The Relationship between Types of Os Trigonum and Findings of Conventional Ankle Magnetic Resonance Imaging: A Study Based on Three-Dimensional Magnetic Resonance Imaging.

This study aimed to investigate the dimensions and types of the os trigonum and evaluate their relationship with various pathologic conditions on the posterior ankle using ankle MRI images. A total of 124 non-contrast-enhanced ankle and foot MR images of 123 consecutive patients were included in this retrospective study. The images were presented randomly, and they contained no patient information. The MR images were retrospectively and independently reviewed by two reviewers with a fellowship-trained musculoskeletal radiologist. The images were classified as type I and II based on the ossicle's medial border overlying the talus's posterior process and the groove for the flexor hallucis longus tendon (FHL). The study revealed that patients with type II os trigonum had a longer transverse diameter of the ossicle than type I, and there were statistically significant differences. Detachment status tended to be less in type I than in type II os trigonum, and the differences between the groups were statistically significant. There were no significant differences between type I and II os trigonum regarding posterior talofibular ligament (PTFL) abnormality, bone marrow edema, FHL tenosynovitis, and posterior synovitis. The study concluded that the os trigonum is a common cause of posterior ankle impingement, and type II os trigonum has a longer transverse diameter of the ossicle than type I.

ChatGPT's Accuracy on Magnetic Resonance Imaging Basics: Characteristics and Limitations Depending on the Question Type.

Our study aimed to assess the accuracy and limitations of ChatGPT in the domain of MRI, focused on evaluating ChatGPT's performance in answering simple knowledge questions and specialized multiple-choice questions related to MRI. A two-step approach was used to evaluate ChatGPT. In the first step, 50 simple MRI-related questions were asked, and ChatGPT's answers were categorized as correct, partially correct, or incorrect by independent researchers. In the second step, 75 multiple-choice questions covering various MRI topics were posed, and the answers were similarly categorized. The study utilized Cohen's kappa coefficient for assessing interobserver agreement. ChatGPT demonstrated high accuracy in answering straightforward MRI questions, with over 85% classified as correct. However, its performance varied significantly across multiple-choice questions, with accuracy rates ranging from 40% to 66.7%, depending on the topic. This indicated a notable gap in its ability to handle more complex, specialized questions requiring deeper understanding and context. In conclusion, this study critically evaluates the accuracy of ChatGPT in addressing questions related to Magnetic Resonance Imaging (MRI), highlighting its potential and limitations in the healthcare sector, particularly in radiology. Our findings demonstrate that ChatGPT, while proficient in responding to straightforward MRI-related questions, exhibits variability in its ability to accurately answer complex multiple-choice questions that require more profound, specialized knowledge of MRI. This discrepancy underscores the nuanced role AI can play in medical education and healthcare decision-making, necessitating a balanced approach to its application.

The Development and Validation of an AI Diagnostic Model for Sacroiliitis: A Deep-Learning Approach.

PURPOSE: Sacroiliitis refers to the inflammatory condition of the sacroiliac joints, frequently causing lower back pain. It is often associated with systemic conditions. However, its signs on radiographic images can be subtle, which may result in it being overlooked or underdiagnosed. This study aims to utilize artificial intelligence (AI) to create a diagnostic tool for more accurate sacroiliitis detection in radiological images, with the goal of optimizing treatment plans and improving patient outcomes. MATERIALS AND METHOD: The study included 492 patients who visited our hospital. Right sacroiliac joint films were independently evaluated by two musculoskeletal radiologists using the Modified New York criteria (Normal, Grades 1-4). A consensus reading resolved disagreements. The images were preprocessed with Z-score standardization and histogram equalization. The DenseNet121 algorithm, a convolutional neural network with 201 layers, was used for learning and classification. All steps were performed on the DEEP:PHI platform. RESULT: The AI model exhibited high accuracy across different grades: 94.53% (Grade 1), 95.83% (Grade 2), 98.44% (Grade 3), 96.88% (Grade 4), and 96.09% (Normal cases). Sensitivity peaked at Grade 3 and Normal cases (100%), while Grade 4 achieved perfect specificity (100%). PPVs ranged from 82.61% (Grade 1) to 100% (Grade 4), and NPVs peaked at 100% for Grade 3 and Normal cases. The F1 scores ranged from 64.41% (Grade 1) to 95.38% (Grade 3). CONCLUSIONS: The AI diagnostic model showcased a robust performance in detecting and grading sacroiliitis, reflecting its potential to enhance diagnostic accuracy in clinical settings. By facilitating earlier and more accurate diagnoses, this model could substantially impact treatment strategies and patient outcomes.

Is ChatGPT a "Fire of Prometheus" for Non-Native English-Speaking Researchers in Academic Writing?

Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.

Changes in CT-Based Morphological Features of the Kidney with Declining Glomerular Filtration Rate in Chronic Kidney Disease.

Chronic kidney disease (CKD) progression involves morphological changes in the kidney, such as decreased length and thickness, with associated histopathological alterations. However, the relationship between morphological changes in the kidneys and glomerular filtration rate (GFR) has not been quantitatively and comprehensively evaluated. We evaluated the three-dimensional size and shape of the kidney using computed tomography (CT)-derived features in relation to kidney function. We included 257 patients aged ≥18 years who underwent non-contrast abdominal CT at the Inha University Hospital. The features were quantified using predefined algorithms in the pyRadiomics package after kidney segmentation. All features, except for flatness, significantly correlated with estimated GFR (eGFR). The surface-area-to-volume ratio (SVR) showed the strongest negative correlation (r = -0.75, p < 0.0001). Kidney size features, such as volume and diameter, showed moderate to high positive correlations; other morphological features showed low to moderate correlations. The calculated area under the receiver operating characteristic (ROC) curve (AUC) for different features ranged from 0.51 (for elongation) to 0.86 (for SVR) for different eGFR thresholds. Diabetes patients had weaker correlations between the studied features and eGFR and showed less bumpy surfaces in three-dimensional visualization. We identified alterations in the CKD kidney based on various three-dimensional shape and size features, with their potential diagnostic value.

Validation of a Deep Learning Chest X-ray Interpretation Model: Integrating Large-Scale AI and Large Language Models for Comparative Analysis with ChatGPT.

This study evaluates the diagnostic accuracy and clinical utility of two artificial intelligence (AI) techniques: Kakao Brain Artificial Neural Network for Chest X-ray Reading (KARA-CXR), an assistive technology developed using large-scale AI and large language models (LLMs), and ChatGPT, a well-known LLM. The study was conducted to validate the performance of the two technologies in chest X-ray reading and explore their potential applications in the medical imaging diagnosis domain. The study methodology consisted of randomly selecting 2000 chest X-ray images from a single institution's patient database, and two radiologists evaluated the readings provided by KARA-CXR and ChatGPT. The study used five qualitative factors to evaluate the readings generated by each model: accuracy, false findings, location inaccuracies, count inaccuracies, and hallucinations. Statistical analysis showed that KARA-CXR achieved significantly higher diagnostic accuracy compared to ChatGPT. In the 'Acceptable' accuracy category, KARA-CXR was rated at 70.50% and 68.00% by two observers, while ChatGPT achieved 40.50% and 47.00%. Interobserver agreement was moderate for both systems, with KARA at 0.74 and GPT4 at 0.73. For 'False Findings', KARA-CXR scored 68.00% and 68.50%, while ChatGPT scored 37.00% for both observers, with high interobserver agreements of 0.96 for KARA and 0.97 for GPT4. In 'Location Inaccuracy' and 'Hallucinations', KARA-CXR outperformed ChatGPT with significant margins. KARA-CXR demonstrated a non-hallucination rate of 75%, which is significantly higher than ChatGPT's 38%. The interobserver agreement was high for KARA (0.91) and moderate to high for GPT4 (0.85) in the hallucination category. In conclusion, this study demonstrates the potential of AI and large-scale language models in medical imaging and diagnostics. It also shows that in the chest X-ray domain, KARA-CXR has relatively higher accuracy than ChatGPT.

Multiacquisition with variable resonance image combination T2 (MAVRIC SL T2) for postoperative cervical spine with artificial disc replacement.

Anterior cervical discectomy with artificial disc replacement (ADR) is an effective treatment of cervical degenerative disc disease. However, postoperative MRI due to recurrent neck/radicular pain is limited due to severe metallic artifacts of artificial disc instrument. Multiacquisition with variable resonance image combination selective T2 (MAVRIC SL T2) has been developed as an MRI technique for metal artifact reduction but has not been evaluated for the postoperative cervical spine with ADR. In our study, we compared MAVRIC SL T2 with the fast spin echo (FSE) T2-weighted sequence (T2WI), which was an essential MR sequence for evaluation of the cervical neural structure, for metallic artifact reduction in the post-operative cervical spine with ADR. Our study revealed MAVRIC SL T2 showed smaller signal void areas, less distortion and signal pile-up, and was more clinically useful than T2WI (p < 0.05). The spinal cord, vertebral bodies, both neural foramina, and anterior paravertebral soft tissue were significantly more visible with MAVRIC SL T2 than with T2WI (p < 0.05). MAVRIC SL T2 might be a useful technique for the evaluation of postoperative cervical spine with ADR and complements T2WI in the evaluation of the spinal cord and nerve roots which were important structures for post-operative recurrent neck/radicular pain.

Compound K ameliorates airway inflammation and mucus secretion through the regulation of PKC signaling in vitro and in vivo.

Background: Cigarette smoke (CS) is considered a principal cause of chronic obstructive pulmonary disease (COPD) and is associated with mucus hypersecretion and airway inflammation. Ginsenoside compound K (CK), a product of ginsenoside metabolism, has various biological activities. Studies on the effects of CK for the treatment of COPD and mucus hypersecretion, including the underlying signaling mechanism, have not yet been conducted. Methods: To study the protective effects and molecular mechanism of CK, phorbol 12-myristate 13-acetate (PMA)-induced human airway epithelial (NCI-H292) cells were used as a cellular model of airway inflammation. An experimental mouse COPD model was also established via CS inhalation and intranasal administration of lipopolysaccharide. Mucin 5AC (MUC5AC), monocyte chemoattractant protein-1, tumor necrosis factor-α (TNF-α), and interleukin-6 secretion, as well as elastase activity and reactive oxygen species production, were determined through enzyme-linked immunosorbent assay. Inflammatory cell influx and mucus secretion in mouse lung tissues were estimated using hematoxylin and eosin and periodic acid-schiff staining, respectively. PKCδ and its downstream signaling molecules were analyzed via western blotting. Results: CK prevented the secretion of MUC5AC and TNF-α in PMA-stimulated NCI-H292 cells and exhibited a protective effect in COPD mice via the suppression of inflammatory mediators and mucus secretion. These effects were accompanied by an inactivation of PKCδ and related signaling in vitro and in vivo. Conclusion: CK suppressed pulmonary inflammation and mucus secretion in COPD mouse model through PKC regulation, highlighting the compound's potential as a useful adjuvant in the prevention and treatment of COPD.

Occurrence of human leukocyte antigen B51-related ankylosing spondylitis in a family: Two case reports.

BACKGROUND: Ankylosing spondylitis (AS) is strongly associated with the human leukocyte antigen (HLA) B27 haplotype. In regions where conventional polymerase chain reaction for HLA typing is available for antigens such as HLA B27 or HLA B51, it is common to perform the HLA B27 test for evaluation of AS. While HLA B27-associated clustered occurrences of AS have been reported in families, we report the first case series of HLA B51-related occurrences of AS in a family. CASE SUMMARY: A father and his daughters were diagnosed with AS and did not have the HLA B27 haplotype. Although they were positive for HLA B51, they exhibited no signs of Behçet's disease (BD). Of the five daughters, one had AS, and three, including the daughter with AS, were positive for HLA B51. The two daughters with the HLA B51 haplotype (excluding the daughter with AS) exhibited bilateral grade 1 sacroiliitis, whereas the daughters without the HLA B51 haplotype did not have sacroiliitis. Thus, this Korean family exhibited a strong association with the HLA B51 haplotype and clinical sacroiliitis, irrespective of the symptoms of BD. CONCLUSION: It is advisable to check for HLA B51 positivity in patients with AS/spondyloarthropathy who test negative for HLA B27.

Prediction of the Acuity of Vertebral Compression Fractures on CT Using Radiologic and Radiomic Features.

RATIONALE AND OBJECTIVES: To develop and validate prediction models to differentiate acute and chronic vertebral compression fractures based on radiologic and radiomic features on CT. MATERIALS AND METHODS: This study included acute and chronic compression fractures in patients who underwent both spine CT and MRI examinations. For each fractured vertebra, three CT findings ([1] cortical disruption, [2] hypoattenuating cleft or sclerotic line, and [3] relative bone marrow attenuation) were assessed by two radiologists. A radiomic score was built from 280 radiomic features extracted from non-contrast-enhanced CT images. Weighted multivariable logistic regression analysis was performed to build a radiologic model based on CT findings and an integrated model combining the radiomic score and CT findings. Model performance was evaluated and compared. Models were externally validated using an independent test cohort. RESULTS: A total to 238 fractures (159 acute and 79 chronic) in 122 patients and 58 fractures (39 acute and 19 chronic) in 32 patients were included in the training and test cohorts, respectively. The AUC of the radiomic score was 0.95 in the training and 0.93 in the test cohorts. The AUC of the radiologic model was 0.89 in the training and 0.83 in the test cohorts. The discriminatory performance of the integrated model was significantly higher than the radiologic model in both the training (AUC, 0.97; p<0.01) and the test (AUC, 0.95; p=0.01) cohorts. CONCLUSION: Combining radiomics with radiologic findings significantly improved the performance of CT in determining the acuity of vertebral compression fractures.

Metallic Artifact Reduction of Multiacquisition With Variable Resonance Image Combination Selective-Short Tau Inversion Recovery for Postoperative Cervical Spine With Artificial Disk Replacement: A Preliminary Study.

OBJECTIVE: This study aimed to evaluate multiacquisition with variable resonance image combination selective short tau inversion recovery (MAVRIC SL STIR) for metallic artifact reduction in magnetic resonance imaging (MRI) of postoperative cervical spine with artificial disk replacement. METHODS: A porcine cervical spine with artificial disk replacement was subject to 3 T MRI with variable fat-suppressed fluid-sensitive sequences. Five volunteers underwent MRI with MAVRIC SL STIR and STIR. Quantitative and qualitative analyses were performed for metallic artifact reduction. RESULTS: MAVRIC SL STIR showed the least signal void areas in the tissue phantom and volunteer study. In the tissue phantom study, MAVRIC SL STIR showed the best visualization of anatomic structure, least distortion, and signal pile-up. However, it ranked last for the homogeneity of fat suppression among sequences. In the volunteer study, MAVRIC SL STIR showed better visualization of anatomic structure and lesser distortion, but showed worse image quality of the spinal cord than STIR in the sagittal plane (P < 0.05). CONCLUSIONS: MAVRIC SL STIR might be useful for visualization of anatomy by reduction of signal void areas and distortion in the operated site but should be used as a complement to STIR for evaluation of the spinal cord signal change.

Daphnodorin C isolated from the stems of Daphne kiusiana Miquel attenuates airway inflammation in a mouse model of chronic obstructive pulmonary disease.

BACKGROUND: Since long-term or high-dose use of COPD medication causes adverse effects in patients with COPD, more effective and safer ways to manage COPD symptoms are required. Daphne kiusiana Miquel is a medicinal plant, but its anti-COPD efficacy was little studied. PURPOSE: We investigated the anti-COPD activity and molecular mechanism of action of active compounds isolated from D. kiusiana to find drug candidates for COPD. METHODS: We isolated seven compounds (1-7) in an ethyl acetate (EtOAc) fraction from D. kiusiana, and determined that seven compounds effectively control the inflammatory responsiveness in both PMA-stimulated lung epithelial cells (in vitro) and/or in COPD model mice using cigarette smoke- and lipopolysaccharides-exposed animals in vivo. RESULTS: We show that the ethyl acetate (EtOAc) fraction from D. kiusiana. suppresses inflammatory response in both PMA-stimulated human lung epithelial cells (in vitro) and COPD model mice (in vivo). The EtOAc fraction effectively suppresses various inflammatory responses, such as mucus secretion, ROS production, bronchial recruitment of inflammatory cells, and release of proinflammatory cytokines. Additionally, we isolated three compounds with anti-inflammatory efficacy from the EtOAc fraction, out of which daphnodorin C was the most effective. Finally, we demonstrated that daphnodorin C negatively regulates inflammatory gene expression by suppressing NF-κB and specific MAPK signaling pathways (JNK and p38) in vitro and in vivo. CONCLUSIONS: These results suggest that daphnodorin C could be a promising therapeutic alternative for managing COPD symptoms.

Sensitivity of quantitative symmetry measurement algorithms for convergent beam electron diffraction technique.

We investigate the sensitivity of symmetry quantification algorithms based on the profile R-factor (Rp) and the normalized cross-correlation (NCC) coefficient (γ). A DM (Digital Micrograph©) script embedded in the Gatan digital microscopy software is used to develop the symmetry quantification program. Using the Bloch method, a variety of CBED patterns are simulated and used to investigate the sensitivity of symmetry quantification algorithms. The quantification results show that two symmetry quantification coefficients are significantly sensitive to structural changes even for small strain values of < 1%.

Sarcomatoid carcinoma associated with chronic empyema and early lung and pleural metastases: A case report.

INTRODUCTION: The relationship between chronic empyema and malignant tumors, most of which are lymphoma, has been recognized for many decades. Sarcomatoid carcinoma associated with chronic empyema is extremely rare, may metastasize to other organs in the early stage, and rapidly progresses to death. As far as we know, this was the first case report on sarcomatoid carcinoma associated chronic empyema. THE PATIENTS MAIN CONCERNS AND IMPORTANT CLINICAL FINDINGS: A 59-year-old man presented to our hospital with a 9-year history of chronic empyema and a chief complaint of left chest wall pain for 5 months. The diagnostic contrast-enhanced computed tomography (CT) showed a large irregular soft tissue mass located on the left lower hemithorax at the margin of the empyema cavity extending to the adjacent chest wall and lung parenchyma. In addition, CT revealed pleural and pulmonary metastases surrounded by ground glass opacity. THE MAIN DIAGNOSIS, THERAPEUTICS INTERVENTIONS, AND OUTCOMES: The patient underwent CT guided percutaneous core needle biopsy (PCNB). The histopathological evaluation showed carcinomatous proliferation of pleomorphic spindle cells with extensive necrosis. Immunohistochemically, tumor cells were positive for cytokeratin and vimentin. The final histopathological diagnosis was sarcomatoid carcinoma underlying chronic empyema. The tumors showed rapid progression on serial simple radiography. Palliative treatments were performed, but the patient still developed severe dyspnea and died shortly after on day 16. CONCLUSION: Sarcomatoid carcinoma can occur very rarely as a complication of chronic empyema, and is more aggressive than usual. Early detection of developing malignancy during the follow-up of chronic empyema is an important factor for patient prognosis.

Transforming Growth Factor ß Inhibits MUC5AC Expression by Smad3/HDAC2 Complex Formation and NF-κB Deacetylation at K310 in NCI-H292 Cells.

Airway mucus secretion is an essential innate immune response for host protection. However, overproduction and hypersecretion of mucus, mainly composed of the gel- forming MUC5AC protein, are significant risk factors for patients with asthma and chronic obstructive pulmonary disease (COPD). The transforming growth factor ß (TGFß) signaling pathway negatively regulates MUC5AC expression; however, the underlying molecular mechanism is not fully understood. Here, we showed that TGFß significantly reduces the expression of MUC5AC mRNA and its protein in NCI-H292 cells, a human mucoepidermoid carcinoma cell line. This reduced MUC5AC expression was restored by a TGFß receptor inhibitor (SB431542), but not by the inhibition of NF-κB (BAY11-7082 or Triptolide) or PI3K (LY294002) activities. TGFß-activated Smad3 dose-dependently bound to MUC5AC promoter. Notably, TGFß-activated Smad3 recruited HDAC2 and facilitated nuclear translocation of HDAC2, thereby inducing the deacetylation of NF-κB at K310, which is essential for a reduction in NF-κB transcriptional activity. Both TGFß-induced nuclear translocation of Smad3/HDAC2 and deacetylation of NF-κB at K310 were suppressed by a Smad3 inhibitor (SIS3). These results suggest that the TGFß-activated Smad3/HDAC2 complex is an essential negative regulator for MUC5AC expression and an epigenetic regulator for NF-κB acetylation. Therefore, these results collectively suggest that modulation of the TGFß1/Smad3/HDAC2/NF-κB pathway axis can be a promising way to improve lung function as a treatment strategy for asthma and COPD.

Longifolioside A inhibits TLR4-mediated inflammatory responses by blocking PKCδ activation in LPS-stimulated THP-1 macrophages.

Longifolioside A is an iridoid glucoside compound isolated from Pseudolysimachion rotundum var. subintegrum, which has been used in traditional herbal medicines to treat respiratory inflammatory diseases. Logifolioside A is a potent antioxidant; however, its underlying pharmacological mechanisms of action in inflammatory diseases are unknown. Here, we investigated the inhibitory effects of longifolioside A in lipopolysaccharide (LPS)-stimulated toll-like receptor 4 (TLR4) signal transduction systems using human THP-1 macrophages and HEK293 cells stably expressing human TLR4 protein (293/HA-hTLR4). Longifolioside A significantly reduced the release of inflammatory cytokines such as interleukin (IL)-6, -8, and tumor necrosis factor (TNF)-α in LPS-stimulated THP-1 macrophages. Furthermore, longifolioside A inhibited the expression of inflammatory mediator genes such as inducible nitric oxide synthase (iNOS) and cyclooxygenase (COX)-2 that produce nitric oxide (NO) and prostaglandin E2 (PGE2), respectively. Longifolioside A suppressed the phosphorylation of PKCδ, IRAK4, IKKα/ß, IκBα, and mitogen-activated protein (MAP) kinases (ERK 1/2 and JNK, but not p38), thereby inactivating the nuclear localization of NF-κB and AP-1, and thus decreasing the expression of inflammatory response genes. Notably, longifolioside A disrupted the interaction between human TLR4 and the TIR domain-containing adaptor protein (TIRAP), an early step during TLR4 activation, thereby reducing IL-8 secretion in 293/HA-hTLR4 cells. This inhibitory effect was comparable to that of TAK-242 (a TLR4 inhibitor, or resatorvid). Our results indicate that longifolioside A prevents inflammatory response by suppressing TLR4 activation required for NF-κB and AP-1 activation.

Diagnostic accuracy of 3T conventional shoulder MRI in the detection of the long head of the biceps tendon tears associated with rotator cuff tendon tears.

OBJECTIVE: To evaluate the diagnostic performance (DP) of 3T (3 Tesla field strength) conventional shoulder magnetic resonance imaging (MRI) in detecting the long head of the biceps tendon (LHBT) tears in association with rotator cuff tendon tears. MATERIALS AND METHODS: This study included 80 consecutive patients who underwent arthroscopic surgery for rotator cuff tendon tears. Two radiologists independently evaluated the preoperative 3T shoulder MRI for the presence of LHBT tears. The DP of MRI was evaluated using the results of arthroscopy as the reference standard. We also evaluated the DP of several MR signs of LHBT in detection of partial LHBT tears. RESULTS: Arthroscopic examination revealed 35 partial and 5 complete tears. According to the results of evaluation by reviewers 1 and 2, shoulder MRI exhibited sensitivities of 77.14 and 80 % and specificities of 71.11 and 73.33 % in detection of partial LHBT tears and sensitivities of 80 and 100 % and a specificity of 100% (both) in detection of complete LHBT tears. In detecting partial LHBT tears, increased T2 signal intensity of the LHBT exhibited high sensitivities (reviewers 1 and 2; 82.85 and 80 %, respectively) and the presence of intratendinous defects or C-signs exhibited the highest specificities (reviewers 1 and 2; 95.55 and 93.33 %, respectively), followed by abnormalities in shape and outer margins of the LHBT (reviewers 1 and 2; 91.11 and 82 %; 91.11 and 86.66 %, respectively). CONCLUSION: Non-contrast-enhanced 3T shoulder MRI is potentially highly accurate in detection of complete LHBT tears, but moderately accurate in detection of partial LHBT tears.