Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging to enhance diagnostic accuracy, improve image quality, and reduce radiation exposure. The use of photon-counting CT provides superior image quality, reduced radiation dose, and material decomposition capabilities, while deep learning algorithms excel in automating image analysis and improving diagnostic accuracy. The integration of these technologies can lead to enhanced material decomposition and classification, spectral image analysis, predictive modeling for individualized medicine, workflow optimization, and radiation dose management. However, data requirements, computational resources, and regulatory and ethical concerns remain challenges that need to be addressed to fully realize the potential of this technology. The fusion of photon-counting CT and deep learning algorithms is poised to revolutionize medical imaging and transform patient care.

"Ring-shaped" meniscus and accompanying intermeniscal bridge meniscus: a rare combined variant resembling a bucket-handle tear.

Many anatomical variations have been described in the menisci, especially in the lateral meniscus. Among these, discoid meniscus is the most common variation. Others are described in the literature as double-layered meniscus, accessory meniscus, ring-shaped meniscus, and hypoplastic meniscus. Also, combined variations associated with ring-shaped meniscus have been described, and they can be confused with fragmented complex tears and cause unnecessary surgery. Increasing awareness of the imaging features of these accompanying combined variations may aid in the recognition and differentiation of this entity from meniscus tears. We report the case of a ring-shaped meniscus and accompanying intermeniscal bridge meniscus, which has not been described before in the literature, highlighting the MRI and arthroscopic imaging findings of it.

Is there an association between olfactory bulb volume and the Keros type of fossa olfactoria?

PURPOSE: The purpose of this study was to investigate the relationship between the volume of the olfactory bulb (OB), the depth of the olfactory sulcus (OS), the depth of the fossa olfactoria (FO), and the height of the OB. METHODS: A total of 54 patients participated (9 women and 45 men; mean [SD] age, 27 [38] y; range, 20-45 y). Magnetic resonance imaging was performed with a 1.5-T system (slice thickness, 1 mm). Measurements of the right and left OB volumes were performed through manual segmentation of the coronal slices. We measured the depth of the FO on the basis of Keros classification on coronal magnetic resonance images. The depth of the OS was measured on the coronal plane at the posterior tangent through the orbital globes. The height of the OB was measured on the coronal plane of the cribriform plate at the highest portion of the OB. RESULTS: The mean (SD) right OB volume was measured to be 52.21 (13.73) mm3 with a range between 33.90 and 95.70 mm3. The mean (SD) left OB volume was measured to be 53.98 (13.31) mm3 with a range between 31.20 and 94.10 mm3. Type 1, type 2, and type 3 Keros ratios of the FO bilaterally were 12.9% (7/54), 68.5% (37/54), and 3.7% (2/54), respectively. There was no significant relationship between the OB volume and ipsilateral Keros type of FO (right side: P = 0.208; left side: P = 0.164). Similarly, there was no significant relationship between the OB volume and depth of OS on both sides (right side: P = 0.073; left side: P = 0.065). There was no significant association between the Keros type of the right FO and depth of the OS (right side: P = 0.812; left side P = 0.863). CONCLUSIONS: We conclude that there is no statistical correlation between the OB volume and depth of the FO (Keros type). From the current study, it may be concluded that the depth of the FO may develop largely independent from OB volumes. The individuals without smell disorder have a wide range in OB volume. The method of OB volume measurement that we described is a valid measure of real OB volumes with high reproducibility.

Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources

Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) platforms have long served as a cornerstone in radiology education, offering rich visual content, interactive sessions, and peer-reviewed materials. They excel in teaching intricate concepts and techniques that necessitate visual aids, such as image interpretation and procedural demonstrations. However, Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI)-powered language model, has made its mark in radiology education. It can generate learning assessments, create lesson plans, act as a round-the-clock virtual tutor, enhance critical thinking, translate materials for broader accessibility, summarize vast amounts of information, and provide real-time feedback for any subject, including radiology. Concerns have arisen regarding ChatGPT's data accuracy, currency, and potential biases, especially in specialized fields such as radiology. However, the quality, accessibility, and currency of e-learning content can also be imperfect. To enhance the educational journey for radiology residents, the integration of ChatGPT with expert-curated e-learning resources is imperative for ensuring accuracy and reliability and addressing ethical concerns. While AI is unlikely to entirely supplant traditional radiology study methods, the synergistic combination of AI with traditional e-learning can create a holistic educational experience.

The implications of the presence of osteomyelitis on outcomes of infected diabetic foot wounds.

AIM: To assess the effect of the presence of osteomyelitis in patients with a diabetic foot infection. METHODS: We reviewed the records of diabetic patients hospitalized at our medical center for a foot infection over a 2-y period. Using clinical, imaging, and microbiology results, we classified each patient as having diabetic foot osteomyelitis (DFO) or not. We then compared several outcome criteria of interest between the 2 groups. RESULTS: Among 73 eligible patients, 37 were in the DFO group (DFO group), while the other 36 were in the soft tissue infection group (STI group). In comparison to the STI group, the DFO group had a significantly longer length of stay (LOS) in the hospital (42 (28.5-51) days vs 19.5 (13.2-29.5) days, p < 0.001), longer duration of antibiotic therapy (46.6 ± 19.9 days vs 22.0 ± 14.6 days, p < 0.001), longer duration of intravenous antibiotic therapy (32.3 ± 16.3 days vs 13.6 ± 14.3 days, p < 0.001), longer duration of wound before admission (44 (31-64.5) days vs 33 (23-45.5) days, p = 0.034), and longer time to wound healing (239.8 ± 108.2 days vs 183.1 ± 73 days, p = 0.011). There were more surgical procedures in the DFO group than in the STI group (24/37 (64.8%) vs 11/36 (30.5%), p = 0.003), and during hospitalization, 22 patients in the DFO group and 5 patients in STI group underwent minor amputation (59.4% vs 13.8%, p < 0.001). CONCLUSION: The presence of osteomyelitis negatively affects both the treatment and outcome of diabetic foot infections.

Improving radiology workflow using ChatGPT and artificial intelligence.

Artificial Intelligence is a branch of computer science that aims to create intelligent machines capable of performing tasks that typically require human intelligence. One of the branches of artificial intelligence is natural language processing, which is dedicated to studying the interaction between computers and human language. ChatGPT is a sophisticated natural language processing tool that can understand and respond to complex questions and commands in natural language. Radiology is a vital aspect of modern medicine that involves the use of imaging technologies to diagnose and treat medical conditions artificial intelligence, including ChatGPT, can be integrated into radiology workflows to improve efficiency, accuracy, and patient care. ChatGPT can streamline various radiology workflow steps, including patient registration, scheduling, patient check-in, image acquisition, interpretation, and reporting. While ChatGPT has the potential to transform radiology workflows, there are limitations to the technology that must be addressed, such as the potential for bias in artificial intelligence algorithms and ethical concerns. As technology continues to advance, ChatGPT is likely to become an increasingly important tool in the field of radiology, and in healthcare more broadly.

There may be a role for hyperbaric oxygen therapy in transient osteoporosis of the hip.

Transient osteoporosis of the hip (TOH) is a rare clinical condition with usually an unknown aetiology and which typically develops in middle-aged men, or in women in the third trimester of their pregnancy. It is characterized by transient osteopenia and by gradually increasing pain associated with a limitation of the range of motion of the hip. Bone marrow oedema is a typical but nonspecific finding in TOH. A 33-year-old female patient presented with severe hip pain one month after delivery. Her history was unremarkable except for a Hashimoto's Disease of 8 years' duration. Magnetic resonance imaging (MRI) showed significant bone marrow oedema with increased signal intensity in the femoral head on T2-weighted images. A diagnosis of TOH was made and the patient received a total of 30 sessions of hyperbaric oxygen (HBO) at 2.4 ATA, 2 hours each, in a multiplace chamber. Over the course of HBO treatment, her pain was gradually relieved and she became asymptomatic after one month together with a complete recovery of the range of motion of the hip. MRI of the hips 10 weeks after onset of HBO therapy showed normal signal intensity on T2-weighted images.

Relationship between Body Mass Index and Articular Injuries Accompanying Primary Anterior Cruciate Ligament Tear in Male Knees: A Retrospective Observational Study.

The objective of this study was to determine the effects of body mass index (BMI), as a modifiable risk factor, on meniscal, chondral, and ligamentous injuries, as well as on bone marrow edema accompanying anterior cruciate ligament (ACL) rupture. This retrospective observational study analyzed 84 male patients who underwent primary ACL reconstruction from 2015 to 2018. Magnetic resonance imaging was performed within 6 weeks of injury. Bone bruise, tendon, ligament, meniscal, and muscle injuries were evaluated. The surgery was performed within 3 months after the injury. Detailed arthroscopic findings (chondral, meniscal, and ligamentous injuries) were documented intraoperatively. The weight and height were used to quantify BMI (weight in kg/height in m2). Of the 84 male patients, 58 had associated articular injuries. The median age of the study population was 24 years (minimum: 17 years, maximum: 43 years) years. The mean BMI, height, and weight were 27.12 ± 0.78 kg/m2, 1.73 ± 0.01 m, and 81.17 ± 21.52 kg, respectively. The relationship between higher BMI and associated articular injuries (95% confidence interval [CI]) was statistically significant (p < 0.001). There was a statistically significant relationship between weight and associated articular injuries (p = 0.003). Height and age were not predictive factors. Higher BMI and weight were significant risk factors for associated articular injuries in the presence of ACL tear. Height was not found to be a predictive factor. Higher BMI was associated with increased risk of medial and/or lateral meniscus tears and bone bruising.

The Combined Effect of Body Mass Index and Tibial Slope Angles on Anterior Cruciate Ligament Injury Risk in Male Knees: A Case-Control Study.

INTRODUCTION: Tibial slope angles (TSAs) have been identified as potential risk factors of anterior cruciate ligament (ACL) injury in the literature. A higher body mass index (BMI) might increase the risk of ACL tear because of greater axial compressive force. The aim of this study was to determine the relationship of these factors and the combined effect of BMI and TSA in determination of risk potential for ACL injury. METHODS: The preoperative magnetic resonance (MR) images of 81 ACL-injured male knees and of 68 male individuals with no ACL injuries were evaluated by 2 radiologists to measure the TSA. The Mann-Whitney U-test was performed to indicate the significant difference in height, weight, and BMI values. The independent samples t-test was used to determine the differences between ACL-injured and non-injured groups regarding TSA values. Odds ratios were calculated by logistic regression tests, and receiver operating characteristics (ROC) curves revealed the area under the receiver operating characteristics curve (AUC) values to compare the relationships of these parameters with ACL injury. RESULTS: Body mass index, lateral tibial slope (LTS), and medial tibial slope (MTS) were predictive of ACL risk injury. Body mass index alone had the greatest effect among these parameters, and there were no statistically significant differences in coronal tibial slope values between the ACL-ruptured and control groups. The greatest AUC was observed for the combination of BMI, MTS, and LTS. CONCLUSIONS: Body mass index, LTS, and MTS angles were associated with ACL injury risk and BMI + MTS + LTS together revealed the greatest effect on ACL injury.