Quantitative Imaging in Medicine and Surgery最新文献

Background: Accurate preoperative glioma grading and isocitrate dehydrogenase (IDH) mutation status prediction via conventional magnetic resonance imaging (MRI) remain challenging. We aimed to evaluate the performance of longitudinal relaxation time in rotating frame (T1rho) mapping and amide proton transfer (APT)-weighted chemical exchange saturation transfer (CEST) for grading gliomas and predicting IDH mutation status using 5-T MRI.

Methods: Fifty patients with histopathologically confirmed glioma underwent 5-T MRI, including T2-weighted, T1-weighted, T1rho mapping, APT-weighted, and contrast-enhanced T1-weighted imaging. The T1rho and APT parameters were measured at the solid tumor portion, peritumoral edema, and contralateral normal-appearing white matter. In addition to absolute lesion values, the relative values (rT1rho and rAPT) were defined as the difference between the lesion and white matter. Differences between low-grade glioma (LGG) and high-grade glioma (HGG) and between IDH mutant-type and IDH wild-type were evaluated via the Mann-Whitney U test. Receiver operating characteristic (ROC) analyses were performed to assess the performance of each parameter and T1rho-plus-APT combination.

Results: Among the 50 patients, 12 had LGG, 38 had HGG, 19 had the IDH mutant type, and 31 had IDH wild type. Compared with LGGs, HGGs exhibited significantly greater T1rho, rT1rho, APT, and rAPT values in both tumor and edema areas (P≤0.036). ROC analysis of individual parameters revealed that T1rho in edema achieved the highest area under the curve (AUC) in differentiating HGG from LGG (AUC, 0.974; sensitivity, 97.4%; specificity, 91.7%). With the combination of T1rho in edema and rAPT in tumor, the AUC further improved to 0.978 (sensitivity, 92.1%; specificity, 100%). Compared with the IDH mutant-type group, the IDH wild-type group had significantly greater T1rho and rT1rho values in tumor, T1rho and rT1rho values in edema, and APT and rAPT values in tumor (P≤0.003). T1rho in the edema achieved the highest AUC (0.883) in differentiating IDH wild type from IDH mutant type (sensitivity, 90.3%; specificity, 89.5%). Significant differences were noted between grade 2, 3, and 4 gliomas (P≤0.007).

Conclusions: Both T1rho mapping and APT-CEST can be used to grade gliomas and differentiate IDH mutational status. Combining these two techniques further aids in the differentiation of HGG from LGG.

Background: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, yet its stage-dependent neurobiological mechanisms remain incompletely understood. Multimodal magnetic resonance imaging (MRI) offers a noninvasive approach to investigate both functional and structural alterations across disease stages. Therefore, this study aimed to characterize stage-dependent functional and iron-related brain alterations in PD using multimodal MRI and to explore their associations with motor severity.

Methods: We enrolled 104 PD patients, stratified into early-stage (n=49) and advanced-stage (n=55) based on Hoehn and Yahr (H&Y) score, along with 53 age- and sex- matched healthy controls. Quantitative susceptibility mapping (QSM) quantified iron deposition in the substantia nigra (SN) and globus pallidus (GP), while resting-state functional magnetic resonance imaging (rs-fMRI) was used to assess functional alterations using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). Group comparisons were conducted using one-way analysis of variance (ANOVA) with post-hoc tests, and voxel-wise analyses were corrected using cluster-level false discovery rate (FDR, P<0.05). Correlation analyses were performed to evaluate associations between imaging metrics and Unified Parkinson's Disease Rating Scale part III (UPDRS-III) motor scores.

Results: Compared with healthy controls, both early and advanced-stage PD patients showed significantly increased iron deposition in the bilateral SN and GP (all P<0.05), with higher QSM values in advanced-stage PD than in early-stage PD (all P<0.01). Iron deposition in these regions was positively correlated with motor severity assessed by UPDRS-III scores (all P<0.001). Early-stage PD primarily exhibited abnormal fALFF and ReHo in visual-related regions, whereas advanced-stage PD showed more widespread involvement of the basal ganglia-thalamocortical motor circuit, frontoparietal regions, and limbic structures. Functional alterations in motor-related regions were significantly associated with UPDRS-III scores (all P<0.001), while ReHo changes in limbic regions were correlated with cognitive performance (Mini-Mental State Examination, MMSE; P<0.001).

Conclusions: Building on established evidence that PD involves progressive iron deposition in the SN and GP and widespread neural network dysfunction, our multimodal MRI findings demonstrate that integrating ReHo, fALFF, and QSM provides a framework for characterizing stage-specific pathophysiological changes and support their potential as biomarkers for early diagnosis, disease staging, and therapeutic development.

Background: Understanding iliac hemodynamics in both healthy individuals and patients with vascular diseases is important from both physiological and pathological perspectives, and the four-dimensional (4D) flow technique is a valuable tool for the accurate quantification of hemodynamics. However, conventional 4D flow acquisition is time-consuming. Therefore, this study aimed to evaluate the hemodynamics of the iliac arteries and veins using both conventional single-velocity encoding (VENC) and compressed sensing (CS)-accelerated dual-VENC 4D flow sequences in healthy controls (HCs) and patients with deep vein thrombosis (DVT).

Methods: This study included HCs and patients with DVT between December 2024 and April 2025. Two conventional single-VENC 4D flow sequences with high and low VENCs and a dual-VENC CS-accelerated sequence were performed and postprocessed by two experienced readers. Quality control, including test-retest reliability, agreement between techniques, and intra- and inter-reader agreement, was performed, and the correlation between age and flow parameters was also calculated.

Results: The acquisition time for conventional high-VENC, low-VENC, and CS dual-VENC 4D flow was 10.6, 10.7, and 8.8 min, respectively. In the quality control analysis, the intraclass correlation coefficients (ICCs) for test-retest reliability, intraobserver, and interobserver agreements were all >0.85 (P≤0.001). In arterial segments, both velocity and wall shear stress (WSS) measured by the CS methods were lower than those obtained by conventional methods, with the underestimation percent ranging from 2.8% to 11.8% in HCs and from 1.9% to 14.8% in patients with DVT. For venous segments, CS-based measurements underestimated velocity and WSS by 1.1-12.0% in HCs and 1.3-14.2% in patients with DVT. Negative correlations were found between age and arterial velocity (R=-0.33), arterial WSS (R=-0.34), and venous velocity (R=-0.29) (all P values <0.05).

Conclusions: The study results indicate that the CS dual-VENC 4D flow sequence is feasible for rapid simultaneous assessment of iliac arteries and veins in both HCs and patients with DVT. However, the underestimation caused by CS should be noted.

Background: Nutcracker syndrome (NCS) diagnosis remains challenging due to the lack of non-invasive, reliable methods. Current techniques, including Doppler ultrasound and computed tomography angiography (CTA), lack hemodynamic data, with invasive measurement of the left renal vein-inferior vena cava (LRV-IVC) pressure gradient (true pressure gradient, TPG) being the gold standard. This study aimed to validate a novel non-invasive approach using finite element analysis (FEA) to simulate the LRV-IVC pressure gradient (SPG) to assist in diagnosing and monitoring NCS.

Methods: This retrospective study included 46 patients (35 NCS, 11 controls) who underwent CTA and invasive TPG measurement. Patient-specific 3D left renal vein (LRV) models were reconstructed from CTA data using MIMICS and 3-matic software. Hemodynamic simulations were performed via ANSYS (an engineering simulation software) to calculate SPG. Diagnostic performance of SPG and imaging parameters (e.g., beak sign, LRV diameter ratio) was evaluated using receiver operating characteristic (ROC) analysis.

Results: SPG showed no significant difference from TPG (5.6±3.9 vs. 5.5±1.9 mmHg, P>0.05) in NCS patients. Postoperative SPG and TPG decreased comparably (P<0.05). SPG achieved an area under the curve (AUC) of 0.808 [95% confidence interval (CI): 0.69-0.92] with 81.8% sensitivity and 80.0% specificity at a cutoff of 3.3 mmHg, outperforming traditional imaging markers. The aortomesenteric angle, LRV diameter ratio, and beak sign also demonstrated diagnostic utility.

Conclusions: FEA-derived SPG correlates closely with invasive TPG, offering a reliable, non-invasive alternative for NCS diagnosis and postoperative monitoring. This approach enhances objectivity, reduces reliance on operator-dependent techniques, and may facilitate early intervention. Further refinement of FEA models and multicenter validation are warranted.

Background: Delayed hydrocephalus, a complication that significantly impacts patient prognosis, arises following subarachnoid hemorrhage (SAH). In this study, we conducted a comprehensive investigation into the correlation between clinical features and computed tomography (CT) images, with the aim of elucidating the development of delayed hydrocephalus in SAH patients. We have developed a model for the early detection and evaluation of SAH, which is based on deep learning (DL).

Methods: The DeepSH model was constructed by concatenating a super-resolution generative adversarial network (SRGAN) model based on a convolutional neural network (CNN) generator and an imagingomics model based on traditional machine learning (ML) models. The data were obtained from non-contrast CT (NCCT) images of 861 patients with SAH admitted to three hospitals in China between July 2019 and December 2021. After training, the model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. The ROC curves and calibration curves indicated that the model fit well, and the decision curve analysis (DCA) validated the clinical utility of DeepSH.

Results: DeepSH demonstrated superior performance, with areas under the curves (AUCs) improved by 0.006 and 0.219 (P<0.05) in the internal- and external-testing sets, respectively, relative to the support vector machine (SVM) model. Clinical benefit and overall efficiency of junior radiologists were significantly improved with model assistance for the internal- and external-testing sets.

Conclusions: DeepSH significantly outperforms conventional methods and expert assessment in predicting SAH-associated delayed hydrocephalus (SAH-H) from NCCT images, providing a valuable tool for early clinical decision-making that can improve patient prognosis.

Background: Contrast-enhanced computed tomography (CT) is routinely employed for diagnosing abdominal diseases. Individualized contrast media (CM) dosing protocols are vital for patient safety and image quality. This study aimed to compare the vascular and parenchymal enhancement effects and overall image quality between fixed-dose and total body weight (TBW)-based high-concentration (400 mgI/mL) CM dosing protocols in abdominal multiphasic contrast-enhanced CT.

Methods: Patients scheduled for abdominal multiphasic CT were retrospectively enrolled and placed into the TBW-based dosing group or the fixed-dose group (80 mL CM at 120 kVp). The TBW-based dosing group was further divided into five subgroups: 400 mgI/TBW (kg) at 100 kVp, 400 mgI/TBW (kg) at 120 kVp, 450 mgI/TBW (kg) at 100 kVp, 450 mgI/TBW (kg) at 120 kVp, and 500 mgI/TBW (kg) at 120 kVp. The CT attenuation values of blood vessels and organs were measured, and the contrast enhancement index (CEI), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated.

Results: There were no significant differences observed in age, sex, TBW, or body mass index between the fixed-dose group and TBW-based subgroups. The TBW-based dosing groups received a significantly lower volume of CM compared with the fixed-dose group (P<0.001). Moreover, the fixed-dose group and TBW-based subgroups were significantly different in terms of the CEI of the aorta, portal vein, and hepatic vein, as well as the SNR and CNR of the aorta, portal vein, kidney, pancreas, liver, and hepatic vein (all P<0.001) but not the SNR of the hepatic vein in the portal venous phase (P=0.050). No significant differences in subjective image quality were found between the 450 mgI/TBW (kg) at 100 kVp, 500 mgI/TBW (kg) at 120 kVp, and the fixed-dose groups.

Conclusions: In abdominal multiphasic contrast-enhanced CT, the TBW-based protocol of 450 mgI/kg at 100 kVp is recommended for assessing vasculature, and the TBW-based protocol of 500 mgI/kg at 120 kVp is recommended for parenchymal and tumor visualization.

Background: Metallic interventional devices such as brachytherapy seeds and stents, are extensively utilized in clinical settings. However, these devices generate significant susceptibility artifacts in conventional magnetic resonance imaging (MRI), manifesting as signal voids that impede precise visualization. Susceptibility-driven positive contrast MRI (PC-MRI) mitigates this limitation by solving regularized ℓ1-norm minimization problems to reconstruct positive contrast images. The conventional nonlinear conjugate gradient (CG) algorithm, commonly employed for solving such non-smooth convex optimization problems, encounters challenges, including slow convergence rates, sensitivity to initial solutions and parameter selection, and difficulties in achieving optimal imaging reconstruction due to ill-posed inversion problems. This study aimed to develop and evaluate an accelerated primal-dual (PD) optimization framework with graphics processing unit (GPU) parallelization to overcome the limitations of the conventional CG algorithm for susceptibility-driven PC-MRI reconstruction. The proposed method seeks to solve the exact ℓ1-minimization problem without smoothing approximations.

Methods: The efficacy of the method was evaluated through computational simulations, phantom experiments, and in vivo studies. Quantitative assessments included convergence behavior, full width at half maximum (FWHM), signal-to-noise ratio (SNR), and reconstruction time. Statistical significance was determined using paired t-tests, with a significance threshold set at P<0.01.

Results: Comparing to the conventional CG method, the PD approach can provide a faster reconstruction convergence rate of 2-4 times, and it demonstrated an end-to-end easy-adjustment method that does not rely on parameter tuning. The results also show that the PD method achieves better visualization and more accurate localization of the metallic interventional devices in positive contrast. Quantitative evaluations showed that the PD method achieved a significant reduction in FWHM near metallic seeds (e.g., from 1.15 for CG to 1.02 for PD in Patient 2, 11.3% improvement, P<0.01), indicating superior image sharpness. A notable improvement in SNR was also observed (e.g., from 110.34 for CG to 131.65 for PD in Patient 2, 19.3% enhancement, P<0.01), confirming enhanced image quality in both phantom and in vivo experiments. Furthermore, GPU acceleration further improved reconstruction speed of the PD approach by 4-15 times.

Conclusions: The susceptibility-driven positive contrast imaging technique based on PD regularization demonstrates faster convergence, superior image quality, and easier parameter adjustment compared to conventional CG methods. The speed of reconstruction can be further improved by GPU acceleration.

Background: Concave supra-arch triple branched stent-graft system (CS system) offers a new option for treating aortic arch pathologies. However, the efficacy of the innovative device still lacks objective evaluations. Patient-specific CS system design and treatment strategies remain unknown. This study aims to assess the effectiveness and to inform the patient-specific CS system design by evaluating the hemodynamic effects of key parameters.

Methods: Simulations were conducted via pre- and post-operative computed tomography angiography datasets from five first-in-man study cases. Parametric studies on the CS system were developed by virtually adjusting concave degree (angle α) in scenarios with patient-specific aortic diameter. Boundary conditions were obtained through three-element Windkessel model. Quantitative and qualitative hemodynamic analyses were conducted via flow rate, pressure, time-averaged wall shear stress (TAWSS)-based parameters and energy loss.

Results: CS system insertion effectively maintained supra-aortic trunks (SATs) blood flow, without significantly affecting ascending aortic (AA) pressure and hemodynamic environments, regardless of postoperative normotensive (120/80 mmHg) or hypertensive (180/140 mmHg) states. Larger concave angles improved SATs perfusion by approximately 1-2%, with hemodynamic variations becoming notably more pronounced when α increased beyond 150°. Specifically, increases in SATs flow were 0.6-0.7% from 120° to 150°, compared with 1.8-2.0% from 150° to 180°, while flow to the left subclavian artery decreased by ~0.45% and ~0.75% over the same ranges. AA pressure changes remained small, with CS implantation increasing systolic pressure by only ~1.2%. Larger aortic diameters or smaller diameter differences between AA and descending aorta (DA) further reduced postoperative AA pressure by approximately 0.1-2%. Notably, patients with smaller aortic diameters exhibited substantially larger hemodynamic changes: for example, TAWSS in the thoracic aorta increased by up to ~40% when D1 =30 mm, compared with only ~10% when D1 =48 mm.

Conclusions: CS system shows improved hemodynamic features in treating aortic arch aneurysm and can maintain stability under both normotensive and hypertensive postoperative blood pressure conditions. Larger concave angle can improve surgical convenience, but may also increase the risk of pressure elevation. For patients with small aortic diameters, reducing the concave degree may help to optimize the hemodynamic environment. The findings presented herein provide objective evaluation for assessing CS system outcomes and patient-specific clinical decision making.