Current Issue : April-June Volume : 2025 Issue Number : 2 Articles : 5 Articles
Objectives: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT). Methods: CT images of a 16 cm dosimetry phantom, a head phantom, and the brains of 11 patients were reconstructed using filtered backprojection (FBP) and various levels of DLR and HIR. The slice thickness was 5, 2.5, 1.25, and 0.625 mm. Phantom imaging was also conducted at various tube currents. The noise reduction ratio was calculated using FBP as the reference. For patient imaging, overall image quality was visually compared between DLR and HIR images that exhibited similar noise reduction ratios. Results: The noise reduction ratio increased with increasing levels of DLR and HIR in phantom and patient imaging. For DLR, noise reduction was more pronounced with decreasing slice thickness, while such thickness dependence was less evident for HIR. Although the noise reduction effects of DLR were similar between the head phantom and patients, they differed for the dosimetry phantom. Variations between imaging objects were small for HIR. The noise reduction ratio was low at low tube currents for the dosimetry phantom using DLR; otherwise, the influence of the tube current was small. In terms of visual image quality, DLR outperformed HIR in 1.25 mm thick images but not in thicker images. Conclusions: The degree of noise reduction using DLR depends on the slice thickness, tube current, and imaging object in addition to the level of DLR, which should be considered in the clinical use of DLR. DLR may be particularly beneficial for thin-slice imaging....
Background: Osteoporosis is commonly evaluated using dual-energy X-ray absorptiometry (DXA) for bone mineral density (BMD). Non-contrast computed tomography (CT) scans provide an alternative for opportunistic osteoporosis assessment. This study aimed to evaluate screening thresholds for osteoporosis based on CT attenuation values in Hounsfield units (HU) of L1–L4 vertebrae from CT scans of the abdominal region, compared to DXA assessments of the lumbar spine and hips. Methods: Conducted retrospectively over approximately two years, the analysis included 109 patients who had both CT and DXA scans within 12 months, excluding those with metal artifacts affecting the vertebrae. CT attenuation values in the trabecular region of the vertebrae were measured and compared among three groups based on the lowest T-score from DXA. Results: In a predominantly female cohort (mean age 66.3 years), the lowest CT attenuation values for L1–L4 vertebrae showed a moderate correlation with the lowest T-score, with a Pearson correlation coefficient of 0.542 (95% CI: 0.388, 0.667). A HU threshold of ≤142 at the L1 vertebra showed 91.9% sensitivity and 48.4% specificity, while a threshold of ≤160 HU showed 97.3% sensitivity and 31.3% specificity for screening osteoporosis. Conclusions: This study supports the use of non-contrast CT with these HU thresholds as an opportunistic tool for osteoporosis assessment....
This study investigates radiomic efficacy in post-surgical traumatic spinal cord injury (SCI), overcoming MRI limitations from metal artifacts to enhance diagnosis, severity assessment, and lesion characterization or prognosis and therapy guidance. Traumatic spinal cord injury (SCI) causes severe neurological deficits. While MRI allows qualitative injury evaluation, standard imaging alone has limitations for precise SCI diagnosis, severity stratification, and pathology characterization, which are needed to guide prognosis and therapy. Radiomics enables quantitative tissue phenotyping by extracting a high-dimensional set of descriptive texture features from medical images. However, the efficacy of postoperative radiomic quantification in the presence of metal-induced MRI artifacts from spinal instrumentation has yet to be fully explored. A total of 50 healthy controls and 12 SCI patients post-stabilization surgery underwent 3D multi-spectral MRI. Automated spinal cord segmentation was followed by radiomic feature extraction. Supervised machine learning categorized SCI versus controls, injury severity, and lesion location relative to instrumentation. Radiomics differentiated SCI patients (Matthews correlation coefficient (MCC) 0.97; accuracy 1.0), categorized injury severity (MCC: 0.95; ACC: 0.98), and localized lesions (MCC: 0.85; ACC: 0.90). Combined T1 and T2 features outperformed individual modalities across tasks with gradient boosting models showing the highest efficacy. The radiomic framework achieved excellent performance, differentiating SCI from controls and accurately categorizing injury severity. The ability to reliably quantify SCI severity and localization could potentially inform diagnosis, prognosis, and guide therapy. Further research is warranted to validate radiomic SCI biomarkers and explore clinical integration....
Objective: To explore regional homogeneity (ReHo) alterations after acupuncture treatment in poststroke cognitive impairment (PSCI) patients. Methods: Twenty-one PSCI patients who underwent acupuncture therapy in our hospital and 12 matched healthy controls were enrolled in this study. All study subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI); for PSCI patients, rs-fMRI scans were conducted before and after acupuncture therapy. Data preprocessing was performed using the DPARSF5.4 and SPM12 toolkits on the MATLAB 2022b platform. DPARSF5.4 was used to calculate the ReHo index of the preprocessed resting-state data. A two-sample t-test was used to compare the differences in ReHo between the PSCI patients group pretreatment and the control group (with sex and age as covariates), and a paired t-test was used to compare the differences in ReHo between the pretreatment and posttreatment groups of PSCI patients (without covariates). AAL_116_binary_ mask.nii was used as the statistical mask, and the statistical results were corrected using family-wise error correction, with P < 0.001 at the voxel level and P < 0.05 at the cluster level considered to indicate statistical significance. Results: In the right cerebellum area 6, the ReHo of the pretreatment PSCI group was significantly greater than that of the control group; in the left middle frontal gyrus, the ReHo of the posttreatment PSCI group was significantly higher than that of the pretreatment group. Conclusion: PSCI patients exhibited abnormal ReHo in the resting state, and ReHo was significantly altered after acupuncture treatment. The results of this study suggest that ReHo might be a potential biomarker in the diagnosis and treatment of PSCI....
Purpose: Studies on imaging findings in mixed connective tissue disease (MCTD) are limited. This study assessed the relationship between CT-derived parameters (pulmonary artery diameter [PAD] and lung parenchymal abnormalities [LPA]) and estimated pulmonary artery pressure (PAP) in patients with MCTD. Materials and Methods: This single-center retrospective study enrolled consecutive patients with MCTD who underwent CT and echocardiography within 6 months between December 2004 and November 2021. Chest CT was used to measure PAD (mm) and evaluate LPA (%). LPA was quantitatively assessed for reticular, ground-glass opacities, consolidation, or honeycombing. Peak tricuspid regurgitation velocity (TRV) on echocardiography was considered to reflect PAP. Correlation and partial correlation analyses were performed to assess the relationship between CT-derived parameters and peak TRV. Results: Overall, 116 patients (mean age 50.0 ± 17.0 years [SD]) with a median disease duration of 3.0 years had a median peak TRV of 2.28 m/sec and median PAD of 27.0 mm. Pulmonary hypertension was found in 18 (15.5%) patients. LPA was observed in 52 patients, with a median of 0.0% and a mean of 4.5% ± 8.9 [SD]. Peak TRV was correlated with PAD (r = 0.58, p < 0.001) and LPA (r = 0.40, p < 0.001). Peak TRV, adjusted for other CT parameters and confounding factors, showed a partial correlation with PAD (r = 0.49, p < 0.001) but was not correlated with LPA (r = 0.19, p = 0.04). Conclusion: A moderate positive correlation was observed in patients with MCTD between PAD and estimated PAP, irrespective of the presence of LPA, whereas LPA was not correlated with estimated PAP....
Loading....