A Review of Artificial Intelligence in Breast Imaging.

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women's physical and mental health. Early breast cancer screening-through mammography, ultrasound, or magnetic resonance imaging (MRI)-can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI.

Medical magnetic resonance imaging publications in Arab countries: A 25-year bibliometric analysis.

Magnetic Resonance Imaging (MRI) is increasingly becoming a cornerstone in modern diagnostic healthcare, offering unparalleled capabilities in stroke, dementia, and cancer screening. Therefore, this study aims to map medical MRI literature affiliated with Arab countries, focusing on publication trends, top journals, author affiliations, study countries, and authors' collaboration, and keyword analysis. The scientific database used is the Scopus database. Microsoft Excel, VOSviewer software, and Biblioshiny for the Bibliometrix R package are the bibliometric tools used in this analysis. A total of 2592 publications were published between 1988 and 2022, with total citations of 22,115. Most of them were original articles (91,7%) and 89.9% were published in traditional journals. The number of total publications exhibited a steady increase over time, whereas total citations showed fluctuations, peaking in 2015 with 1571 citations for publications from that year. The most cited article was authored by Yaseen M. Arabi, receiving 286 citations. Saudi Arabia was the top active country. In addition, the most prolific author was Maha S Zaki, and the most prolific source was the "Egyptian Journal of Radiology and Nuclear Medicine". The most prolific affiliation was Cairo University. The "multiple sclerosis" and "case report" were the most trending keywords. The analysis revealed a significant growth in MRI research inside Arab countries, as shown by an increase in the total number of publications and international collaborations. Despite these developments, the results of this study suggest that there is still room for MRI research in the Arab region to advance. This can be achieved through increasing international collaboration and multidisciplinary work.

Early career accuracy of shoulder ultrasound in evaluating rotator cuff tendon tears.

Aim To compare the accuracy of shoulder ultrasound (US) in diagnosing rotator cuff tendon tears between junior and experienced musculoskeletal (MSK) radiologists. Also, to compare the overall ultrasound accuracy referenced to MRI. Methods A retrospective data collection for patients with clinically suspected rotator cuff tears who underwent ultrasound from June 2021 - June 2023 was conducted. Patients who also performed MRI for the same shoulder were only included in the study. US and MRI images were evaluated by two MSK radiologists with different experience levels. The diagnosis of rotator cuff tears was done on MRI through consensus. Ultrasound accuracy referenced to MRI was calculated for each radiologist. A second consensus was conducted for US images to calculate the overall US accuracy. The percentage of agreement and Cohen's kappa correlation coefficient were calculated before and after the US consensus. Results Forty-one patients were included in the study, 12 (29.3%) males and 29 (70.7%) females, with a mean age of 49.6 years. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and accuracy of US interpreted by junior vs experienced MSK radiologists for supraspinatus full thickness tears (FTTs) were 100% vs 91%, 90% vs 93%, 79% vs 83%, 100% vs 97%, and 93% vs 93%, respectively. After the second consensus, sensitivity, specificity, PPV and NPV, and accuracy were 91%, 90%, 77%, 96%, and 90%, respectively. Conclusion The accuracy of shoulder ultrasound in diagnosing supraspinatus FTTs by junior MSK radiologists compares well to the more experienced ones, but not for partial thickness tears (PTTs).

Bilateral spontaneous quadriceps tendon rupture: a case report and literature review.

Bilateral spontaneous quadriceps tendon rupture is a rare condition characterized by the simultaneous tear of the fibrous tissue connecting the quadriceps muscle to the patella bone. Prompt diagnosis is crucial for appropriate treatment and optimal outcomes. We present a case of a 70-year-old male with bilateral knee pain and an inability to walk, resulting from a trivial fall. Despite initial misdiagnosis, a thorough evaluation, including physical examination and imaging, revealed bilateral quadriceps tendon rupture. Surgical repair was performed, followed by a comprehensive rehabilitation program. At the four-month follow-up, the patient showed significant improvement in pain and function. This article provides a comprehensive review of the existing literature on bilateral quadriceps tendon rupture, emphasizing the challenges in the diagnosis and management of this rare condition. Early diagnosis, prompt surgical intervention, and a tailored rehabilitation program are crucial for successful outcomes.

Is There a Role for Ordering a DEXA (Dual Energy X-Ray Absorptiometry) Scan for Patients with Symptomatic Advanced Knee Osteoarthritis?

Background: Osteoarthritis of the knee (OA) and osteoporosis are two conditions that have a significant impact on society, have a great impact on quality of life, and can lead to functional impairment. However, the relationship between knee OA and osteoporosis is unclear. Objective: The aim of this study was to examine if there is a link between symptomatic advanced knee osteoarthritis and low bone mineral density. Methods: A total of 430 patients with symptomatic and advanced radiographic knee OA served as participants in this study. Plain radiographs were used to screen participants for osteoarthritis, and a Dual Energy X-ray Absorptiometry (DEXA) scan was used to determine each participant's bone mineral density (BMD). Results: The lumbar spine, whole femur, and femoral neck BMD levels were statistically higher in the early OA (Kelldren-Lawrence (KL) I and II) group compared with the advanced (III and IV) OA group. Higher BMD at the whole femur and femoral neck but not at the lumbar spine was observed when comparing patients with grades I, II, and III with patients with grade IV after adjustment for body mass index. Conclusion: The findings of this study indicate that the degree of knee OA is correlated with a decline in BMD. These findings lend credence to the theory that the two conditions may be linked to one another. Our study concluded that patients with advanced knee osteoarthritis are at risk of developing osteoporosis. As a result, orthopedic doctors are required to screen for osteoporosis in patients with advanced knee osteoarthritis to both prevent and treat osteoporosis at an earlier stage.

Perforated Stress Ulcer of the Duodenum: a Case of an Unexpected Diagnosis in a COVID-19 Patient Following Dilatation and Curettage Procedure.

Background: Stress ulcers in the upper gastrointestinal tract can arise from pathologies related to erosive or inflammatory insults in critically ill patients. The relationship between stressful bodily events and the ischemia and perforation of stress ulcers is poorly understood. Objective: We present a case of perforated stress ulcer following an abortion that was treated by dilatation and curettage (D&C) and complicated by a coronavirus disease 2019 (COVID-19) infection. Case presentation: A 40-year-old lady presented to the emergency room complaining of diffuse abdominal pain, she was recently diagnosed with an incomplete abortion and managed via a D&C procedure in an external hospital. A computed tomography (CT) scan was done at our center for the abdomen and pelvis, showing extensive pneumoperitoneum, which brought the radiologist's attention to suspect a small bowel perforation presumably accompanying a uterine perforation secondary to the D&C. There were no obvious signs of pelvic small bowel perforation in the initial CT images. The perforated duodenal stress ulcer was diagnosed the next day by a new CT scan following oral contrast ingestion and managed surgically by repair and omental patch, and no other bowel perforations were found upon surgical exploration. After the surgery, the patient was diagnosed with COVID-19, and her clinical status deteriorated gradually during the following week, and she passed away from a cardiac arrest. Conclusion: It is unclear whether septic abortion or COVID-19 has resulted in stress ulcer perforation in our patient. This case report highlights the importance of raising early suspicion in the diagnosis of stress ulcer perforation in critically ill patients to reduce the risk of morbidity and mortality.

Predicting the Severity of COVID-19 from Lung CT Images Using Novel Deep Learning.

Purpose: Coronavirus 2019 (COVID-19) had major social, medical, and economic impacts globally. The study aims to develop a deep-learning model that can predict the severity of COVID-19 in patients based on CT images of their lungs. Methods: COVID-19 causes lung infections, and qRT-PCR is an essential tool used to detect virus infection. However, qRT-PCR is inadequate for detecting the severity of the disease and the extent to which it affects the lung. In this paper, we aim to determine the severity level of COVID-19 by studying lung CT scans of people diagnosed with the virus. Results: We used images from King Abdullah University Hospital in Jordan; we collected our dataset from 875 cases with 2205 CT images. A radiologist classified the images into four levels of severity: normal, mild, moderate, and severe. We used various deep-learning algorithms to predict the severity of lung diseases. The results show that the best deep-learning algorithm used is Resnet101, with an accuracy score of 99.5% and a data loss rate of 0.03%. Conclusion: The proposed model assisted in diagnosing and treating COVID-19 patients and helped improve patient outcomes.

Showering gas bubbles within the inferior vena cava detected sonographically can unmask a hidden infection: a case report of a rare presentation in a patient with emphysematous cystitis.

We present a case of incidentally discovered gas bubbles flowing within the inferior vena cava during a routine abdominal sonographic examination, that subsequently unmasked a previously undiagnosed emphysematous cystitis.