Clinical [18F]FSPG Positron Emission Tomography Imaging Reveals Heterogeneity in Tumor-Associated System xc- Activity.

BACKGROUND: (4S)-4-(3-[18F]fluoropropyl)-L-glutamic acid ([18F]FSPG) positron emission tomography/computed tomography (PET/CT) provides a readout of system xc- transport activity and has been used for cancer detection in clinical studies of different cancer types. As system xc- provides the rate-limiting precursor for glutathione biosynthesis, an abundant antioxidant, [18F]FSPG imaging may additionally provide important prognostic information. Here, we performed an analysis of [18F]FSPG radiotracer distribution between primary tumors, metastases, and normal organs from cancer patients. We further assessed the heterogeneity of [18F]FSPG retention between cancer types, and between and within individuals. METHODS: This retrospective analysis of prospectively collected data compared [18F]FSPG PET/CT in subjects with head and neck squamous cell cancer (HNSCC, n = 5) and non-small-cell lung cancer (NSCLC, n = 10), scanned at different institutions. Using semi-automated regions of interest drawn around tumors and metastases, the maximum standardized uptake value (SUVmax), SUVmean, SUV standard deviation and SUVpeak were measured. [18F]FSPG time-activity curves (TACs) for normal organs, primary tumors and metastases were subsequently compared to 18F-2-fluoro-2-deoxy-D-glucose ([18F]FDG) PET/CT at 60 min post injection (p.i.). RESULTS: The mean administered activity of [18F]FSPG was 309.3 ± 9.1 MBq in subjects with NSCLC and 285.1 ± 11.3 MBq in those with HNSCC. The biodistribution of [18F]FSPG in both cohorts showed similar TACs in healthy organs from cancer patients. There was no statistically significant overall difference in the average SUVmax of tumor lesions at 60 min p.i. for NSCLC (8.1 ± 7.1) compared to HNSCC (6.0 ± 4.1; p = 0.29) for [18F]FSPG. However, there was heterogeneous retention between and within cancer types; the SUVmax at 60 min p.i. ranged from 1.4 to 23.7 in NSCLC and 3.1-12.1 in HNSCC. CONCLUSION: [18F]FSPG PET/CT imaging from both NSCLC and HNSCC cohorts showed the same normal-tissue biodistribution, but marked tumor heterogeneity across subjects and between lesions. Despite rapid elimination through the urinary tract and low normal-background tissue retention, the diagnostic potential of [18F]FSPG was limited by variability in tumor retention. As [18F]FSPG retention is mediated by the tumor's antioxidant capacity and response to oxidative stress, this heterogeneity may provide important insights into an individual tumor's response or resistance to therapy.

Differences in Neuropathology between Nitroglycerin-Induced Mouse Models of Episodic and Chronic Migraine.

Multiple animal models of migraine have been used to develop new therapies. Understanding the transition from episodic (EM) to chronic migraine (CM) is crucial. We established models mimicking EM and CM pain and assessed neuropathological differences. EM and CM models were induced with single NTG or multiple injections over 9 days. Mechanical hypersensitivity was assessed. Immunofluorescence utilized c-Fos, NeuN, and Iba1. Proinflammatory and anti-inflammatory markers were analyzed. Neuropeptides (CGRP, VIP, PACAP, and substance P) were assessed. Mechanical thresholds were similar. Notable neuropathological distinctions were observed in Sp5C and ACC. ACC showed increased c-Fos and NeuN expression in CM (p < 0.001) and unchanged in EM. Sp5C had higher c-Fos and NeuN expression in EM (p < 0.001). Iba1 was upregulated in Sp5C of EM and ACC of CM (p < 0.001). Proinflammatory markers were strongly expressed in Sp5C of EM and ACC of CM. CGRP expression was elevated in both regions and was higher in CM. VIP exhibited higher levels in the Sp5C of EM and ACC of CM, whereas PACAP and substance P were expressed in the Sp5C in both models. Despite similar thresholds, distinctive neuropathological differences in Sp5C and ACC between EM and CM models suggest a role in the EM to CM transformation.

Prognostic value of left ventricular mechanical dyssynchrony indices derived from gated myocardial perfusion SPECT in coronary artery disease: a systematic review and meta-analysis.

PURPOSE: Left ventricular mechanical dyssynchrony (LVMD) is an important prognostic factor in coronary artery disease. A growing body of evidence indicates that LVMD parameters derived from phase analysis of gated myocardial SPECT may allow risk stratification for future cardiac events. We performed a systematic review and meta-analysis on the prognostic value of LVMD on gated SPECT in patients with coronary artery disease. METHODS: PubMed, Embase, and the Cochrane library were searched until August 25, 2022, for studies reporting the prognostic value of LVMD on gated SPECT for outcomes of all-cause death, cardiac death, or major adverse cardiovascular event (MACE) in patients with coronary artery disease. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were meta-analytically pooled using a random-effects model. RESULTS: Nine studies (26,750 patients) were included in a qualitative synthesis. Among the SPECT LVMD parameters used in various studies, high phase standard deviation, phase bandwidth, and phase entropy were widely evaluated and reported to be associated with high rates of all-cause death, cardiac death, or MACE. For five studies (23,973 patients) in the quantitative synthesis, the pooled HR of LVMD for predicting MACE was 2.81 (95% CI 2.03-3.88). Studies using combined phase parameters to define LVMD showed higher HRs than a study using phase entropy (p = 0.0180). CONCLUSION: LVMD from gated myocardial SPECT is a significant prognostic factor for coronary artery disease. Phase analysis of gated SPECT may be useful for accurate risk stratification and could be applied for clinical decision-making in such patients.

Diagnostic Performance of Perfusion-Only SPECT/CT for Chronic Thromboembolic Pulmonary Hypertension in Comparison With Ventilation-Perfusion Planar, SPECT, and SPECT/CT Imaging.

PURPOSE: The aim of this study was to assess the diagnostic performance of perfusion-only SPECT/CT (Q SPECT/CT) in comparison with that of ventilation/perfusion planar scintigraphy (V/Q planar), perfusion SPECT with ventilation scan (V/Q SPECT), and perfusion SPECT/CT with ventilation scan (V/Q SPECT/CT) in chronic thromboembolic pulmonary hypertension (CTEPH). PATIENTS AND METHODS: Patients with pulmonary hypertension who underwent ventilation-perfusion planar and SPECT/CT were retrospectively recruited. Two nuclear medicine physicians interpreted V/Q planar, V/Q SPECT, V/Q SPECT/CT, and Q SPECT/CT according to the European Association of Nuclear Medicine criteria. The diagnostic accuracy of these modalities for CTEPH was compared using a composite reference standard of pulmonary angiography, imaging test, cardiorespiratory assessment, and follow-up. RESULTS: A total of 192 patients were enrolled, including 85 with CTEPH. The sensitivity of Q SPECT/CT was 98.8%, which similar to that of V/Q planar (97.6%), V/Q SPECT (96.5%), or V/Q SPECT/CT (100.0%). In contrast, Q SPECT/CT exhibited significantly lower specificity (73.8%) compared with V/Q planar (86.9%, P = 0.001), V/Q SPECT (87.9%, P < 0.001), and V/Q SPECT/CT (88.8%, P < 0.001). The significantly lower specificity of Q SPECT/CT, compared with the 3 others, was observed in the subgroup aged ≥50 years ( P < 0.001 for all), but not in those <50 years. CONCLUSIONS: Q SPECT/CT exhibited lower specificity compared with V/Q planar, V/Q SPECT, and V/Q SPECT/CT in diagnosing CTEPH. It might underscore the essential role of a ventilation scan in patients with PH, even with the introduction of SPECT/CT.

Lymphatic remapping by long-term lymphoscintigraphy follow-up in secondary lymphedema after breast cancer surgery.

The purpose of the study is to investigate long-term changes on lymphoscintigraphy and their association with clinical factors in breast cancer-related lymphedema (BCRL) patients. This single-center cohort study included BCRL patients who underwent baseline and follow-up lymphoscintigraphy. The percentage of excessive circumference (PEC) of the affected upper limb compared with the unaffected side was used as an indicator of the clinical severity of BCRL. Each 99mTc-phytate lymphoscintigraphy image was categorized according to the Taiwan lymphoscintigraphy staging system. Clinical parameters and the lymphoscintigraphy stage at baseline and follow-up were compared and analyzed. Eighty-seven patients were included. Baseline and follow-up lymphoscintigraphies were performed at median 7 (interquartile range [IQR]: 2‒14) and 78 (IQR: 49‒116) months after surgery, respectively. Both lymphoscintigraphy stage and PEC showed variable change with overall increases in their severity. Stepwise multivariable analysis revealed follow-up lymphoscintigraphy stage (P = 0.001) to be independent variables for PEC at follow-up, however, baseline lymphoscintigraphy stage was not. The clinical courses of BCRL and patients' lymphoscintigraphy patterns showed diverse changes over long-term follow-up. In addition to initial lymphoscintigraphy for diagnosis, lymphatic remapping by follow-up lymphoscintigraphy can be useful to visualize functional changes in the lymphatic system that may guide the optimal management in BCRL.

Comparison of SUVA/V and SUVA-V for Evaluating Atherosclerotic Inflammation in 18F-FDG PET/CT.

Purpose: This study aimed to compare the clinical significance of two parameters, division of standardized uptake value (SUV) of target arterial activity by background venous blood pool activity (SUVA/V) and subtraction of background venous blood pool activity from SUV of target arterial activity (SUVA-V) of carotid arteries with atherosclerotic plaques using 18F-fluorodeoxyglucose (FDG) positron emission tomography and computed tomography (PET/CT). Methods: Patients aged 50 years or more who were diagnosed with carotid artery stenosis of 50% or more with carotid Doppler ultrasonography and had torso 18F-FDG PET/CT were enrolled retrospectively and classified patients who developed cerebrovascular events (CVEs) within 5 years after 18F-FDG PET/CT scan as the active group and patients who did not experience the CVE within 5 years as an inactive group. We calculated SUVA/V and SUVA-V using measurements of SUVmax of carotid arteries and mean SUV of superior vena cava (SVC). Results: SUVA-V, SUVA-V_high, and SUVA-V_low were significantly higher in the active group than in the inactive group, but neither SUVA/V, SUVA/V_high, nor SUVA/V_low showed significant differences between the active and inactive groups. The difference in rank between groups of SUVA/V_high and SUVA/V_low was greater than the difference in rank between groups of SUVA-V_high and SUVA-V_low. The CVE incidence differed between SUVA/V_high and SUVA/V_low of high carotid FDG uptake, but the CVE incidence did not differ between SUVA-V_high and SUVA-V_low of high carotid FDG uptake. Conclusion: SUVA-V may be a more rational solution than SUVA/V for evaluating atherosclerotic plaque inflammation on 18F-FDG PET/CT.

miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer's disease.

BACKGROUND: Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers. METHODS: We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification. RESULTS: Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and APOE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs. CONCLUSIONS: Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Effect of pre-stroke antiplatelet use on stroke outcomes in acute small vessel occlusion stroke with moderate to severe white matter burden.

BACKGROUND: Cerebral small vessel disease is characterized by white matter hyperintensities (WMH) and acute small vessel occlusion (SVO) stroke. We investigated the effect of prior antiplatelet use (APU) on stroke outcome in 1151 patients with acute SVO stroke patients and moderate to severe WMH. METHODS: Using a multicenter database, this retrospective study used quantitative WMH volume measurements and propensity score matching (PSM) for comparisons between patients with prior APU and without APU. Primary outcomes were stroke progression and poor functional outcome (modified Rankin Scale>2) at 3 months. Logistic regression analyses assessed associations between prior APU, WMH burden, and stroke outcomes. RESULTS: Stroke progression was lower in the prior APU group in both the total cohort (14.8% vs. 6.9%, p < 0.001) and the PSM cohort (16.3% vs. 6.9%, p < 0.001). The proportion of poor functional outcomes at 3 months was not significantly different in the total cohort, but the PSM cohort showed a lower proportion in the prior APU group (30.8% vs. 20.2%, p = 0.002). Logistic regression analysis confirmed that prior APU was associated with a reduced risk of stroke progression (OR, 0.39; 95% CI, 0.22-0.70; p = 0.001) and poor functional outcome at 3 months (OR, 0.37; 95% CI, 0.23-0.59; p < 0.001). CONCLUSION: Prior APU is associated with reduced stroke progression and improved functional outcome at 3 months in acute SVO stroke patients with moderate to severe WMH. Early treatment of WMH and acute SVO stroke may have potential benefits in improving stroke outcomes.

Deep Learning-Based Knee MRI Classification for Common Peroneal Nerve Palsy with Foot Drop.

Foot drop can have a variety of causes, including the common peroneal nerve (CPN) injuries, and is often difficult to diagnose. We aimed to develop a deep learning-based algorithm that can classify foot drop with CPN injury in patients with knee MRI axial images only. In this retrospective study, we included 945 MR image data from foot drop patients confirmed with CPN injury in electrophysiologic tests (n = 42), and 1341 MR image data with non-traumatic knee pain (n = 107). Data were split into training, validation, and test datasets using a 8:1:1 ratio. We used a convolution neural network-based algorithm (EfficientNet-B5, ResNet152, VGG19) for the classification between the CPN injury group and the others. Performance of each classification algorithm used the area under the receiver operating characteristic curve (AUC). In classifying CPN MR images and non-CPN MR images, EfficientNet-B5 had the highest performance (AUC = 0.946), followed by the ResNet152 and the VGG19 algorithms. On comparison of other performance metrics including precision, recall, accuracy, and F1 score, EfficientNet-B5 had the best performance of the three algorithms. In a saliency map, the EfficientNet-B5 algorithm focused on the nerve area to detect CPN injury. In conclusion, deep learning-based analysis of knee MR images can successfully differentiate CPN injury from other etiologies in patients with foot drop.

miR-129-5p as a biomarker for pathology and cognitive decline in Alzheimer's disease.

Background: Alzheimer's dementia (AD) pathogenesis involves complex mechanisms, including microRNA (miRNA) dysregulation. Integrative network and machine learning analysis of miRNA can provide insights into AD pathology and prognostic/diagnostic biomarkers. Methods: We performed co-expression network analysis to identify network modules associated with AD, its neuropathology markers, and cognition using brain tissue miRNA profiles from the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) (N = 702) as a discovery dataset. We performed association analysis of hub miRNAs with AD, its neuropathology markers, and cognition. After selecting target genes of the hub miRNAs, we performed association analysis of the hub miRNAs with their target genes and then performed pathway-based enrichment analysis. For replication, we performed a consensus miRNA co-expression network analysis using the ROS/MAP dataset and an independent dataset (N = 16) from the Gene Expression Omnibus (GEO). Furthermore, we performed a machine learning approach to assess the performance of hub miRNAs for AD classification. Results: Network analysis identified a glucose metabolism pathway-enriched module (M3) as significantly associated with AD and cognition. Five hub miRNAs (miR-129-5p, miR-433, miR-1260, miR-200a, and miR-221) of M3 had significant associations with AD clinical and/or pathologic traits, with miR129-5p by far the strongest across all phenotypes. Gene-set enrichment analysis of target genes associated with their corresponding hub miRNAs identified significantly enriched biological pathways including ErbB, AMPK, MAPK, and mTOR signaling pathways. Consensus network analysis identified two AD-associated consensus network modules, and two hub miRNAs (miR-129-5p and miR-221). Machine learning analysis showed that the AD classification performance (area under the curve (AUC) = 0.807) of age, sex, and apoE ε4 carrier status was significantly improved by 6.3% with inclusion of five AD-associated hub miRNAs. Conclusions: Integrative network and machine learning analysis identified miRNA signatures, especially miR-129-5p, as associated with AD, its neuropathology markers, and cognition, enhancing our understanding of AD pathogenesis and leading to better performance of AD classification as potential diagnostic/prognostic biomarkers.

Effect of Cerebral Small Vessel Disease Burden on Infarct Growth Rate and Stroke Outcomes in Large Vessel Occlusion Stroke Receiving Endovascular Treatment.

This study aimed to investigate the association between cerebral small vessel disease (CSVD) burden and infarct growth rate (IGR) in patients with large vessel occlusion (LVO) stroke who underwent endovascular treatment (EVT). A retrospective analysis was conducted on a cohort of 495 patients with anterior circulation stroke who received EVT. CSVD burden was assessed using a CSVD score based on neuroimaging features. IGR was calculated from diffusion-weighted imaging (DWI) lesion volumes divided by the time from stroke onset to imaging. Clinical outcomes included stroke progression and functional outcomes at 3 months. Multivariate analyses were performed to assess the relationship between CSVD burden, IGR, and clinical outcomes. The fast IGR group had a higher proportion of high CSVD scores than the slow IGR group (24.4% vs. 0.8%, p < 0.001). High CSVD burden was significantly associated with a faster IGR (odds ratio [95% confidence interval], 26.26 [6.26-110.14], p < 0.001) after adjusting for confounding factors. High CSVD burden also independently predicted stroke progression and poor functional outcomes. This study highlights a significant relationship between CSVD burden and IGR in LVO stroke patients undergoing EVT. High CSVD burden was associated with faster infarct growth and worse clinical outcomes.

Performance of deep learning models for response evaluation on whole-body bone scans in prostate cancer.

OBJECTIVE: We aimed to develop deep learning classifiers for assessing therapeutic response on bone scans of patients with prostate cancer. METHODS: A set of 3791 consecutive bone scans coupled with their last previous scan (1528 patients) was evaluated. Bone scans were labeled as "progression" or "nonprogression" on the basis of clinical reports and image review. A 2D-convolutional neural network architecture was trained with three different preprocessing methods: 1) no preprocessing (Raw), 2) spatial normalization (SN), and 3) spatial and count normalization (SCN). Data were allocated into training, validation, and test sets in the ratio of 72:8:20, with the 20% independent test set rotating all scans over a five-fold testing procedure. A Grad-CAM algorithm was employed to generate class activation maps to visualize the lesions contributing to the decision. Diagnostic performance was compared using area under the receiver operating characteristics curves (AUCs). RESULTS: The data consisted of 791 scans labeled as "progression" and 3000 scans labeled as "nonprogression." The AUCs of the classifiers were 0.632-0.710 on the Raw dataset, were significantly higher with the use of SN at 0.784-0.854 (p < 0.001 for Raw versus SN), and higher still with SCN at 0.954-0.979 (p < 0.001 for SN versus SCN). Class activation maps of the SCN model visualized lesions contributing to the model's decision of progression. CONCLUSION: With preprocessing of spatial and count normalization, our deep learning model achieved excellent performance in classifying the therapeutic response of bone scans in patients with prostate cancer.

Effects of Androgen Treatment on Growth in Patients with 5-α-Reductase Type 2 Deficiency.

BACKGROUND: Patients with 5-α-reductase type 2 deficiency (5αRD2) require androgen treatment for the growth of normal male external genitalia. Since limited research has been conducted on the effects of androgen treatment on height in individuals with 5αRD2, we investigated the effect of androgen treatment on bone age (BA) and the height status in children with 5αRD2. METHODS: Of the 19 participants who were followed up for an average of 10.6 years, 12 received androgen treatment. BA and height standard deviation scores (SDS) were compared between the treatment and non-treatment groups, as well as between the dihydrotestosterone (DHT) and testosterone enanthate (TE) treatment groups. RESULTS: Despite the above-average height of the 19 patients with 5αRD2, the height SDS relative to BA (htSDS-BA) was below average, particularly in the androgen treatment group. DHT treatment did not lead to an increase in BA or htSDS-BA, whereas TE treatment resulted in BA advancement and decreased htSDS-BA, especially in the prepubertal period. CONCLUSIONS: DHT treatment is more favorable for height than TE treatment in patients with 5αRD2, particularly during the prepubertal period. Therefore, age and the type of androgen used should be carefully considered to minimize the risk of height reduction in these patient groups.

Associations of cardiovascular and diabetes-related risk factors with myocardial perfusion reserve assessed by 201Tl/99mTc-tetrofosmin single-photon emission computed tomography in patients with diabetes mellitus and stable coronary artery disease.

We aimed to examine the associations of cardiovascular risk factors with myocardial perfusion reserve (MPR) in patients with type 2 diabetes and stable coronary artery disease. The study patients were retrospectively identified from a database of patients with diabetes and stable coronary artery disease at Asan Medical Center (Seoul, Republic of Korea), covering the period from 2017 to 2019. The primary outcome variable was MPR assessed by dynamic stress 201Tl/rest 99mTc-tetrofosmin SPECT. Univariable and stepwise multivariable analyses were performed to assess the associations of cardiovascular risk factors with MPR. A total of 276 patients (236 men and 40 women) were included. The median global MPR was 2.4 (interquartile range 1.9-3.0). Seventy-five (27.2%) patients had an MPR < 2.0. Multivariable linear regression showed that smoking (ß = - 0.44, 95% confidence interval - 0.68 to - 0.21, P < 0.001), hypertension (ß = - 0.24, 95% confidence interval - 0.47 to - 0.02, P = 0.033), and summed difference score (ß = - 0.05, 95% confidence interval - 0.07 to - 0.03, P < 0.001) were independently associated with MPR. Abnormal MPR (< 2.0) was associated with a higher incidence of cardiac death or myocardial infarction (P = 0.034). MPR assessed by dynamic stress 201Tl/rest 99mTc-tetrofosmin SPECT was impaired in a large cohort of patients with diabetes. After adjusting for risk variables, including standard myocardial perfusion imaging characteristics, smoking, and hypertension were associated with MPR. Our results may aid in identifying patients with impaired MPR and stratifying patients with type 2 diabetes.

The Genotype-Phenotype Correlation in Human 5α-Reductase Type 2 Deficiency: Classified and Analyzed from a SRD5A2 Structural Perspective.

The phenotype of the 5α-reductase type 2 deficiency (5αRD2) by the SRD5A2 gene mutation varies, and although there have been many attempts, the genotype-phenotype correlation still has not yet been adequately evaluated. Recently, the crystal structure of the 5α-reductase type 2 isozyme (SRD5A2) has been determined. Therefore, the present study retrospectively evaluated the genotype-phenotype correlation from a structural perspective in 19 Korean patients with 5αRD2. Additionally, variants were classified according to structural categories, and phenotypic severity was compared with previously published data. The p.R227Q variant, which belongs to the NADPH-binding residue mutation category, exhibited a more masculine phenotype (higher external masculinization score) than other variants. Furthermore, compound heterozygous mutations with p.R227Q mitigated phenotypic severity. Similarly, other mutations in this category showed mild to moderate phenotypes. Conversely, the variants categorized as structure-destabilizing and small to bulky residue mutations showed moderate to severe phenotypes, and those categorized as catalytic site and helix-breaking mutations exhibited severe phenotypes. Therefore, the SRD5A2 structural approach suggested that a genotype-phenotype correlation does exist in 5αRD2. Furthermore, the categorization of SRD5A2 gene variants according to the SRD5A2 structure facilitates the prediction of the severity of 5αRD2 and the management and genetic counseling of patients affected by it.

The Impact of Prior Antithrombotic Use on Blood Viscosity in Cardioembolic Stroke with Non-Valvular Atrial Fibrillation.

Although clinical studies have demonstrated that prior use of antiplatelets was associated with decreased blood viscosity (BV) in patients with acute ischemic stroke, the impact of previous anticoagulant use on blood viscosity in cardioembolic stroke with non-valvular AF (NVAF) has not yet been clearly studied. This single-center retrospective observational study aimed to determine the impact of prior antithrombotic (antiplatelet and anticoagulant) use on BV in patients with cardioembolic stroke (CES) due to NVAF. Patients with CES and NVAF were analyzed with the following inclusion criteria: (1) patients over 20 years of age admitted within five days of stroke onset; (2) ischemic stroke presumably due to an NVAF-derived embolus; (3) compatible cortical/subcortical lesion on brain computed tomography or magnetic resonance imaging; (4) hemoglobin level of 10-18 mg/dL; and (5) receiving antiplatelets within five days or anticoagulants within two days if previously medicated. From the screening of 195 patients (22% of the total stroke population during the study period) who had experienced ischemic stroke with AF, 160 were included for the final analysis. Eighty-nine patients (56%) were taking antithrombotics (antiplatelet, 57%; warfarin, 13%; NOACs, 30%) regularly. Compared to patients without previous antithrombotic use, those with previous antithrombotic use (antiplatelets, warfarin, and NOACs) were significantly associated with decreased systolic BV (SBV) and diastolic BV (DBV) (p < 0.036). In multiple linear regression analysis, hematocrit (Hct) level and prior antithrombotic use were significantly associated with decreased SBV and DBV. Hct was positively correlated with increased SBV and DBV. In Hct-adjusted partial correlation analysis, prior uses of any antithrombotic agents were associated with decreased SBV (r < -0.270, p < 0.015) and DBV (r < -0.183, p < 0.044). In conclusion, this study showed that prior antithrombotic use (antiplatelets, VKAs, and NOACs) was associated with decreased SBV and DBV in patients presenting with acute CES secondary to NVAF. Our results indicated that previous use of NOACs may be a useful hemorheological parameter in patients with acute CES due to NVAF. Accumulation of clinical data from a large number of patients with the risk of stroke occurrence, initial stroke severity, and functional outcome is necessary to assess the usefulness of BV.

Prognostic significance of pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography in patients with T2N1 hormone receptor-positive, ERBB2-negative breast cancer who underwent adjuvant chemotherapy.

PURPOSE: To determine whether tumor uptake of 18F-fluorodeoxyglucose (18F-FDG) is associated with invasive disease-free survival (IDFS) in patients with hormone receptor (HR)-positive ERBB2-negative early-stage breast cancer treated with adjuvant chemotherapy. METHODS: This is a single-center cohort study of women with breast cancer who underwent surgery between 2008 and 2015 at Asan Medical Center, Seoul, Korea. Patients were enrolled if they were diagnosed with HR-positive ERBB2-negative breast cancer with histology of invasive ductal carcinoma, had an American Joint Committee on Cancer pathologic tumor stage of T2N1 with 1-3 positive axillary nodes, underwent preoperative 18F-FDG positron emission tomography/computed tomography (PET/CT), and underwent breast cancer surgery followed by anthracycline- or taxane-based adjuvant chemotherapy. The primary outcome measure was IDFS. The maximum standardized uptake value (SUVmax) was dichotomized using a predefined cut-off of 4.14. RESULTS: A total of 129 patients were included. The median follow-up period for IDFS in those without recurrence was 82 months (interquartile range, 65-106). Multivariable Cox analysis showed that SUVmax was independently associated with IDFS [adjusted hazard ratio 2.49; 95% confidence interval (CI), 1.06-5.84]. Ten-year IDFS estimates via the Kaplan-Meier method were 0.60 (95% CI, 0.42-0.74) and 0.82 (95% CI, 0.65-0.91) for high and low SUVmax groups, respectively. The overall association between SUVmax and IDFS appeared to be consistent across subgroups divided according to age, progesterone receptor status, histologic grade, or presence of lymphovascular invasion. CONCLUSION: High SUVmax on preoperative 18F-FDG PET/CT was independently associated with reduced long-term IDFS in T2N1 HR-positive ERBB2-negative breast cancer patients who underwent adjuvant chemotherapy.

FDG metabolic parameter-based models for predicting recurrence after upfront surgery in synchronous colorectal cancer liver metastasis.

OBJECTIVE: This study aimed to develop and validate post- and preoperative models for predicting recurrence after curative-intent surgery using an FDG PET-CT metabolic parameter to improve the prognosis of patients with synchronous colorectal cancer liver metastasis (SCLM). METHODS: In this retrospective multicenter study, consecutive patients with resectable SCLM underwent upfront surgery between 2006 and 2015 (development cohort) and between 2006 and 2017 (validation cohort). In the development cohort, we developed and internally validated the post- and preoperative models using multivariable Cox regression with an FDG metabolic parameter (metastasis-to-primary-tumor uptake ratio [M/P ratio]) and clinicopathological variables as predictors. In the validation cohort, the models were externally validated for discrimination, calibration, and clinical usefulness. Model performance was compared with that of Fong's clinical risk score (FCRS). RESULTS: A total of 374 patients (59.1 ± 10.5 years, 254 men) belonged in the development cohort and 151 (60.3 ± 12.0 years, 94 men) in the validation cohort. The M/P ratio and nine clinicopathological predictors were included in the models. Both postoperative and preoperative models showed significantly higher discrimination than FCRS (p < .05) in the external validation (time-dependent AUC = 0.76 [95% CI 0.68-0.84] and 0.76 [0.68-0.84] vs. 0.65 [0.57-0.74], respectively). Calibration plots and decision curve analysis demonstrated that both models were well calibrated and clinically useful. The developed models are presented as a web-based calculator ( https://cpmodel.shinyapps.io/SCLM/ ) and nomograms. CONCLUSIONS: FDG metabolic parameter-based prognostic models are well-calibrated recurrence prediction models with good discriminative power. They can be used for accurate risk stratification in patients with SCLM. KEY POINTS: • In this multicenter study, we developed and validated prediction models for recurrence in patients with resectable synchronous colorectal cancer liver metastasis using a metabolic parameter from FDG PET-CT. • The developed models showed good predictive performance on external validation, significantly exceeding that of a pre-existing model. • The models may be utilized for accurate patient risk stratification, thereby aiding in therapeutic decision-making.

Association of Serum Liver Enzymes with Brain Amyloidopathy and Cognitive Performance.

Background: Alzheimer's disease (AD) is characterized by amyloid-ß (Aß) plaque accumulation and neurofibrillary tangles in the brain. Emerging evidence has suggested potential interactions between the brain and periphery, particularly the liver, in regulating Aß homeostasis. Objective: This study aimed to investigate the association of serum liver enzymes with brain amyloidopathy and cognitive performance in patients with complaints of cognitive decline. Methods: A total of 1,036 patients (mean age 74 years, 66.2% female) with subjective cognitive decline, mild cognitive impairment, AD dementia, and other neurodegenerative diseases were included using the Smart Clinical Data Warehouse. Amyloid positron emission tomography (PET) imaging, comprehensive neuropsychological evaluations, and measurements of liver enzymes, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, total bilirubin, and albumin, were assessed. After propensity score matching, logistic and linear regression analyses were used to investigate the associations between liver enzymes, amyloid status, and cognitive performance. Additionally, a machine learning approach was used to assess the classification performance of liver enzymes in predicting amyloid PET positivity. Results: Lower ALT levels and higher AST-to-ALT ratios were significantly associated with amyloid PET positivity and AD diagnosis. The AST-to-ALT ratio was also significantly associated with poor memory function. Machine learning analysis revealed that the classification performance of amyloid status (AUC = 0.642) for age, sex, and apolipoprotein E ɛ4 carrier status significantly improved by 6.2% by integrating the AST-to-ALT ratio. Conclusions: These findings highlight the potential association of liver function on AD and its potential as a diagnostic and therapeutic implications.

Prediction of amyloid PET positivity via machine learning algorithms trained with EDTA-based blood amyloid-ß oligomerization data.

BACKGROUND: The tendency of amyloid-ß to form oligomers in the blood as measured with Multimer Detection System-Oligomeric Amyloid-ß (MDS-OAß) is a valuable biomarker for Alzheimer's disease and has been verified with heparin-based plasma. The objective of this study was to evaluate the performance of ethylenediaminetetraacetic acid (EDTA)-based MDS-OAß and to develop machine learning algorithms to predict amyloid positron emission tomography (PET) positivity. METHODS: The performance of EDTA-based MDS-OAß in predicting PET positivity was evaluated in 312 individuals with various machine learning models. The models with various combinations of features (i.e., MDS-OAß level, age, apolipoprotein E4 alleles, and Mini-Mental Status Examination [MMSE] score) were tested 50 times on each dataset. RESULTS: The random forest model best-predicted amyloid PET positivity based on MDS-OAß combined with other features with an accuracy of 77.14 ± 4.21% and an F1 of 85.44 ± 3.10%. The order of significance of predictive features was MDS-OAß, MMSE, Age, and APOE. The Support Vector Machine using the MDS-OAß value only showed an accuracy of 71.09 ± 3.27% and F-1 value of 80.18 ± 2.70%. CONCLUSIONS: The Random Forest model using EDTA-based MDS-OAß combined with the MMSE and apolipoprotein E status can be used to prescreen for amyloid PET positivity.