Psoas Cross-Sectional Measurements Using Manual CT Segmentation before and after Endovascular Aortic Repair (EVAR).

Sarcopenia has been associated with an increased incidence of adverse outcomes, including higher mortality, after endovascular aortic repair (EVAR). We aim to use computed tomography (CT) to quantify changes in total psoas muscles area (PMA) and psoas muscle density (PMD) after EVAR, and to evaluate the reproducibility of both measurements. PMA and PMD were assessed via manual segmentation of the psoas muscle on pre- and post-operative CT scans belonging to consecutive patients who underwent EVAR. Wilcoxon test was used to compare PMA and PMD before and after EVAR, and inter- and intra-reader agreements of both methods were evaluated through Bland−Altman analysis. A total of 50 patients, 42 of them males (84%), were included in the study. PMA changes from 1243 mm2 (1006−1445 mm2) to 1102 mm2 (IQR 937−1331 mm2), after EVAR (p < 0.001). PMD did not vary between pre-EVAR (33 HU, IQR 26.5−38.7 HU) and post-EVAR (32 HU, IQR 26−37 HU, p = 0.630). At inter-reader Bland−Altman analysis, PMA showed a bias of 64.0 mm2 and a coefficient of repeatability (CoR) of 359.2 mm2, whereas PMD showed a bias of −2.43 HU and a CoR of 6.19 HU. At intra-reader Bland−Altman analysis, PMA showed a bias of −81.1 mm2 and a CoR of 394.6 mm2, whereas PMD showed a bias of 1.41 HU and a CoR of 6.36 HU. In conclusion, PMA decreases after EVAR. A good intra and inter-reader reproducibility was observed for both PMA and PMD. We thus propose to use PMA during the follow-up of patients who underwent EVAR to monitor muscle depletion after surgery.

Computed Tomography-Based Body Composition in Patients With Ovarian Cancer: Association With Chemotoxicity and Prognosis.

PURPOSE: To assess the association between computed tomography (CT)-derived quantitative measures of body composition profiling and chemotherapy-related complications, in terms of dose reduction, premature discontinuation of chemotherapy, and cycle delays in patients with ovarian cancer. Secondary purposes were to evaluate associations between sarcopenia and survival, and to evaluate differences in body composition profiling at baseline and after neoadjuvant chemotherapy. MATERIALS AND METHODS: The study population was retrospectively selected from a database of patients with newly diagnosed ovarian cancer (any stage) referred to our Institution between Feb 2011 and Mar 2020. Clinical data were recorded, and CT images at the level of the 3rd lumbar vertebra were stored. By using specific software, skeletal muscle area (SMA), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle density (SMD) were extracted. Skeletal muscle index (SMI) was then calculated. Statistical analysis was performed by logistic regression models to identify body composition features predictive of dose reduction, premature end of chemotherapy, and cycle delays. Kaplan-Meier analyses were performed to assess overall survival (OS) and progression-free survival (PFS). The log-rank test was used to determine differences in OS and PFS between sarcopenic and non-sarcopenic patients. Wilcoxon test was performed to compare body composition features before and after neoadjuvant chemotherapy (NACT). RESULTS: Sixty-nine patients were included. A significant association was found between VAT and cycle delays (OR = 1.01, z = 2.01, 95% CI: 1.00-1.02, p < 0.05), between SMA and early discontinuation of chemotherapy (OR = 1.03, z = 2.10, 95% CI: 1.00-1.05, p < 0.05), and between mean SMD and cycle delays (OR = 0.92, z = -2.70, 95%CI: 0.87-0.98, p < 0.01). No significant difference emerged for OS in sarcopenic and non-sarcopenic patients, nor in CT body composition features before and after NACT. CONCLUSIONS: In ovarian cancer patients, CT-derived body composition profiling might predict the risk of chemotoxicity. In particular, VAT and SMD are associated with chemotherapy cycle delays, and SMA with early discontinuation of chemotherapy.

Radiomics in cervical and endometrial cancer.

Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer. Nonetheless, cervical cancer is the most frequent gynecological malignancy in developing countries and endometrial cancer is the most common in western countries. The purpose of this narrative review is to give an overview of the latest published papers evaluating the role of radiomics in cervical and endometrial cancer, mostly evaluating association with tumor prognostic factors, with response to therapy and with prediction of recurrence and distant metastasis.

Do oncologists prefer subspecialty radiology reports? A quality care study.

BACKGROUND: The main objective was to assess whether CT reports of radiologists subspecialized in oncologic imaging respond better to oncological referrals than reports from general radiologists. The secondary objective was to assess differences in ratings between a senior and junior oncologist. Two hundred radiological reports pertaining to oncological patients were retrospectively selected of which 100 each were written by subspecialized radiologists and general radiologists, respectively. The senior and junior oncologists each rated all CT reports using a Likert scale from 1 to 5 (1 = very poor, 5 = excellent) for the following information: anatomical details; interpretation of findings; need for further explanations; appropriateness of conclusions; overall satisfaction. Comparisons between ratings assigned to reports from generalist radiologists and subspecialty radiologists were performed using the Mann-Whitney U test. Agreement between both oncologists was assessed through Gwet's coefficient. RESULTS: For all but two of the five items obtained from the senior oncologist, oncologists' ratings were significantly higher for subspecialty radiologists' reports (p < 0.01); mean values from both oncologists were generally higher for subspecialty reports (p < 0.001). Agreement between the senior and junior oncologist in the rating of reports from general and subspecialty radiologists was either moderate to substantial (0.5986-0.6788) or substantial to almost perfect (0.6958-0.8358). CONCLUSIONS: According to a senior and junior oncologist, CT reports performed by subspecialized radiologists in oncologic imaging are clearer, more accurate, and more appropriate in the interpretation and conclusions compared to reports written by general radiologists. Likewise, the overall satisfaction of the oncologist from a subspecialized radiologist report is higher.

Quantification of heterogeneity to classify benign parotid tumors: a feasibility study on most frequent histotypes.

Aim: To differentiate Warthin tumors (WTs) and pleomorphic adenomas (PAs) measuring heterogeneity of intravoxel incoherent motion (IVIM) and dynamic-contrast enhanced-magnetic resonance imaging biomarkers. Methods: Volumes of interest were traced on 18 WT and 18 PA in 25 patients. For each IVIM and dynamic-contrast enhanced biomarker, histogram parameters were calculated and then compared using the Wilcoxon-signed-rank test. Receiver operating characteristic curves and multivariate analysis were employed to identify the parameters and their pairs with the best accuracy. Results: Most of the biomarkers exhibited significant difference (p < 0.05) between PA and WT for histogram parameters. Time to peak median and skewness, and D* median and entropy showed the highest area under the curve. No meaningful improvement of accuracy was obtained using two features. Conclusion: IVIM and dynamic-contrast enhanced histogram descriptors may help in the classification of WT and PA.