A Unique Case of Eight Fetuses in a Single Fetu.

Fetus in fetu is a rare congenital anomaly in which a malformed parasitic twin is found within the body of a living child or adult. In this case report, a 1-day-old child presented with a large firm abdominal mass on the left side of the upper abdomen. Imaging studies misdiagnosed the mass as an intraperitoneal benign dermoid cyst displacing the bowel loops and internal viscera. A surgical resection was performed on 21 days of life, and pathology confirmed eight fetuses inside the cyst.

Greater burden of white matter lesions and silent infarcts ipsilateral to carotid stenosis.

OBJECTIVES: Carotid stenosis may cause silent cerebrovascular disease (CVD) through atheroembolism and hypoperfusion. If so, revascularization may slow progression of silent CVD. We aimed to compare the presence and severity of silent CVD to the degree of carotid bifurcation stenosis by cerebral hemisphere. MATERIALS AND METHODS: Patients age ≥40 years with carotid stenosis >50% by carotid ultrasound who underwent MRI brain from 2011-2015 at Mayo Clinic were included. Severity of carotid stenosis was classified by carotid duplex ultrasound as 50-69% (moderate), 70-99% (severe), or occluded. White matter lesion (WML) volume was quantified using an automated deep-learning algorithm applied to axial T2 FLAIR images. Differences in WML volume and prevalent silent infarcts were compared across hemispheres and severity of carotid stenosis. RESULTS: Of the 183 patients, mean age was 71±10 years, and 39.3% were female. Moderate stenosis was present in 35.5%, severe stenosis in 46.5% and occlusion in 18.0%. Patients with carotid stenosis had greater WML volume ipsilateral to the side of carotid stenosis than the contralateral side (mean difference, 0.42±0.21cc, p=0.046). Higher degrees of stenosis were associated with greater hemispheric difference in WML volume (moderate vs. severe; 0.16±0.27cc vs 0.74±0.31cc, p=0.009). Prevalence of silent infarct was 23.5% and was greater on the side of carotid stenosis than the contralateral side (hemispheric difference 8.8%±3.2%, p=0.006). Higher degrees of stenosis were associated with higher burden of silent infarcts (moderate vs severe, 10.8% vs 31.8%; p=0.002). CONCLUSIONS: WML and silent infarcts were greater on the side of severe carotid stenosis.

Transradial versus transfemoral arterial access in the uterine artery embolization of fibroids.

Purpose: Transradial arterial access has become more popular in body interventional procedures but has not been ubiquitously adapted. This retrospective study assesses the efficacy of this approach in uterine artery embolization. Aim of the study was to compare transradial to transfemoral arterial access in patients undergoing uterine artery embolization for the treatment of fibroids. Material and methods: A total of 172 patients underwent uterine artery embolization procedures at our institute from October 2014 to June 2020. Of these, 76 patients had their operations performed via transfemoral access while 96 underwent transradial access. The peak radiation dose, fluoroscopy time, procedure time, total contrast volume, and equipment cost for each procedure were all reviewed to evaluate for statistical differences between the 2 groups. Results: All cases were technically successful without major complications. The average peak skin dose was 2281 mGy,with no statistical difference between the transradial or transfemoral cohorts. Average fluoroscopy time was 25 minutes, also with no statistical difference between the subsets. Mean procedure time was 100 min, and mean contrast volume usage was 138 mL with no statistical differences. Similarly, the average equipment cost was $2204, with no significant differences found between transradial and transfemoral access. Conclusions: With respect to many pertinent radiation parameters, transradial access was evaluated as being an equally efficacious alternative to transfemoral access in uterine artery embolization procedures. The results of this study suggest that transradial access should be considered more often, whenever viable, as an option in the uterine artery embolization treatment of fibroids.

Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use.

Coronary computed tomography angiography (CCTA) evaluation of chest pain patients in an emergency department (ED) is considered appropriate. While a "negative" CCTA interpretation supports direct patient discharge from an ED, labor-intensive analyses are required, with accuracy in jeopardy from distractions. We describe the development of an artificial intelligence (AI) algorithm and workflow for assisting qualified interpreting physicians in CCTA screening for total absence of coronary atherosclerosis. The two-phase approach consisted of (1) phase 1-development and preliminary testing of an algorithm for vessel-centerline extraction classification in a balanced study population (n = 500 with 50% disease prevalence) derived by retrospective random case selection, and (2) phase 2-simulated clinical Trialing of developed algorithm on a per-case (entire coronary artery tree) basis in a more "real-world" study population (n = 100 with 28% disease prevalence) from an ED chest pain series. This allowed pre-deployment evaluation of the AI-based CCTA screening application which provides vessel-by-vessel graphic display of algorithm inference results integrated into a clinically capable viewer. Algorithm performance evaluation used area under the receiver operating characteristic curve (AUC-ROC); confusion matrices reflected ground truth vs AI determinations. The vessel-based algorithm demonstrated strong performance with AUC-ROC = 0.96. In both phase 1 and phase 2, independent of disease prevalence differences, negative predictive values at the case level were very high at 95%. The rate of completion of the algorithm workflow process (96% with inference results in 55-80 s) in phase 2 depended on adequate image quality. There is potential for this AI application to assist in CCTA interpretation to help extricate atherosclerosis from chest pain presentations.

Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.

Collecting and curating large medical-image datasets for deep neural network (DNN) algorithm development is typically difficult and resource-intensive. While transfer learning (TL) decreases reliance on large data collections, current TL implementations are tailored to two-dimensional (2D) datasets, limiting applicability to volumetric imaging (e.g., computed tomography). Targeting performance enhancement of a DNN algorithm based on a small image dataset, we assessed incremental impact of 3D-to-2D projection methods, one supporting novel data augmentation (DA); photometric grayscale-to-color conversion (GCC); and/or TL on training of an algorithm from a small coronary computed tomography angiography (CCTA) dataset (200 examinations, 50% with atherosclerosis and 50% atherosclerosis-free) producing 245 diseased and 1127 normal coronary arteries/branches. Volumetric CCTA data was converted to a 2D format creating both an Aggregate Projection View (APV) and a Mosaic Projection View (MPV), supporting DA per vessel; both grayscale and color-mapped versions of each view were also obtained. Training was performed both without and with TL, and algorithm performance of all permutations was compared using area under the receiver operating characteristics curve. Without TL, APV performance was 0.74 and 0.87 on grayscale and color images, respectively, compared to 0.90 and 0.87 for MPV. With TL, APV performance was 0.78 and 0.88 on grayscale and color images, respectively, compared with 0.93 and 0.91 for MPV. In conclusion, TL enhances performance of a DNN algorithm from a small volumetric dataset after proposed 3D-to-2D reformatting, but additive gain is achieved with application of either GCC to APV or the proposed novel MPV technique for DA.

Geospatial assessment of tourism impact on land environment of Dehradun, Uttarakhand, India.

India's tourism industry has emerged as a leading industry with a potential to grow further in the next few decades. Dehradun, one of the famous tourist places in India located in the state of Uttarakhand, attracts tourist from all over the country and abroad. The surge in tourist number paved the way for new infrastructure projects like roads, buildings, and hotels, which in turn affects the topography of the mountainous region. In this study, remote sensing and GIS techniques have been used to assess the impact of tourism on the land environment of Dehradun. Satellite images of the years 1972, 2000, and 2016 were analyzed using object-based image analysis (OBIA) to derive land use and land cover (LULC) and ASTER-DEM (Digital Elevation Model) was used to determine the topography of the study area. LULC classification includes built-up, vegetation, forest, scrub, agriculture, plantation, and water body. The slope of the region was categorized as gentle, moderate, strong, extreme, steep, and very steep. To assess the sprawl of built-up on high terrain land, built-up class of LULC was overlaid on slope classes. The overlay analysis reveals that due to increase in tourism, the land use in terms of the built-up area has been extended from gentle slope to very steep slope. The haphazard construction on the extreme, steep, and very steep slope is prone to landslide and other natural disasters. For this, landslide susceptibility maps have also been generated using multicriteria evaluation (MCE) techniques to prevent haphazard construction and to assist in further planning of Dehradun City. This study suggests that a proper developmental plan of the city is essential which follows the principles of optimum use of land and sustainable tourism.

Fully Automated Agatston Score Calculation From Electrocardiography-Gated Cardiac Computed Tomography Using Deep Learning and Multi-Organ Segmentation: A Validation Study.

To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calcium quantification was performed using a neural network based on mask regions with convolutional neural networks (R-CNNs) for multi-organ segmentation. Manual evaluation of calcium was carried out using proprietary software. This is a retrospective study of archived data. This study used 40 patients to train the segmentation model and 110 patients were used for the validation of the algorithm. The Pearson correlation coefficient between the reference actual and the computed predictive scores shows high level of correlation (0.84; P < .001) and high limits of agreement (±1.96 SD; -2000, 2000) in Bland-Altman plot analysis. The proposed method correctly classifies the risk group in 75.2% and classifies the subjects in the same group. In total, 81% of the predictive scores lie in the same categories and only seven patients out of 110 were more than one category off. For the presence/absence of coronary artery calcifications, the deep learning model achieved a sensitivity of 90% and a specificity of 94%. Fully automated model shows good correlation compared with reference standards. Automating process reduces evaluation time and optimizes clinical calcium scoring without additional resources.

Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge.

The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography systems, models built using data from one system do not generalize well to other systems. Though federated learning (FL) has emerged as a way to improve the generalizability of AI without the need to share data, the best way to preserve features from all training data during FL is an active area of research. To explore FL methodology, the breast density classification FL challenge was hosted in partnership with the American College of Radiology, Harvard Medical Schools' Mass General Brigham, University of Colorado, NVIDIA, and the National Institutes of Health National Cancer Institute. Challenge participants were able to submit docker containers capable of implementing FL on three simulated medical facilities, each containing a unique large mammography dataset. The breast density FL challenge ran from June 15 to September 5, 2022, attracting seven finalists from around the world. The winning FL submission reached a linear kappa score of 0.653 on the challenge test data and 0.413 on an external testing dataset, scoring comparably to a model trained on the same data in a central location.

Large pelvic masses of obscure origin: urologist's perspective.

BACKGROUND: Large pelvic masses pose unique diagnostic and therapeutic challenges due to varied aetiology, paucity of characteristic imaging features, lack of therapeutic algorithms and surgical difficulties in resection inside the narrow confines of the pelvis with close proximity of vital structures. METHODS: Records of 22 patients with large pelvic masses in the last six years were analysed. Their demographic and clinical features were noted, along with imaging features, preoperative biopsy, surgical procedure, intraoperative difficulties, complications, adjuvant therapy and outcome. RESULTS: There were 14 men and 8 women with a median age of 45 years. Presenting symptoms were abdominal mass, pain, lower urinary tract symptoms, urinary retention and constipation. Imaging was mostly unable to determine the organ of origin of the tumour. Histopathology revealed pelvic fibromatosis (2), chondrosarcoma (1), liposarcoma (1), haemangioendothelioma (1), lymphangioma (2), fibroleiomyoma (1), leiomyosarcoma (3), schwannoma (4), malignant nerve sheath tumour (1), rectal gastrointestinal stromal tumour (1), retrovesical hydatid cysts (3), sacral chordoma (1) and Ewing's sarcoma (1). In 5 patients complete excision was not possible because of extension into vital structures. Fifteen patients were alive at 1-5 years of follow-up. CONCLUSIONS: Urologists, being the 'gatekeepers of the pelvis', are usually involved in the management of large pelvic masses. Good outcome can be achieved with careful surgical planning.

Transradial versus transfemoral arterial access in DEB-TACE for hepatocellular carcinoma.

Objectives: Transradial access has become increasingly popular in body interventional procedures but has not been ubiquitously adapted. This retrospective study compares the efficacy of this approach versus transfemoral access in hepatocellular carcinoma (HCC) patients who underwent drug-eluting bead transarterial chemoembolization (DEB-TACE). Materials and Methods: A total of 130 HCC patients underwent 146 DEB-TACE procedures within our institution from June 2015 to May 2020. About 90 and 56 procedures were logged for the transradial and transfemoral cohorts, respectively. Peak skin dose, fluoroscopy time, administered contrast volume, total procedure time, and equipment cost data for each procedure were reviewed to evaluate for statistical differences between the two groups. Results: All 146 cases were technically successful without major complications or access failures in either group. No statistical differences were present between the two access groups in regards to peak skin dose or fluoroscopy time. Transradial access recorded a significantly higher contrast volume (P < 0.05), and a significantly longer procedural time than transfemoral access (P < 0.01). However, transradial access also displayed a significantly lower procedural equipment cost (P < 0.01) between the two groups. Conclusion: Transradial DEB-TACE has similar trends to transfemoral DEB-TACE in several pertinent radiation parameters and is also significantly more cost-efficacious. The results of this investigation suggest the consideration of transradial access whenever viable as an alternative to transfemoral access in the DEB-TACE treatment of HCC patients.