Current Medical Imaging Reviews最新文献

Background: Disseminated tuberculosis (dTB) can occur in immunocompetent adults, frequently mimicking metastatic malignancy, thereby delaying the diagnosis.

Case presentation: A young woman without known immunosuppression developed multisystem disease involving the peritoneum/ovaries, hepatobiliary structures, lymph nodes, adrenals, and thoracolumbar spine. CT/MRI and PET/CT suggested widespread neoplastic disease. Because FDG avidity is nonspecific, we prioritized histologic confirmation. Surgical exploration and targeted biopsies showed necrotizing granulomatous inflammation compatible with tuberculosis; microbiologic testing supported the diagnosis. The patient commenced directly observed first-line therapy (isoniazid, rifampin, pyrazinamide, ethambutol) as the intensive phase, followed by an isoniazid-rifampin continuation phase. Under treatment, symptoms improved, and interval imaging showed regression of inflammatory lesions.

Conclusion: In cancer-like, multisystem presentations, even in apparently immunocompetent hosts, tissue diagnosis is decisive, and imaging should primarily guide sampling. Early recognition and standardized therapy can prevent irreversible morbidity.

Introduction: This study aimed to predict the occurrence of cardiac remodeling and/or myocardial fibrosis using machine learning based on T1 mapping from cardiovascular magnetic resonance in athletes.

Methods: A total of 104 athletes and 20 healthy sedentary controls underwent a 3.0T cardiovascular magnetic resonance scan. Cardiac function parameters, T1 and extracellular volume, were measured for 16 segments of the left ventricle. These parameters were separately compared between athletes and controls, and between the positive and negative athlete groups. Gradient boosting machines, logistic regression, classification and regression trees, and support vector machines were constructed for the prediction of cardiac remodeling and/or myocardial fibrosis.

Result: Higher extracellular volume values of segments 1,4,6,8, and 9 and lower native T1 values of segments 8 and 14 were found in athletes than controls (p<0.05). Native T1 values of segments 3,6,8,9,10,14, and 15 and extracellular volume values of segments 3,6, and 8 were higher in the positive athletes group than those in the negative athletes group (p<0.05). The most effective model was the Gradient Boosting Machine, with an AUC of 0.899, an accuracy of 82.7%, a sensitivity of 90.0%, and a specificity of 81.0%. The top three important factors were: the native T1 value of segment 10, the extracellular volume value of segment 3, and body surface area.

Conclusion: Native T1 and extracellular volume values increased in athletes with cardiac remodeling, which may reveal the relationship between cardiac remodeling and myocardial fibrosis. Early cardiac magnetic resonance imaging is performed to monitor athletes' native myocardial T1 and ECV values, assess their risk levels, and guide subsequent surge planning to reduce the risk of adverse cardiovascular events. A GBM model with better performance can predict adverse cardiovascular events based on T1 mapping parameters, and the prediction can be verified by tracking the subsequent athlete's status.

Background: Lipomas represent a rare benign etiology of intussusception in adults, affecting both the small intestine and the colon. Diagnosing intussusception in adults can be challenging, and there are no reports on the use of positron emission tomography/CT (PET/CT) in the diagnosis of lipoma-induced intussusception. This study aimed to preliminarily explore the potential diagnostic utility of 18F-FDG PET/CT in the diagnosis of intussusception caused by lipomas.

Methods: We conducted a retrospective review of the clinical characteristics and imaging findings of three patients diagnosed with lipoma-induced intussusception using 18F-FDG PET/CT from 2019 to 2023 at our hospital.

Results: The three cases presented with diverse clinical presentations and were diagnosed based on PET/CT imaging. Surgical confirmation was obtained in two cases. Lipomas were identified in both the small intestine and the colon, with one case displaying increased metabolic activity on FDG uptake, suggesting a possible link between FDG uptake and clinical severity.

Conclusion: Lipoma is a benign cause of intussusception that can occur in both the small intestine and the colon. The symptoms of adult intussusception are often atypical and variable. Imaging modalities, particularly PET/CT, are instrumental in diagnosing intussusception due to lipomas, differentiating between benign and malignant causes, and assessing the severity to inform treatment strategies.

Background: Given multiple risk factors for lung cancer, this study explored associations between lung cancer and AI-derived quantitative chest computed tomography (CT) parameters of emphysema, airways, and pulmonary vasculature.

Methods: This retrospective single-center study (December 2020-February 2023) analyzed relevant parameters of the left upper lobe (LUL) and right upper lobe (RUL) in 170 lung cancer patients and 126 healthy individuals. Subgroups were defined by cancer-free lobes (129 patients/126 controls for LUL; 120 patients/126 controls for RUL). Univariate and multivariate binary logistic regression analyses were used for analysis.

Results: The emphysema-related 15th percentile of CT attenuation values (PI-15) was significantly associated with lung cancer, with lower values in patients’ LUL. Pulmonary vascular parameters (diameter, count, area at 6 mm/24 mm from the lung surface) differed significantly; the patients had smaller diameters, higher counts, and larger areas at 6 mm in the LUL. Airway parameters (Awt-Pi10, level 6 wall thickness) were higher in patients’ LUL. Multivariate regression identified PI-15 and vascular diameters (6 mm/24 mm) in LUL [area under the curve (AUC) = 0.841, 95% confidence interval (95% CI): 0.789–0.892] and vascular diameters (6 mm/24 mm) and vascular count at 24 mm from the lung surface in RUL (AUC=0.819, 95% CI:0.766–0.872) as significant predictors (all P<0.001).

Conclusion: AI-derived quantitative CT parameters of emphysema, vasculature, and airways are associated with lung cancer and may serve as complementary tools for clinical risk assessment.

Introduction: Pseudomyogenic Hemangioendothelioma (PMHE), also known as epithelioid sarcoma-like hemangioendothelioma, is a rare, indolent, low-grade vascular tumor. It typically presents as firm cutaneous nodules, with a predilection for the lower extremities and a male predominance. While numerous cases have been reported in pathology literature, detailed radiologic descriptions, particularly of soft tissue origins, are scarce. This report aims to bridge this gap by presenting a rare case of PMHE with comprehensive imaging findings.

Case presentation: We report on a 67-year-old male who presented with painful, palpable papules on his right buttock. MRI revealed multifocal dermal nodules demonstrating low signal intensity on T1-weighted images and high signal intensity with a distinctive peripheral high-signal halo on T2-weighted images. Notably, T1 gadolinium fat-saturated sequences exhibited marked enhancement with a characteristic peripheral rim enhancement pattern. The lesions were confined to the cutaneous layer. Initial radiological differentials included post-inflammatory granuloma and sarcoma. Histopathological examination confirmed PMHE. PET/CT demonstrated no evidence of systemic metastasis, and the patient has remained recurrence-free for two years following surgery.

Conclusion: This report highlights a rare case of cutaneous PMHE and details its distinctive MRI features, particularly the peripheral rim enhancement. Given its rarity and often non-specific clinical and imaging presentations, there is a significant potential for misdiagnosis. Therefore, it is crucial for radiologists to be aware of PMHE and familiarize themselves with its characteristic radiological patterns to facilitate accurate, timely diagnosis and ensure appropriate patient management.

Introduction: Transanal small bowel evisceration is an extremely rare and life-threatening surgical emergency that primarily occurs in debilitated elderly patients. Preoperative computed tomography (CT) can be useful for identifying the viability of eviscerated small bowel and other intra-abdominal pathologies.

Case presentation: In this study, we report the case of an 81-year-old woman who presented with sudden anal protrusion of small bowel loops. Computed tomography (CT) demonstrated a rectal wall defect, pneumoperitoneum, and herniation of the small bowel with features suggestive of strangulation. Emergency laparotomy revealed a firmly impacted ileal segment plugging a perforation at the rectosigmoid junction, likely due to increased intra-abdominal pressure, necessitating small bowel resection and the Hartmann procedure. Early diagnosis and prompt surgical intervention led to a favorable postoperative course.

Conclusion: This case highlights the critical role of CT in identifying rectal perforation and intrarectal small bowel evisceration.

Background: Acute pancreatitis (AP) is associated with a high mortality rate that is directly related to its severity. Limited research has been conducted on the role of DWI-MRI in the diagnosis and staging of acute pancreatitis as it pertains to the revised Atlanta classification. The objective of this study was to examine the role of diffusion-weighted (DW) magnetic resonance imaging (MRI) in early diagnosis and staging of acute pancreatitis in correlation to the revised Atlanta classification.

Methods: According to the revised Atlanta classification, a prospective assessment was performed to examine the correlation between DW MRI and apparent diffusion coefficient (ADC) values with the severity of acute pancreatitis (AP) in a sample of 34 patients diagnosed with AP.

Results: The mean ADC value of mild edematous pancreatitis was 1.14±0.06x10-3 mm2/sec, moderate edematous pancreatitis was 1.18±0.16x10-3 mm2/sec, severe necrotizing pancreatitis was 1.99±0.06x10-3 mm2/sec, and that of the normal pancreas was 1.54±0.05 x10-3 mm2/sec. Based on the revised Atlanta classification, there was a significant difference between the ADC values of normal pancreas and acute, severe, and mild/moderate pancreatitis, while there was no significant difference between mild and moderate pancreatitis cases. ROC analysis yielded high accuracy in differentiating normal pancreas from acute pancreatitis and severe pancreatitis from non-severe pancreatitis (AUC=0.827 and 0.870, respectively).

Discussion: In the current study, the qualitative assessment of DWI images indicated that all cases of mild acute pancreatitis (AP) displayed true diffusion restriction, while facilitated diffusion was observed in 80% of patients diagnosed with necrotizing pancreatitis. Our findings have validated the outcomes of earlier research regarding the average ADC values of both the healthy and acutely inflamed pancreas. According to the Revised Atlanta Classification, DWI has the ability to assist in the prompt diagnosis of acute pancreatitis and to differentiate mild forms from severe ones.

Conclusion: DW-MRI using both qualitative and quantitative methods provides a concise, safe, and radiation-free imaging method for early detection and assessing the severity of acute pancreatitis.

Background: Non-invasive biomarkers of liver metabolism are essential for early detection of metabolic alterations. Choline plays a central role in hepatic function, yet its dietary intake and imaging correlates remain underexplored. This study evaluated the feasibility of proton Magnetic Resonance Spectroscopy (1H-MRS) at 3T for hepatic choline quantification and examined its correlation with dietary intake in young women, a population at risk of nutrient-sensitive liver conditions.

Methods: In this prospective cohort study, 88 healthy female radiology students (mean age: 21.4 ± 1.8 years) underwent single-voxel 1H-MRS of the liver using a 3T Siemens Magnetom Vida scanner. Spectra were acquired with a point-resolved spectroscopy (PRESS) sequence (TR = 2000 ms, TE = 40 ms, voxel size = 20 × 20 × 20 mm3), with automated shimming and unsuppressed water referencing. Spectral analysis was performed using LCModel (v6.3), applying quality thresholds (Signal-to-Noise Ratio (SNR) > 5, linewidth < 0.1 ppm, Cramér–Rao Lower Bound (CRLB) < 20%. Hepatic choline concentrations were expressed in Institutional Units (IU). Dietary intake was assessed using a validated Food Frequency Questionnaire (FFQ).

Results: High-quality spectra were consistently obtained (mean SNR: 12.6 ± 3.1; linewidth: 0.048 ± 0.012 ppm). Mean hepatic choline concentration was 4.63 ± 1.21 IU, while mean dietary intake was 29.1 ± 8.7 mg/day. A significant positive correlation was observed (r = 0.555, p < 0.001). Regression analysis confirmed dietary intake as a significant predictor (β = 0.56, R2 = 0.308, p < 0.001).

Discussion: These findings demonstrate that ¹H MRS at 3T provides reproducible hepatic choline quantification and captures meaningful variability linked to dietary intake. The observed correlation highlights the potential of MRS as a translational biomarker of nutrient related liver metabolism. Integrating MRS into multiparametric liver imaging protocols may enhance early detection of metabolic alterations and broaden the scope of noninvasive liver assessment.

Conclusion: 1H-MRS at 3T is a feasible and reproducible technique for hepatic choline quantification. By measuring metabolites directly in the liver at their site of production, rather than in circulation, where concentrations may be altered, MRS provides physiologically relevant insights into nutrient-related hepatic metabolism. Its correlation with dietary intake highlights its potential as a translational imaging biomarker for early detection and risk stratification of nutrient-sensitive liver conditions.

The rapid advancement of computational technologies has significantly transformed medical diagnostics, particularly in the realm of neurological disorders. This review provides a comprehensive analysis of the current computational approaches employed for the diagnosis of five major neurological disorders: Alzheimer's disease, Parkinson's disease, Epilepsy, Huntington's disease, and Amyotrophic Lateral Sclerosis. By evaluating 140 peer-reviewed studies, we explored a diverse array of diagnostic methods, including machine learning algorithms, neuroimaging techniques, and electrophysiological signal analysis. Our review highlights the efficacy, accuracy, and limitations of these diagnostic methods, emphasizing their role in early detection and differential diagnosis. Furthermore, we discuss the integration of multimodal data and the potential of emerging technologies such as deep learning and artificial intelligence to enhance diagnostic practices. We also address the current challenges in clinical implementation and propose future research directions to improve diagnostic precision and patient outcomes. This review aims to serve as a valuable resource for researchers, clinicians, and stakeholders in the field of neurodiagnostics, fostering a deeper understanding of computational methodologies that shape the future of neurological disorder diagnosis.