Nuck Canal Endometriosis Following IVF Attempts in a Young Patient-Report of a Case.

INTRODUCTION: Endometriosis is a common benign condition affecting 10-15% of women of reproductive age. An unusual site of endometriosis is the canal of Nuck, which is a physiologically obliterated space in women spanning the area from the deep inguinal ring to the labia majora. CASE PRESENTATION: A 37-year-old woman, with a past medical history of several in vitro fertilization attempts, presented with a right-sided painful inguinal mass. She was subsequently offered surgical exploration and excision of the lesion, which revealed the presence of endometrial glands and stroma. DISCUSSION: Despite being a relatively common and benign pelvic condition, endometriosis can rarely manifest in the inguinal region, within the canal of Nuck. The treating physician should be cognizant of Nuck canal endometriosis, especially in young female patients presenting with an irreducible mass in the inguinal region and associated cyclic pain or infertility. CONCLUSION: When clinically and radiologically suspected, surgical excision is indicated to establish the diagnosis, provide symptomatic relief and guide further decision making.

Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28-83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Biodegradable Microspheres for Transarterial Chemoembolization in Malignant Liver Disease.

Transarterial chemoembolization (TACE) has revolutionized the treatment landscape for malignant liver disease, offering localized therapy with reduced systemic toxicity. This manuscript delves into the use of degradable microspheres (DMS) in TACE, exploring its potential advantages and clinical applications. DMS-TACE emerges as a promising strategy, offering temporary vessel occlusion and optimized drug delivery. The manuscript reviews the existing literature on DMS-TACE, emphasizing its tolerability, toxicity, and efficacy. Notably, DMS-TACE demonstrates versatility in patient selection, being suitable for both intermediate and advanced stages. The unique properties of DMS provide advantages over traditional embolic agents. The manuscript discusses the DMS-TACE procedure, adverse events, and tumor response rates in HCC, ICC, and metastases.

Factors Impacting Microwave Ablation Zone Sizes: A Retrospective Analysis.

PURPOSE: Evaluation of the influence of intrinsic and extrinsic conditions on ablation zone volumes (AZV) after microwave ablation (MWA). METHODS: Retrospective analysis of 38 MWAs of therapy-naïve liver tumours performed with the NeuWave PR probe. Ablations were performed either in the 'standard mode' (65 W, 10 min) or in the 'surgical mode' (95 W, 1 min, then 65 W, 10 min). AZV measurements were obtained from contrast-enhanced computed tomography immediately post-ablation. RESULTS: AZVs in the 'standard mode' were smaller than predicted by the manufacturer (length 3.6 ± 0.6 cm, 23% below 4.7 cm; width 2.7 ± 0.6, 23% below 3.5 cm). Ablation zone past the tip was limited to 6 mm in 28/32 ablations. Differences in AZV between the 'surgical mode' and 'standard mode' were not significant (15.6 ± 7.8 mL vs. 13.9 ± 8.8 mL, p = 0.6). AZVs were significantly larger in case of hepatocellular carcinomas (HCCs) (n = 19) compared to metastasis (n = 19; 17.8 ± 9.9 mL vs. 10.1 ± 5.1 mL, p = 0.01) and in non-perivascular tumour location (n = 14) compared to perivascular location (n = 24, 18.7 ± 10.4 mL vs. 11.7 ± 6.1 mL, p = 0.012), with both factors remaining significant in two-way analysis of variance (HCC vs. metastasis: p = 0.02; perivascular vs. non-perivascular tumour location: p = 0.044). CONCLUSION: Larger AZVs can be expected in cases of HCCs compared with metastases and in non-perivascular locations. Using the 'surgical mode' does not increase AZV significantly.

AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.

OBJECTIVES: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence. METHODS: We included n = 1591 multicenter, multivendor chest CT scans and divided them into AI training and validation datasets to develop an AI algorithm (n = 991 CT scans; n = 462 COVID-19, and n = 529 CAP) from three centers in China. An independent Chinese and German test dataset of n = 600 CT scans from six centers (COVID-19 / CAP; n = 300 each) was used to test the performance of eight blinded radiologists and the AI algorithm. A subtest dataset (180 CT scans; n = 90 each) was used to evaluate the radiologists' performance without and with AI assistance to quantify changes in diagnostic accuracy, reporting time, and diagnostic confidence. RESULTS: The diagnostic accuracy of the AI algorithm in the Chinese-German test dataset was 76.5%. Without AI assistance, the eight radiologists' diagnostic accuracy was 79.1% and increased with AI assistance to 81.5%, going along with significantly shorter decision times and higher confidence scores. CONCLUSION: This large multicenter study demonstrates that AI assistance in CT-based differentiation of COVID-19 and CAP increases radiological performance with higher accuracy and specificity, faster diagnostic time, and improved diagnostic confidence. KEY POINTS: • AI can help radiologists to get higher diagnostic accuracy, make faster decisions, and improve diagnostic confidence. • The China-German multicenter study demonstrates the advantages of a human-machine interaction using AI in clinical radiology for diagnostic differentiation between COVID-19 and CAP in CT scans.

COVID-19 pneumonia and its lookalikes: How radiologists perform in differentiating atypical pneumonias.

PURPOSE: To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens. METHODS: Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia. RESULTS: The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% ± 4 (SD), 79% ± 6 (SD), and 90% ± 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively. CONCLUSIONS: Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.

Simultaneous presence of the "bullseye" and "reversed halo" sign at CT of COVID-19 pneumonia: A case report.

The "bullseye" sign has been exclusively reported in patients suffering from coronavirus disease 2019 (COVID-19) pneumonia. It is theorized that this newly recognized computed tomography (CT) feature represents a sign of organizing pneumonia. Well established signs of organizing pneumonia also reported in COVID-19 patients include linear opacities, the "reversed halo" sign (or "atoll" sign), and a perilobular distribution of abnormalities. These findings are usually present on imaging in the intermediate and late stage of the disease. This is a case of simultaneous presence of the "bullseye" and the "reversed halo" sign on chest CT images of a COVID-19 patient examined 22 days after symptom onset.

Fully Automated Segmentation of Pulmonary Fibrosis Using Different Software Tools.

OBJECTIVE: Evaluation of software tools for segmentation, quantification, and characterization of fibrotic pulmonary parenchyma changes will strengthen the role of CT as biomarkers of disease extent, evolution, and response to therapy in idiopathic pulmonary fibrosis (IPF) patients. METHODS: 418 nonenhanced thin-section MDCTs of 127 IPF patients and 78 MDCTs of 78 healthy individuals were analyzed through 3 fully automated, completely different software tools: YACTA, LUFIT, and IMBIO. The agreement between YACTA and LUFIT on segmented lung volume and 80th (reflecting fibrosis) and 40th (reflecting ground-glass opacity) percentile of the lung density histogram was analyzed using Bland-Altman plots. The fibrosis and ground-glass opacity segmented by IMBIO (lung texture analysis software tool) were included in specific regression analyses. RESULTS: In the IPF-group, LUFIT outperformed YACTA by segmenting more lung volume (mean difference 242 mL, 95% limits of agreement -54 to 539 mL), as well as quantifying higher 80th (76 HU, -6 to 158 HU) and 40th percentiles (9 HU, -73 to 90 HU). No relevant differences were revealed in the control group. The 80th/40th percentile as quantified by LUFIT correlated positively with the percentage of fibrosis/ground-glass opacity calculated by IMBIO (r = 0.78/r = 0.92). CONCLUSIONS: In terms of segmentation of pulmonary fibrosis, LUFIT as a shape model-based segmentation software tool is superior to the threshold-based YACTA, tool, since the density of (severe) fibrosis is similar to that of the surrounding soft tissues. Therefore, shape modeling as used in LUFIT may serve as a valid tool in the quantification of IPF, since this mainly affects the subpleural space.

Postoperative acute pancreatitis is a serious but rare complication after distal pancreatectomy.

BACKGROUND: The clinical relevance of hyperamylasemia after distal pancreatectomy (DP) remains unclear and no internationally accepted definition of postoperative acute pancreatitis (POAP) exists. The aim of this study was to characterize POAP after DP and to assess the role of serum amylase (SA) in POAP. METHODS: Outcomes of 641 patients who had undergone DP between 2015 and 2019 were analyzed. Postoperative SA was determined in all patients. POAP was defined based on contrast-enhanced computed tomography (CT) or intraoperative findings during relaparotomy. RESULTS: An elevation of SA on postoperative day 1 (hyperamylasemiaPOD1) was found in 398 patients (62.1%). Twelve patients (1.87%) were identified with POAP. Ten patients demonstrated radiologic criteria for POAP and in two patients POAP was diagnosed during relaparotomy. Outcome of POAP patients was worse than that of patients with hyperamylasemiaPOD1 alone and that with normal SAPOD1 without POAP evidence (postoperative pancreatic fistula 50% vs 30.6% vs 18.5%; length of hospital stay 26 days vs 12 vs 11, respectively). The overall 90-day mortality of all 641 patients was 0.6%. CONCLUSION: POAP is a serious but rare complication after DP. HyperamylasemiaPOD1 is of prognostic relevance after DP, but it seems not sufficient as a single parameter to diagnose POAP.

Hyperamylasemia and acute pancreatitis after pancreatoduodenectomy: Two different entities.

BACKGROUND: Serum amylase activity greater than the institutional upper limit of normal (hyperamylasemia) on postoperative day 0-2 has been suggested as a criterion to define postoperative acute pancreatitis after pancreatoduodenectomy, but robust evidence supporting this definition is lacking. BACKGROUND: To assess the clinical impact of hyperamylasemia after pancreatoduodenectomy and to define postoperative acute pancreatitis. METHODS: Data of 1,235 consecutive patients who had undergone pancreatoduodenectomy between January 2010 and December 2014 were extracted from a prospective database and analyzed. Postoperative acute pancreatitis was defined based on the computed tomography severity index. Logistic regression modeling was used to calculate the postoperative acute pancreatitis rate of the entire study population. RESULTS: Hyperamylasemia on postoperative day 1 was found in 52% of patients after pancreatoduodenectomy. Patients with hyperamylasemia on postoperative day 1 had statistically significantly greater morbidity and mortality than patients with a normal serum amylase activity on postoperative day 1 with the rates of postoperative pancreatic fistula of 14.5% vs 2.1%, and 90-day mortality of 6.6% vs 2.2%, respectively. Of the 364 patients who underwent postoperative computed tomography, 103 (28%) had radiologic signs of acute pancreatitis, thus defining them as having postoperative acute pancreatitis by our definition. Logistic regression modeling showed a 14.7% rate of postoperative acute pancreatitis for the entire patient cohort and 29.2% for patients with hyperamylasemia on postoperative day 1. Outcomes of patients with postoperative acute pancreatitis defined based on the computed tomography severity index showed a rate of postoperative pancreatic fistula of 32.4% and a 90-day mortality rate of 11.8%, which were worse than those of patients with hyperamylasemia on postoperative day 1 alone. CONCLUSION: Hyperamylasemia on postoperative day 1 is a frequent finding after pancreatoduodenectomy, but hyperamylasemia on postoperative day 1 alone is not synonymous with postoperative acute pancreatitis because only 29.2% of such patients have acute pancreatitis based on computed tomography findings. Postoperative acute pancreatitis is a dangerous complication after pancreatoduodenectomy, but its prevalence, according to the gold standard of CT, is not as high as reported previously. Our data suggest that hyperamylasemia on postoperative day 1 and postoperative acute pancreatitis are 2 different entities.