Purpose: This study assessed the reproducibility and clinical value of the vascular index (VI), derived from superb microvascular imaging (SMI) using Doppler ultrasonography, for evaluating renal function in transplanted kidneys. Methods: This retrospective study included 63 renal transplant patients who underwent grayscale and Doppler ultrasonography with SMI from January 2022 to February 2023. The VI of the transplanted kidneys was measured using three methods (VI_box, VI_F1, VI_F2). The VI was compared across chronic kidney disease (CKD) groups categorized by estimated glomerular filtration rate (eGFR) and Kidney Disease: Improving Global Outcomes (KDIGO) CKD risk groups based on eGFR and albuminuria. The correlation between VI and renal function was evaluated. Univariate and multivariate linear regression analyses were used to identify predictors of eGFR. Results: Significant differences in VI were observed among CKD groups based on eGFR (VI_box, P=0.001; VI_F1, P<0.001; VI_F2, P<0.001) and KDIGO CKD groups based on eGFR and albuminuria (VI_box, P=0.039; VI_F1, P=0.001; VI_F2, P<0.001). VI_F1 and VI_F2 demonstrated moderate/high correlations with eGFR (r=0.627, P<0.001 and r=0.657, P<0.001, respectively) and serum creatinine (r=-0.626, P<0.001 and r=-0.649, P<0.001, respectively). VI_box moderately correlated with eGFR (r=0.445, P<0.001). Multivariate regression identified the urine albumincreatinine ratio (ACR) (adjusted odds ratio [aOR], 1.122; 95% confidence interval [CI], -0.007 to, 0.000; P=0.030) and VI_F2 (aOR, 1.114; 95% CI, 0.466 to 1.235; P<0.001) were independently associated with eGFR. Conclusion The VI measured by drawing a region of interest along the border of the transplanted kidney in SMI (VI_F2) is highly reproducible and correlates well with eGFR. Both VI_F2 and ACR independently predict eGFR.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Objective: We aimed to investigate the associations of the triglyceride-glucose index, which measures insulin resistance, and the incidence of Parkinson’s disease. Methods: Our study used the Health Screening Cohort database of the National Health Insurance Service of South Korea (2002–2019). We included 310,021 participants who had no previous history of Parkinson’s disease and for whom more than 3 triglyceride-glucose index measurements were available. A diagnosis of Parkinson’s disease was determined via the International Classification of Diseases Tenth edition (G20) with a specific reimbursement code for rare intractable diseases and a history of prescriptions for anti-Parkinsonism drugs. Results: During a median of 9.64 years (interquartile range 8.72–10.53), 4,587 individuals (1.5%) had Parkinson’s disease. Based on a multivariable time-dependent Cox proportional hazards model, a per-unit increase in triglyceride-glucose index score was associated with a significantly increased risk of Parkinson’s disease (hazard ratio [HR]: 1.062; 95% confidence interval [CI] 1.007–1.119). In a sensitivity analysis, the triglyceride-glucose index was associated with the incidence of Parkinson’s disease in a non–diabetes mellitus cohort (HR: 1.093; 95% CI 1.025–1.165), but not in the diabetes mellitus cohort (HR: 0.990; 95% CI 0.902–1.087). In a restricted cubic spline analysis, the association between the triglyceride-glucose index and the incidence risk of Parkinson’s disease showed a nonlinear increasing (J-shaped) trend. Conclusion Our study demonstrated that higher triglyceride-glucose index scores were associated with the incidence of Parkinson’s disease in the general population, particularly in a nondiabetic mellitus cohort.

Purpose: This study assessed the reproducibility and clinical value of the vascular index (VI), derived from superb microvascular imaging (SMI) using Doppler ultrasonography, for evaluating renal function in transplanted kidneys. Methods: This retrospective study included 63 renal transplant patients who underwent grayscale and Doppler ultrasonography with SMI from January 2022 to February 2023. The VI of the transplanted kidneys was measured using three methods (VI_box, VI_F1, VI_F2). The VI was compared across chronic kidney disease (CKD) groups categorized by estimated glomerular filtration rate (eGFR) and Kidney Disease: Improving Global Outcomes (KDIGO) CKD risk groups based on eGFR and albuminuria. The correlation between VI and renal function was evaluated. Univariate and multivariate linear regression analyses were used to identify predictors of eGFR. Results: Significant differences in VI were observed among CKD groups based on eGFR (VI_box, P=0.001; VI_F1, P<0.001; VI_F2, P<0.001) and KDIGO CKD groups based on eGFR and albuminuria (VI_box, P=0.039; VI_F1, P=0.001; VI_F2, P<0.001). VI_F1 and VI_F2 demonstrated moderate/high correlations with eGFR (r=0.627, P<0.001 and r=0.657, P<0.001, respectively) and serum creatinine (r=-0.626, P<0.001 and r=-0.649, P<0.001, respectively). VI_box moderately correlated with eGFR (r=0.445, P<0.001). Multivariate regression identified the urine albumincreatinine ratio (ACR) (adjusted odds ratio [aOR], 1.122; 95% confidence interval [CI], -0.007 to, 0.000; P=0.030) and VI_F2 (aOR, 1.114; 95% CI, 0.466 to 1.235; P<0.001) were independently associated with eGFR. Conclusion The VI measured by drawing a region of interest along the border of the transplanted kidney in SMI (VI_F2) is highly reproducible and correlates well with eGFR. Both VI_F2 and ACR independently predict eGFR.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Purpose: This study assessed the reproducibility and clinical value of the vascular index (VI), derived from superb microvascular imaging (SMI) using Doppler ultrasonography, for evaluating renal function in transplanted kidneys. Methods: This retrospective study included 63 renal transplant patients who underwent grayscale and Doppler ultrasonography with SMI from January 2022 to February 2023. The VI of the transplanted kidneys was measured using three methods (VI_box, VI_F1, VI_F2). The VI was compared across chronic kidney disease (CKD) groups categorized by estimated glomerular filtration rate (eGFR) and Kidney Disease: Improving Global Outcomes (KDIGO) CKD risk groups based on eGFR and albuminuria. The correlation between VI and renal function was evaluated. Univariate and multivariate linear regression analyses were used to identify predictors of eGFR. Results: Significant differences in VI were observed among CKD groups based on eGFR (VI_box, P=0.001; VI_F1, P<0.001; VI_F2, P<0.001) and KDIGO CKD groups based on eGFR and albuminuria (VI_box, P=0.039; VI_F1, P=0.001; VI_F2, P<0.001). VI_F1 and VI_F2 demonstrated moderate/high correlations with eGFR (r=0.627, P<0.001 and r=0.657, P<0.001, respectively) and serum creatinine (r=-0.626, P<0.001 and r=-0.649, P<0.001, respectively). VI_box moderately correlated with eGFR (r=0.445, P<0.001). Multivariate regression identified the urine albumincreatinine ratio (ACR) (adjusted odds ratio [aOR], 1.122; 95% confidence interval [CI], -0.007 to, 0.000; P=0.030) and VI_F2 (aOR, 1.114; 95% CI, 0.466 to 1.235; P<0.001) were independently associated with eGFR. Conclusion The VI measured by drawing a region of interest along the border of the transplanted kidney in SMI (VI_F2) is highly reproducible and correlates well with eGFR. Both VI_F2 and ACR independently predict eGFR.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Purpose: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT). Materials and Methods: This retrospective study included 273 patients (aged 63.9±13.2 years; 129 men) who underwent CACscoring CT. A DL-CAD system based on thin-section images was used for pulmonary nodule detection, and two independent junior readers reviewed the standard CAC-scoring CT scans with and without referencing DL-CAD results. A reference standard was established through the consensus of two experienced radiologists. Sensitivity, positive predictive value, and F1-score were assessed on a per-nodule and per-patient basis. The patients’ medical records were monitored until November 2023. Results: A total of 269 nodules were identified in 129 patients. With DL-CAD assistance, the readers’ sensitivity significantly improved (65% vs. 80% for reader 1; 82% vs. 86% for reader 2; all p<0.001), without a notable increase in the number of false-positives per case (0.11 vs. 0.13, p=0.078 for reader 1; 0.11 vs. 0.11, p>0.999 for reader 2). Per-patient analysis also enhanced sensitivity with DL-CAD assistance (73% vs. 84%, p<0.001 for reader 1; 89% vs. 91%, p=0.250 for reader 2). During follow-up, lung cancer was diagnosed in four patients (1.5%). Among them, two had lesions detected on CAC-scoring CT, both of which were successfully identified by DL-CAD. Conclusion DL-CAD based on thin-section images can assist less experienced readers in detecting pulmonary nodules on CACscoring CT scans, improving detection sensitivity without significantly increasing false-positives.

Background: Circulating tumor DNA (ctDNA) profiling from peripheral blood allows relatively noninvasive monitoring of solid tumors; however, its utility post-surgery or chemotherapy in colorectal cancer remains underexplored. We evaluated the clinical implications of a ctDNA next-generation sequencing (NGS) panel post-surgery or chemotherapy in patients with colorectal cancer. Methods: We collected samples from 23 patients with colorectal cancer (17 men, median age 65 yrs) at baseline and post-surgery or chemotherapy at the National Cancer Center, Korea, between January 2021 and September 2023. ctDNA was analyzed using an NGS panel including 46 genes, and variant allele frequencies (VAFs) were determined. Followup samples were analyzed using the NGS panel or droplet digital PCR (ddPCR) when probes were available. Clinical status was compared with ctDNA results, and survival was analyzed using a time-dependent Cox model. Results: Mutations were identified in 13 out of 14 patients (92.8%) with stage II/III cancer and in all nine patients (100%) with stage IV cancer. Mutations were detected in KRAS (N = 15, 65%), APC (N = 8, 35%), TP53 (N = 7, 30%), PIK3CA (N = 5, 22%), and RET (N = 4, 17%). A 1% increase in KRAS and TP53 VAFs was associated with 48% and 32% increased mortality risk, respectively. Changes in VAF correlated well with clinical findings. Conclusions The detection of and an increase in KRAS and TP53 VAFs were associated with poor prognosis. ddPCR-based ctDNA monitoring results were comparable to those obtained with the NGS panel. ctDNA monitoring during treatment is clinically informative in managing colorectal cancer.

Background: Genetic alterations play a pivotal role in multiple myeloma (MM) development and therapeutic resistance. Traditionally, the genetic profiling of MM requires invasive bone marrow (BM) procedures; however, these procedures are associated with patient discomfort and cannot fully capture the spatial and temporal heterogeneity of the disease.Therefore, we investigated the clinical implications of liquid biopsy using targeted deep sequencing. Methods: We analyzed the genetic profiles of circulating tumor DNA (ctDNA) by targeted deep sequencing from 102 patients, including those with monoclonal gammopathy of undetermined significance (MGUS, N = 7), smoldering MM (N = 6), and symptomatic MM (N = 89). Results: The number of ctDNA mutations increased with disease progression from MGUS to MM, with averages of 1.0 mutations in MGUS, 1.8 mutations in smoldering MM, and 1.9 mutations in MM, respectively. Shared mutations between BM and ctDNA were more prevalent in MM (68.9%) than in MGUS (25.0%). RAS/RAF and TP53 mutations were significantly enriched in MM ctDNA. Specific mutations were associated with clinical features in patients with MM: hypercalcemia and TET2 (P = 0.006), renal insufficiency and NRAS (P = 0.012), paramedullary myeloma and TP53(P = 0.02), and extramedullary myeloma and NRAS (P = 0.007). TET2 mutations significantly affected 2-yr progression-free survival (hazard ratio = 7.11, P = 0.003). Serial ctDNA profiling accurately predicted treatment response in patients with MM. Conclusions Our findings highlight the potential of liquid biopsy for understanding MM progression and prognosis utilizing a minimally invasive approach, paving the way for its integration into personalized treatment strategies and real-time disease monitoring.