Characterizing the hyper- and hypometabolism in temporal lobe epilepsy using multivariate machine learning.

Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy, presenting both structural and metabolic abnormalities in the ipsilateral mesial temporal lobe. While it has been demonstrated that the metabolic abnormalities in MTLE actually extend beyond the epileptogenic zone, how such multidimensional information is associated with the diagnosis of MTLE remains to be tested. Here, we explore the whole-brain metabolic patterns in 23 patients with MTLE and 24 healthy controls using [18 F]fluorodeoxyglucose PET imaging. Based on a multivariate machine learning approach, we demonstrate that the brain metabolic patterns can discriminate patients with MTLE from controls with a superior accuracy (>95%). Importantly, voxels showing the most extreme contributing weights to the classification (i.e., the most important regional predictors) distribute across both hemispheres, involving both ipsilateral negative weights over the anterior part of lateral and medial temporal lobe, posterior insula, and lateral orbital frontal gyrus, and contralateral positive weights over the anterior frontal lobe, temporal lobe, and lingual gyrus. Through region-of-interest analyses, we verify that in patients with MTLE, the negatively weighted regions are hypometabolic, and the positively weighted regions are hypermetabolic, compared to controls. Interestingly, despite that both hypo- and hypermetabolism have mutually contributed to our model, they may reflect different pathological and/or compensative responses. For instance, patients with earlier age at epilepsy onset present greater hypometabolism in the ipsilateral inferior temporal gyrus, while we find no evidence of such association with hypermetabolism. In summary, quantitative models utilizing multidimensional brain metabolic information may provide additional assistance to presurgical workups in TLE.

Evaluating the efficacy of balloon pulmonary angioplasty using quantitative analysis of SPECT pulmonary ventilation/perfusion scintigraphy in patients with chronic thromboembolic pulmonary hypertension.

Background: Single-photon emission computed tomography (SPECT) ventilation perfusion imaging is the main imaging method for the diagnosis of pulmonary embolism, and its application in the diagnosis and efficacy evaluation of chronic thromboembolic pulmonary hypertension (CTEPH) has been paid more and more attention. In recent years, with the development of computer software technology, ventilation/perfusion (V/Q) imaging quantitative analysis technology has become more and more mature. The objective of this study was to investigate the utility of quantitative analysis of pulmonary V/Q scintigraphy in evaluating the efficacy of balloon pulmonary angioplasty (BPA) in patients with CTEPH. Methods: In this retrospective analysis, we collected data of patients diagnosed with CTEPH who underwent BPA at the China-Japan Friendship Hospital from April 2018 to September 2020. The sample consisted of 23 males and 28 females, with an average age of 55.1±12.7 years. All patients underwent V/Q scintigraphy within one week before surgery, and we reviewed the pulmonary angiography within 1-3 months following the last BPA procedure. We repeated V/Q scintigraphy within 1 week before or after the pulmonary angiography, at the time of collecting clinical and hemodynamic parameters of these patients. We divided the patients into two groups based on the presence of residual pulmonary hypertension post-surgery and compared the pre- and post-operative quantitative pulmonary perfusion defect percentage scores (PPDs%) using the t-test. Results: In all, 102 V/Q scintigraphy scans were performed in 51 patients. The quantitative PPDs% were positively correlated with the hemodynamic indexes mean pulmonary arterial pressure (mPAP), pulmonary vascular resistance (PVR), and mean right ventricular pressure (RVP) (r=0.605, 0.391, and 0.464, respectively, all P<0.001) and negatively correlated with the 6-minute walking distance (6MWD) (r=-0.254, P=0.010). The average preoperative quantitative PPDs% were (49.0±15.6)% which significantly decreased to (33.5±13.9)% after surgery (t=11.249, P<0.001). The preoperative quantitative PPDs% were (54.7±15.7)% and (44.0±13.8)% in the residual pulmonary hypertension group and the non-residual pulmonary hypertension group, respectively (t=2.599, P=0.012). The postoperative quantitative PPDs% were (41.5±12.5)% and (26.3±11.0)%, in the residual pulmonary hypertension group and the non-residual pulmonary hypertension group, respectively (t=4.647, P<0.001). Conclusions: In this study, we found that quantitative analysis of SPECT pulmonary V/Q scintigraphy adequately reflected the pulmonary artery pressure and clinical status in patients with CTEPH. Our results demonstrate its definite utility in predicting residual pulmonary hypertension and in evaluating the postoperative efficacy of BPA in patients with CTEPH.

Improved image resolution on thoracic carcinomas by quantitative 18F-FDG coincidence SPECT/CT in comparison to 18F-FDG PET/CT.

Currently, 18F-FDG coincidence SPECT (Co-SPECT)/CT scan still serves as an important tool for diagnosis, staging, and evaluation of cancer treatment in developing countries. We implemented full physical corrections (FPC) to Co-SPECT (quantitative Co-SPECT) to improve the image resolution and contrast along with the capability for image quantitation. FPC included attenuation, scatter, resolution recovery, and noise reduction. A standard NEMA phantom filled with 10:1 F-18 activity concentration ratio in spheres and background was utilized to evaluate image performance. Subsequently, 15 patients with histologically confirmed thoracic carcinomas were included to undergo a 18F-FDG Co-SPECT/CT scan followed by a 18F-FDG PET/CT scan. Functional parameters as SUVmax, SUVmean, SULpeak, and MTV from both quantitative Co-SPECT and PET were analyzed. Image resolution of Co-SPECT for NEMA phantom was improved to reveal the smallest sphere from a diameter of 28 mm to 22 mm (17 mm for PET). The image contrast was enhanced from 1.7 to 6.32 (6.69 for PET) with slightly degraded uniformity in background (3.1% vs. 6.7%) (5.6% for PET). Patients' SUVmax, SUVmean, SULpeak, and MTV measured from quantitative Co-SPECT were overall highly correlated with those from PET ( r=0.82-0.88). Adjustment of the threshold of SUVmax and SUV to determine SUVmean and MTV did not further change the correlations with PET ( r=0.81-0.88). Adding full physical corrections to Co-SPECT images can significantly improve image resolution and contrast to reveal smaller tumor lesions along with the capability to quantify functional parameters like PET/CT.

Gd-EOB-DTPA-enhanced T1ρ imaging vs diffusion metrics for assessment liver inflammation and early stage fibrosis of nonalcoholic steatohepatitis in rabbits.

To assess the value of T1ρ,T1ρ on hepatobiliary phase (HBP) and diffusion metrics in staging of Non-alcoholic fatty liver disease (NAFLD) activity scores, inflammation, fibrosis in NASH rabbits model. Non-alcoholic steatohepatitis (NASH) rabbits model was induced by feeding a varied duration of high-fat, high-cholesterol diet. T1ρ,T1ρ (HBP) 20min after administration of Gd-EOB-DTPA, and Intravoxel incoherent motion imaging (IVIM) diffusion-weighted imaging were performed on a 3.0T magnetic resonance (MR) imaging unit. The diagnostic value of each parameter for NAS, inflammation and fibrosis severity were determined. T1ρ (r=0.658) and T1ρ (HBP) (r=0.750) have strong association with NASH overall activity, T1ρ (HBP) is strongly relevant to inflammation stage (r=0.812). There was negative association between f and inflammation (r=-0.480), whilst no significant relation between other three parameters (apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and true diffusion coefficient (D)) and inflammation or overall activity. The areas under the receiver operating characteristic curves (AUCs) of f, ADC, T1ρ and T1ρ-HBP were 0.871, 0.728, 0.849 and 0.949 for differentiating NASH; 0.731, 0.552, 0.925 and 0.922 for G2-3 inflammation; and 0.767, 0.625, 0.816, and 0.882 for S1-2 fibrosis. Comparison of ROC curve showed T1ρ (HBP) had an optimal diagnostic performance for NASH [T1ρ (HBP) vs ADC, AUC:0.949 vs 0.728, P=0.043], inflammation [T1ρ (HBP) vs ADC, AUC:0.922 vs 0.552, P=0.003], fibrosis [T1ρ (HBP) vs ADC, AUC:0.882 vs 0.625, P=0.046]. The combination of T1ρ (HBP)+perfusion fraction (f) showed highest diagnostic value for NASH (AUC:0.971), inflammation (AUC:0.935). Among T1ρ imaging and IVIM diffusion metrics, combination of T1rho (HBP)+f was found to be superior noninvasive imaging biomarker for NASH activity assessment.