The ability of digital breast tomosynthesis to reduce additional examinations in older women.

Aims: To assess the diagnostic performance of digital breast tomosynthesis (DBT) in older women across varying breast densities and to compare its effectiveness for cancer detection with 2D mammography and ultrasound (U/S) for different breast density categories. Furthermore, our study aimed to predict the potential reduction in unnecessary additional examinations among older women due to DBT. Methods: This study encompassed a cohort of 224 older women. Each participant underwent both 2D mammography and digital breast tomosynthesis examinations. Supplementary views were conducted when necessary, including spot compression and magnification, ultrasound, and recommended biopsies. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) were calculated for 2D mammography, DBT, and ultrasound. The impact of DBT on diminishing the need for supplementary imaging procedures was predicted through binary logistic regression. Results: In dense breast tissue, DBT exhibited notably heightened sensitivity and NPV for lesion detection compared to non-dense breasts (61.9% vs. 49.3%, p < 0.001) and (72.9% vs. 67.9%, p < 0.001), respectively. However, the AUC value of DBT in dense breasts was lower compared with non-dense breasts (0.425 vs. 0.670). Regarding the ability to detect calcifications, DBT demonstrated significantly improved sensitivity and NPV in dense breasts compared to non-dense breasts (100% vs. 99.2%, p < 0.001) and (100% vs. 94.7%, p < 0.001), respectively. On the other hand, the AUC value of DBT was slightly lower in dense breasts compared with non-dense (0.682 vs. 0.711). Regarding lesion detection for all cases between imaging examinations, the highest sensitivity was observed in 2D mammography (91.7%, p < 0.001), followed by DBT (83.7%, p < 0.001), and then ultrasound (60.6%, p < 0.001). In dense breasts, sensitivity for lesion detection was highest in 2D mammography (92.9%, p < 0.001), followed by ultrasound (76.2%, p < 0.001), and the last one was DBT. In non-dense breasts, sensitivities were 91% (p < 0.001) for 2D mammography, 50.7% (p < 0.001) for ultrasound, and 49.3% (p < 0.001) for DBT. In terms of calcification detection, DBT displayed significantly superior sensitivity compared to 2D mammography in both dense and non-dense breasts (100% vs. 91.4%, p < 0.001) and (99.2% vs. 78.5%, p < 0.001), respectively. However, the logistic regression model did not identify any statistically significant relationship (p > 0.05) between DBT and the four dependent variables. Conclusion: Our findings indicate that among older women, DBT does not significantly decrease the requirement for further medical examinations.

Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans.

Kidney tumor (KT) is one of the diseases that have affected our society and is the seventh most common tumor in both men and women worldwide. The early detection of KT has significant benefits in reducing death rates, producing preventive measures that reduce effects, and overcoming the tumor. Compared to the tedious and time-consuming traditional diagnosis, automatic detection algorithms of deep learning (DL) can save diagnosis time, improve test accuracy, reduce costs, and reduce the radiologist's workload. In this paper, we present detection models for diagnosing the presence of KTs in computed tomography (CT) scans. Toward detecting and classifying KT, we proposed 2D-CNN models; three models are concerning KT detection such as a 2D convolutional neural network with six layers (CNN-6), a ResNet50 with 50 layers, and a VGG16 with 16 layers. The last model is for KT classification as a 2D convolutional neural network with four layers (CNN-4). In addition, a novel dataset from the King Abdullah University Hospital (KAUH) has been collected that consists of 8,400 images of 120 adult patients who have performed CT scans for suspected kidney masses. The dataset was divided into 80% for the training set and 20% for the testing set. The accuracy results for the detection models of 2D CNN-6 and ResNet50 reached 97%, 96%, and 60%, respectively. At the same time, the accuracy results for the classification model of the 2D CNN-4 reached 92%. Our novel models achieved promising results; they enhance the diagnosis of patient conditions with high accuracy, reducing radiologist's workload and providing them with a tool that can automatically assess the condition of the kidneys, reducing the risk of misdiagnosis. Furthermore, increasing the quality of healthcare service and early detection can change the disease's track and preserve the patient's life.

Radiological and Histological Correlation in Small Cell Neuroendocrine Carcinoma of the Breast: A Case Report.

BACKGROUND Primary breast small cell neuroendocrine carcinoma is a rare subtype of breast cancer with about 57 cases reported in the literature. This rare type of cancer represents about 0.1% of breast carcinomas. Recently, the World Health Organization defined this type of cancer as a separate entity from other breast cancer types. The diagnosis of this type of cancer in the breast is difficult because the histological pattern is similar to the small cell neuroendocrine carcinoma of other more common primary sites of origin, including the lung. CASE REPORT A 39-year-old woman presented to our hospital with a left breast mass and recurrent mastitis. Physical examination revealed a painless lump in her left breast with a brown-colored discharge from the nipple, and her child refused breastfeeding from the left breast. A high-density well-defined rounded mass was observed upon mammography in the upper lateral aspect of the left breast. This mass lesion appeared hypoechoic with no posterior acoustic shadowing on ultrasound scan. A core-needle biopsy of the mass was performed and the diagnosis of small cell neuroendocrine carcinoma was rendered after histopathologic examination. Positron emission tomography scanning was helpful in the exclusion of primary origin from other organ sites; thus, the primary breast origin of the tumor was confirmed. CONCLUSIONS This case report provides a comprehensive approach to diagnose this type of small cell carcinoma originating primarily in the breast. The suspicion of this type of breast cancer should be raised if there is presence of characteristic histopathologic findings with the exclusion of any primary origin from other organ sites by the help of imaging studies.

The radiological characteristics of childhood intussusception including unusual features and rare pathological lead points.

PURPOSE: To describe the radiological characteristics for childhood intussusceptions including unusual radiological features and rare pathological lead points (PLP). MATERIAL AND METHODS: The medical records of all childhood intussusceptions between 1/1/2010 -1/10/2020 were retrospectively reviewed. 95 cases were identified in 82 patients. The demographic data, presenting symptoms, diagnostic and treatment methods, radiological features, and PLPs among the different types of intussusception were analyzed. RESULTS: Ileocolic intussusception (ICI) represented 53.7% (51/95). The average age for ICI was 1.87 years. Males constituted 72.1% (31/43). 29.4% (15/51) were treated primarily surgically due to peritonitis. Small bowel intussusception (SBI) represented 40% (38/95) in which females constituted 51.5% (17/33). Ileo-ileal represented 63.2% (24/38). 81.8% (27/33) were transient. On ultrasound; There was a statistically significant difference in the size of the outer diameter of ICI compared to SBI (P-value 0.00012). Ileo-ileocolic and colo-colic intussusceptions constituted 3.2% (3/95); each and were more common in females. Vomiting was the most common symptom for intussusception and ultrasound was diagnostic in the majority of cases. PLPs were seen in 36.6% (30/82) of the patients of which the average age was 7 years. PLPs/risk factors were benign in 80% (24/30). A case of colo-colic intussusception was seen in a 16-year-old female due to clear cell sarcoma which was not reported before. 12.2% patients (10/82) had recurrent intussusception. CONCLUSION: Our study showed that ICI is the most commonly encountered type. SBIs are mostly transient. It is important to radiologically determine the type of intussusception and to identify PLPs or unusual radiological features to avoid unnecessary intervention and significant patient morbidity.

Extraspinal findings prevalence and clinical significance in 4250 lumbar spine MRI exams.

To assess extraspinal findings (ESFs) prevalence in lumbar spine MRI, including clinically significant findings using a systematic approach, and to determine their reporting rate. Lumbar spine MRI scans were retrospectively reviewed over 18 months by two radiologists. Reading discrepancies were resolved by consensus. ESFs were classified according to the involved system, clinical diagnosis, and clinical significance. The reporting rate was estimated by referring to the original report. There were 1509 ESFs in 1322/4250 patients with a substantial agreement between the two radiologists (kappa = 0.8). Almost half (621/1322) were in the 45-60 age group. Females represented 56.6% (748/1322). 74.2% (1120/1509) of the ESFs involved the urinary system among which 79.6% (892/1120) were renal cysts. Clinically significant findings represented 8.7% (131/1509) among which hydronephrosis represented 23% (30/131). First time detected malignant lesions represented 4.6% (6/131). ESFs reporting rate was 47.3%. 58.8% of the clinically significant ESFs were not reported. ESFs prevalence was 31.1%. The Urinary system was the most commonly involved. Most ESFs were benign warranting no further workup. However, clinically significant ESF were not infrequently detected. More than half of the clinically significant findings were not reported. A systematic review of MRI images is highly recommended to improve patient's outcome.