, healthy donors (HD) were enrolled. Results: At the baseline, compared to HD (n = 53), COVID-19 patients (n = 129) showed higher plasma levels of MMP-9 (p < 0.0001) and TIMP-1 (p < 0.0001) and the higher plasma activity of MMP-2 (p < 0.0001) and MMP-9 (p < 0.0001). In the ARDS group, higher plasma levels of MMP-9 (p = 0.0339) and TIMP-1 (p = 0.0044) and the plasma activity of MMP-2 (p = 0.0258) and MMP-9 (p = 0.0021) compared to non-ARDS was observed. A positive correlation between the plasma levels of TIMP-1 and chest computed tomography (CT) score (ρ = 0.2302, p = 0.0160) was observed. At the T post, a reduction in plasma levels of TIMP-1 (p < 0.0001), whereas an increase in the plasma levels of MMP-9 was observed (p = 0.0088). Conclusions: The positive correlation between TIMP-1 with chest CT scores highlights its potential use as a marker of fibrotic burden. At T post, the increase in plasma levels of MMP-9 and the reduction in plasma levels of TIMP-1 suggested that inflammation and fibrosis resolution were still ongoing.