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Background: Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide. Oxford classification including mesangial hypercellularity (M), endothelial hypercellularity (E), segmental sclerosis (S), interstitial fibrosis/tubular atrophy (T), and crescent (C) were recommended to predict the prognosis of IgAN. Purpose: To explore whether multiparametric magnetic resonance imaging (MRI) can be applied to assess the renal function, Oxford classification, and risk of progression to end‐stage kidney disease within 5 years of IgAN. Study Type: Prospective. Population: A total of 46 patients with pathologically confirmed IgAN and 20 healthy volunteers. Field Strength/Sequence: A 3‐T, blood oxygenation level‐dependent (BOLD)‐MRI, intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI). Assessment: Two radiologists measured the cortex and medulla T2*, apparent diffusion coefficient (ADC), true diffusion (Dt), pseudo‐diffusion (Dp), perfusion fraction (fp). All participants were divided into three groups: group 1, healthy volunteers; group 2, patients with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2; group 3, patients with eGFR <60 mL/min/1.73 m2. Or two groups: group A, 5‐year risk scores ≤10% and group B, 5‐year risk scores >10%. Statistical Tests: Intraclass correlation coefficient, one‐way analysis of variance, least‐significant difference, Student's t‐test, Pearson product–moment correlation, Spearman's rank correlation, and receiver operating characteristics (ROC) with the area under the curve (AUC). A P value <0.05 was considered statistically significant. Results: Except for cortical Dp, all other MRI parameters showed significant differences between group 1 and group 2. None of the MRI parameters showed a significant correlation with M, E, or C scores. Cortical T2*, Dt, fp, and medullary Dt and fp showed low‐to‐moderate significant correlations with S scores. Except for cortical and medullary Dp, all other MRI parameters were significantly correlated with T scores. Cortical Dt showed the largest AUC for differentiating group A from group B (AUC = 0.927) and T0 from T1/T2 (AUC = 0.963). Data Conclusion: Imaging by IVIM‐DWI and BOLD‐MRI could facilitate noninvasive assessment of the renal function, Oxford classification, and prognostic risk of IgAN patients. Evidence Level: 2. Technical Efficacy: Stage 3. [ABSTRACT FROM AUTHOR]

A satisfactory treatment of an 18-year-old lady was reported with right combination-type condylar hyperplasia (CH) in active phase. The chin severely deviated to the left, with the right gonial angle locating at a lower level. Intraorally, the lower centre line shifted to the left, the scale of which reached the width of one lower incisor. The right molar relation was mesial. Right maxillary second molar over-erupted without contact to lower teeth. There had been 2.5-mm anterior open bite (AOB) before surgery (T1) due to the tongue-spitting habit. After judging the benefits and disadvantages of all treatment alternatives, the decision was made to perform a right condylectomy and post-surgery orthodontics. Before orthodontics (T2) when the chin was positioned centred, an asymmetrical open bite occurred, caused by pre-contact between the right maxillary and mandibular second molars. Meanwhile, the AOB at T2 became 11.5mm. Orthodontic-related treatment included four premolars extraction and intrusion of bilateral maxillary molars using four miniscrews. Finally, this treatment achieved a clinically centred chin with two gonial angles at the same level. Post-condylectomy, the large AOB was resolved, together with a bilateral neutral molar relationship and alignment of the incisor midlines. Besides, the resected right condyle was covered by a continuous cortex bone and returned to the glenoid fossa. In sum, a high-challenging combined-type CH case was accomplished with impressive improvement in facial and occlusal symmetry, thanks to condylectomy and post-surgery miniscrew-assisted orthodontics., (Copyright © 2024 CEO. Published by Elsevier Masson SAS. All rights reserved.)

Urgent detection of calculous pyonephrosis is crucial for surgical planning and preventing severe outcomes. This study aims to evaluate the performance of computed tomography (CT)-based radiomics and a three-dimensional convolutional neural network (3D-CNN) model, integrated with independent clinical factors, to identify patients with calculous pyonephrosis. We recruited 182 patients receiving either percutaneous nephrostomy tube placement or percutaneous nephrolithotomy for calculous hydronephrosis or pyonephrosis. The regions of interest were manually delineated on plain CT images and the CT attenuation value (HU) was measured. Radiomics analysis was performed using least absolute shrinkage and selection operator (LASSO). A 3D-CNN model was also developed. The better-performing machine-learning model was combined with independent clinical factors to build a comprehensive clinical machine-learning model. The performance of these models was assessed using receiver operating characteristic analysis and decision curve analysis. Fever, blood neutrophils, and urine leukocytes were independent risk factors for pyonephrosis. The radiomics model showed higher area under the curve (AUC) than the 3D-CNN model and HU (0.876 vs. 0.599, 0.578; p = 0.003, 0.002) in the testing cohort. The clinical machine-learning model surpassed the clinical model in both the training (0.975 vs. 0.904, p = 0.019) and testing (0.967 vs. 0.889, p = 0.045) cohorts.