Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

Background: Quantitative computed tomography (QCT) is essential for assessing osteoporosis and monitoring spinal deformities. “Clari-QCT,” a software that uses artificial intelligence to analyze conventional computed tomography (CT) scans and produce QCTequivalent reports. This study aims to evaluate the effectiveness of Clari-QCT by comparing its results with traditional QCT, with the goal of validating new diagnostic tools for spinal deformities. Methods: The study analyzed dual energy X-ray absorptiometry, CT, and QCT data from 18 patients at Inha University Hospital. Clari-QCT software was evaluated for its ability to generate QCT-equivalent reports from CT images. The software processes abdomen CT images, calculates bone density in designated slices, and provides bone mineral density (BMD), T-score, and Z-score values. Patients were classified into normal, mild, and severe spinal deformity groups. Intraclass correlation coefficient (ICC) analysis was used to measure the agreement between actual and predicted BMD values. Results: The study included participants with an average age of 64 and a mean body mass index of 24.88. The average BMD was 94.7 g/cm³ by QCT and 122.5 g/cm³ by Clari- QCT, with individual differences ranging from 4.9 to 61.8. T-score discrepancies ranged from 0.16 to 6.86. ICC analysis showed moderate to high agreement between methods, with ICC1 values of 0.597, ICC2 of 0.64, ICC3 of 0.81, and ICC1k, ICC2k, ICC3k values ranging from 0.748 to 0.895. Conclusions Clari-QCT demonstrates good agreement with actual QCT measurements in normal and severe spinal deformity groups but shows reduced accuracy in patients with mild deformities. If the limitations are addressed, it could become a useful tool for monitoring bone health in patients with spinal deformities.

Guillain-Barre syndrome is an acute inflammatory demyelinating polyradiculopathy characterized by progressive motor weakness, areflexia, and ascending paralysis. Guillain-Barre syndrome is extremely rare in pregnant patients, and there are no established guidelines for delivery or safest anesthetic methods. We report a Cesarean delivery in the case of a 32-year old woman who was diagnosed with Guillain-Barre syndrome 18 weeks into gestation. Tracheostomy was performed due to progressive respiratory muscle weakness and respiratory failure, and ventilator support was required in the intensive care unit. The respiratory difficulty was exacerbated by the growth of the fetus, necessitating emergency Cesarean delivery. The delivery was successfully performed under general anesthesia, and the patient recovered without neurological sequelae.
Anesthesia, General ; Cesarean Section ; Emergencies ; Female ; Fetus ; Guillain-Barre Syndrome ; Humans ; Intensive Care Units ; Paralysis ; Polyradiculopathy ; Pregnancy ; Respiratory Insufficiency ; Respiratory Muscles ; Tracheostomy ; Ventilators, Mechanical

Diffuse large B-cell lymphoma associated with chronic inflammation (DLBCL-CI), specifically arising in ileal neobladder, is a rare neoplasm. We present an unusual case of Epstein–Barr virus (EBV)–positive DLBCL-CI arising within neobladder with detailed clinical, histological, and immunophenotypical features in an immunocompetent patient. An 88-year-old male was admitted for gross hematuria. He had undergone radical cystectomy and ileal neobladder 17 years ago for invasive bladder cancer. Computed tomography showed enhancing lesions on dome and posterior wall of neobladder with mucosal thickening and multiple enlarged retroperitoneal lymphadenopathies. Transurethralresection of neobladder lesion revealed the diffuse infiltration of large lymphoid cells which were positive for CD20, CD30, and multiple myeloma oncogen-1 with EBV-encoded small RNAs co-localizing, and diagnosis of EBV-positive DLBCL-CI was made. After multi-agent chemotherapy, the lesion disappeared. We suggest that clinicians should consider the possibility of DLBCL-CI in patients presented with hematuria during follow-up after bladder reconstruction.
Aged, 80 and over ; B-Lymphocytes ; Cystectomy ; Diagnosis ; Drug Therapy ; Follow-Up Studies ; Hematuria ; Humans ; Inflammation ; Lymphocytes ; Lymphoma, B-Cell ; Male ; Multiple Myeloma ; RNA ; Urinary Bladder ; Urinary Bladder Neoplasms

The use of extracorporeal membrane oxygenation (ECMO) in patients with severe hypoxemia refractory to conventional ventilation has recently gained attention due to recent reports that highlighted its potential benefit. This report presents a case of acute onset acute respiratory distress syndrome (ARDS) with severe hypoxemia in the operating room that showed significant improvement after applying ECMO in the intensive care unit. Although the oxygen saturation decreased to as low as 50% before the application of ECMO, at no time did the patient show hypotension or decreased cardiac output. The patient improved within 48 hours of ECMO and recovered with no major complications or neurologic sequelae. Our case shows that ECMO is a valuable and viable option in ARDS with severe refractory hypoxemia.
Anoxia ; Cardiac Output ; Extracorporeal Membrane Oxygenation* ; Humans ; Hypotension ; Intensive Care Units ; Operating Rooms ; Oxygen ; Respiratory Distress Syndrome, Adult* ; Ventilation

Oronasal fistulae (ONF) could remain after surgery in some patients with cleft palate. ONF ultimately requires intraoral surgery, which may lead to perioperative airway obstruction. Tongue flap surgery is a technique used to repair ONF. During the second surgery for performing tongue flap division, the flap transplanted from the tongue dorsum to the palate of the patient acts as an obstacle to airway management, which poses a great challenge for anesthesiologists. In particular, anesthesiologists may face difficulty in airway evaluation and patient cooperation during general anesthesia for tongue flap division surgery in pediatric patients. The authors report a case of airway management using a flexible fiberoptic bronchoscope during general anesthesia for tongue flap division surgery in a 6-year-old child.
Airway Management ; Airway Obstruction ; Anesthesia, General ; Bronchoscopes ; Child ; Cleft Palate ; Fistula ; Humans ; Palate ; Patient Compliance ; Tongue

Background/Aims: This study aims to investigate the effect of a fermented rice drink with Lactiplantibacillus plantarum JSA22 on symptoms, blood tests, microbiomes, and fecal metabolites in patients with irritable bowel syndrome (IBS) who were overweight. Methods: Sixty overweight (body mass index ≥ 23 kg/m2 ) patients aged between 20 and 65 with IBS were enrolled. Patients were divided into 2 groups and administered either a fermented rice drink or an nonfermented rice drink for a month. The symptom questionnaire, blood samples, and stool samples for microbiome and metabolite were collected before and after the month of rice drink administration.The primary efficacy variable was the subject’s global assessment of IBS symptoms. Results: In both groups, global IBS symptoms, including abdominal pain, bowel habit, urgency, and abdominal distension, improved significantly (P < 0.01). The abdominal bloating was more significantly improved in the fermented rice drink group than in the nonfermented rice drink group (P < 0.05). Significant changes were not observed in metabolic syndrome-related blood tests or fecal metabolites in either group. However, microbiome analysis showed significant differences in genus levels before and after consuming fermented rice drink, such as in Blautia in stool (P = 0.020) and Prevotella (P = 0.017) and Oribacterium (P = 0.018) in saliva. Conclusions The fermented rice drink with L. plantarum JSA22 showed a beneficial effect in reducing abdominal distension in IBS patients. Bacteria that reduce visceral fat accumulation increased in the stool and saliva of patients who consumed fermented rice drinks.

OBJECTIVE: To compare the detection performance of the automated whole breast ultrasound (AWUS) with that of the hand-held breast ultrasound (HHUS) and to evaluate the interobserver variability in the interpretation of the AWUS. MATERIALS AND METHODS: AWUS was performed in 38 breast cancer patients. A total of 66 lesions were included: 38 breast cancers, 12 additional malignancies and 16 benign lesions. Three breast radiologists independently reviewed the AWUS data and analyzed the breast lesions according to the BI-RADS classification. RESULTS: The detection rate of malignancies was 98.0% for HHUS and 90.0%, 88.0% and 96.0% for the three readers of the AWUS. The sensitivity and the specificity were 98.0% and 62.5% in HHUS, 90.0% and 87.5% for reader 1, 88.0% and 81.3% for reader 2, and 96.0% and 93.8% for reader 3, in AWUS. There was no significant difference in the radiologists' detection performance, sensitivity and specificity (p > 0.05) between the two modalities. The interobserver agreement was fair to good for the ultrasonographic features, categorization, size, and the location of breast masses. CONCLUSION: AWUS is thought to be useful for detecting breast lesions. In comparison with HHUS, AWUS shows no significant difference in the detection rate, sensitivity and the specificity, with high degrees of interobserver agreement.
Aged ; Breast Neoplasms/pathology/*ultrasonography ; Chi-Square Distribution ; *Clinical Competence ; Diagnosis, Differential ; Female ; Humans ; Image Interpretation, Computer-Assisted/methods ; Magnetic Resonance Imaging ; Middle Aged ; Neoplasm Staging ; Observer Variation ; Sensitivity and Specificity ; Ultrasonography, Mammary/*methods

Purpose: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of sentinel lymph nodes by a pathologist is not easy and is a tedious and time-consuming task. The purpose of this study is to review a challenge competition (HeLP 2018) to develop automated solutions for the classification of metastases in hematoxylin and eosin–stained frozen tissue sections of SLNs in breast cancer patients. Materials and Methods: A total of 297 digital slides were obtained from frozen SLN sections, which include post–neoadjuvant cases (n = 144, 48.5%) in Asan Medical Center, South Korea. The slides were divided into training, development, and validation sets. All of the imaging datasets have been manually segmented by expert pathologists. A total of 10 participants were allowed to use the Kakao challenge platform for six weeks with two P40 GPUs. The algorithms were assessed in terms of the AUC (area under receiver operating characteristic curve). Results: The top three teams showed 0.986, 0.985, and 0.945 AUCs for the development set and 0.805, 0.776, and 0.765 AUCs for the validation set. Micrometastatic tumors, neoadjuvant systemic therapy, invasive lobular carcinoma, and histologic grade 3 were associated with lower diagnostic accuracy. Conclusion In a challenge competition, accurate deep learning algorithms have been developed, which can be helpful in making frozen diagnosis of intraoperative sentinel lymph node biopsy. Whether this approach has clinical utility will require evaluation in a clinical setting