• 한국ITS학회 논문지
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• 제23권2호
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• pp.1-14
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• 2024

지금까지의 최적경로탐색 알고리즘은 노드표지와 링크표지를 적용하는 방안이 소개되었다. 노드표지는 2개의 노드를 최적경로 탐색과정에서 동시에 고려한다. 링크표지는 2개의 링크를 탐색과정에서 동시에 고려한다. 본 연구는 2개의 회전을 탐색과정에서 동시에 고려하는 회전표지기반 최적경로탐색기법을 제안한다. 회전표지기반 최적경로탐색은 2개의 회전을 탐색과정에서 고려하기 때문에 Bellman(1957)의 최적원리에 근거한 동적프로그래밍의 최적해가 보장된다. 한편 회전표지기반 최적경로탐색은 링크표지의 극한 접근 개념을 동일하게 적용하기 때문에 링크표지를 적용하는 장점을 수용할 수 있다. 따라서 네트워크의 확장없이 노드는 복수의 방문이 허용되면서 링크는 방문이 허용되지 않는 합리적 순환통행을 반영하는 것이 가능하다. 특히 2개의 연속회전에서 나타나는 추가적인 비용구조를 반영하는 특성이 포함되어 통행비용함수의 구조를 보다 유연하게 표현하는 것이 가능하다. 교통카드 단말기로 구성된 수도권 도시철도 네트워크를 대상으로 시행된 사례연구는 연속된 보행환승이 나타나는 통행에 대한 심리적 저항감을 나타내는 파라메타를 Turn Label 최적경로탐색에 도입하여 연구의 현실적 확장성을 검토하였다. 연속회전에 대한 심리적 저항값이 커지면서 통행시간 및 거리가 늘어나도 연속된 환승을 우회하는 방안으로 시뮬레이션 결과가 도출되어 Turn Label의 비용구조를 반영하는 것이 확인되었다. 향후 도로교통망 및 대중교통망의 통행비용함수에 대해 다양성을 확보하기 위한 추가적인 연구의 진행이 필요하다.

• 대한임상검사과학회지
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• 제55권4호
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• pp.269-275
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• 2023

심장초음파검사는 폐동맥고혈압 진단에 유용한 비침습 방법으로 심장초음파 검사자의 교육상태, 지식수준, 경력에 따라 영향을 받는다. 이 연구의 목적은 폐동맥고혈압으로 진단받은 환자의 심장초음파 영상을 경력이 다른 검사자 간의 측정값 일치도를 비교하는 것이다. 2020년 1월 1일부터 2020년 12월 31일까지 S 병원에서 폐동맥고혈압으로 진단받고 심장초음파 검사를 받은 148명 환자의 심장초음파 영상을 심장초음파검사 경력이 다른 3명의 검사자가 재측정하였다. 각 검사자가 측정한 심장초음파 측정값을 분석한 결과, 이산변수 분석에서 검사자 간 일치도 평가는 검사자 3과 심장내과 전문의 그룹에서 모두 우수한 일치도를 보여 검사 경력이 많을수록 측정값 예측에 유리했다. 또한, 연속변수에서 모든 검사자는 구조적으로 복잡한 우심실의 측정값보다 내면이 단순하고 명확한 우심방의 측정값에서 좋은 일치도를 보였다. 본 연구는 국내 최초로 심장초음파를 시행하는 임상병리사 중 경력이 다른 임상병리사들이 심장초음파 영상을 재측정한 측정값의 일치도를 분석한 것이다.

• Korean Journal of Radiology
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• 제25권6호
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• pp.575-588
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• 2024

Objective: Differentiating intracranial aneurysms from normal variants using CT angiography (CTA) or MR angiography (MRA) poses significant challenges. This study aimed to evaluate the efficacy of proton-density MRA (PD-MRA) compared to high-resolution time-of-flight MRA (HR-MRA) in diagnosing aneurysms among patients with indeterminate findings on conventional CTA or MRA. Materials and Methods: In this retrospective analysis, we included patients who underwent both PD-MRA and HR-MRA from August 2020 to July 2022 to assess lesions deemed indeterminate on prior conventional CTA or MRA examinations. Three experienced neuroradiologists independently reviewed the lesions using HR-MRA and PD-MRA with reconstructed voxel sizes of 0.25³ mm³ or 0.2³ mm³, respectively. A neurointerventionist established the gold standard with digital subtraction angiography. We compared the performance of HR-MRA, PD-MRA (0.25³-mm³ voxel), and PD-MRA (0.2³-mm³ voxel) in diagnosing aneurysms, both per lesion and per patient. The Fleiss kappa statistic was used to calculate inter-reader agreement. Results: The study involved 109 patients (average age 57.4 ± 11.0 years; male:female ratio, 11:98) with 141 indeterminate lesions. Of these, 78 lesions (55.3%) in 69 patients were confirmed as aneurysms by the reference standard. PD-MRA (0.25³-mm³ voxel) exhibited significantly higher per-lesion diagnostic performance compared to HR-MRA across all three readers: sensitivity ranged from 87.2%-91.0% versus 66.7%-70.5%; specificity from 93.7%-96.8% versus 58.7%-68.3%; and accuracy from 90.8%-92.9% versus 63.8%-69.5% (P ≤ 0.003). Furthermore, PD-MRA (0.25³-mm³ voxel) demonstrated significantly superior per-patient specificity and accuracy compared to HR-MRA across all evaluators (P ≤ 0.013). The diagnostic accuracy of PD-MRA (0.2³-mm³ voxel) surpassed that of HR-MRA and was comparable to PD-MRA (0.25³-mm³ voxel). The kappa values for inter-reader agreements were significantly higher in PD-MRA (0.820-0.938) than in HR-MRA (0.447-0.510). Conclusion: PD-MRA outperformed HR-MRA in diagnostic accuracy and demonstrated almost perfect inter-reader consistency in identifying intracranial aneurysms among patients with lesions initially indeterminate on CTA or MRA.

• Korean Journal of Radiology
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• 제24권6호
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• pp.529-540
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• 2023

Objective: To compare the diagnostic performance and clinical outcomes of 2-mSv computed tomography (CT) and conventional-dose CT (CDCT), following radiology residents' interpretation of CT examinations for suspected appendicitis. Materials and Methods: Altogether, 3074 patients with suspected appendicitis aged 15-44 years (28 ± 9 years, 1672 females) from 20 hospitals were randomly assigned to the 2-mSv CT (n = 1535) or CDCT (n = 1539) groups in a pragmatic trial from December 2013 and August 2016. Overall, 107 radiology residents participated in the trial as readers in the form of daily practice after online training for 2-mSv CT. They made preliminary CT reports, which were later finalized by attending radiologists via addendum reports, for 640 and 657 patients in the 2-mSv CT and CDCT groups, respectively. We compared the diagnostic performance of the residents, discrepancies between preliminary and addendum reports, and clinical outcomes between the two groups. Results: Patient characteristics were similar between the 640 and 657 patients. Residents' diagnostic performance was not significantly different between the 2-mSv CT and CDCT groups, with a sensitivity of 96.0% and 97.1%, respectively (difference [95% confidence interval {CI}], -1.1% [-4.9%, 2.6%]; P = 0.69) and specificity of 93.2% and 93.1%, respectively (0.1% [-3.6%, 3.7%]; P > 0.99). The 2-mSv CT and CDCT groups did not significantly differ in discrepancies between the preliminary and addendum reports regarding the presence of appendicitis (3.3% vs. 5.2%; -1.9% [-4.2%, 0.4%]; P = 0.12) and alternative diagnosis (5.5% vs. 6.4%; -0.9% [-3.6%, 1.8%]; P = 0.56). The rates of perforated appendicitis (12.0% vs. 12.6%; -0.6% [-4.3%, 3.1%]; P = 0.81) and negative appendectomies (1.9% vs. 1.1%; 0.8% [-0.7%, 2.3%]; P = 0.33) were not significantly different between the two groups. Conclusion: Diagnostic performance and clinical outcomes were not significantly different between the 2-mSv CT and CDCT groups following radiology residents' CT readings for suspected appendicitis.

• Korean Journal of Radiology
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• 제24권6호
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• pp.541-552
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• 2023

Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using supine and erect abdominal radiography. Materials and Methods: A model that can utilize "pneumoperitoneum" and "non-pneumoperitoneum" classes was developed through knowledge distillation. To train the proposed model with limited training data and weak labels, it was trained using a recently proposed semi-supervised learning method called distillation for self-supervised and self-train learning (DISTL), which leverages the Vision Transformer. The proposed model was first pre-trained with chest radiographs to utilize common knowledge between modalities, fine-tuned, and self-trained on labeled and unlabeled abdominal radiographs. The proposed model was trained using data from supine and erect abdominal radiographs. In total, 191212 chest radiographs (CheXpert data) were used for pre-training, and 5518 labeled and 16671 unlabeled abdominal radiographs were used for fine-tuning and self-supervised learning, respectively. The proposed model was internally validated on 389 abdominal radiographs and externally validated on 475 and 798 abdominal radiographs from the two institutions. We evaluated the performance in diagnosing pneumoperitoneum using the area under the receiver operating characteristic curve (AUC) and compared it with that of radiologists. Results: In the internal validation, the proposed model had an AUC, sensitivity, and specificity of 0.881, 85.4%, and 73.3% and 0.968, 91.1, and 95.0 for supine and erect positions, respectively. In the external validation at the two institutions, the AUCs were 0.835 and 0.852 for the supine position and 0.909 and 0.944 for the erect position. In the reader study, the readers' performances improved with the assistance of the proposed model. Conclusion: The proposed model trained with the DISTL method can accurately detect pneumoperitoneum on abdominal radiography in both the supine and erect positions.

• Korean Journal of Radiology
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• 제25권1호
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

• Korean Journal of Radiology
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• 제23권2호
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• pp.256-263
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• 2022

Objective: This study aimed to evaluate the image quality and dose reduction of low-dose three-dimensional (3D) rotational angiography (RA) for evaluating intracranial aneurysms. Materials and Methods: We retrospectively evaluated the clinical data and 3D RA datasets obtained from 146 prospectively registered patients (male:female, 46:100; median age, 58 years; range, 19-81 years). The subjective image quality of 79 examinations obtained from a conventional method and 67 examinations obtained from a low-dose (5-seconds and 0.10-μGy/frame) method was assessed by two neurointerventionists using a 3-point scale for four evaluation criteria. The total image quality score was then obtained as the average of the four scores. The image quality scores were compared between the two methods using a noninferiority statistical testing, with a margin of -0.2 (i.e., score of low-dose group - score of conventional group). For the evaluation of dose reduction, dose-area product (DAP) and air kerma (AK) were analyzed and compared between the two groups. Results: The mean total image quality score ± standard deviation of the 3D RA was 2.97 ± 0.17 by reader 1 and 2.95 ± 0.20 by reader 2 for conventional group and 2.92 ± 0.30 and 2.95 ± 0.22, respectively, for low-dose group. The image quality of the 3D RA in the low-dose group was not inferior to that of the conventional group according to the total image quality score as well as individual scores for the four criteria in both readers. The mean DAP and AK per rotation were 5.87 Gy-cm² and 0.56 Gy, respectively, in the conventional group, and 1.32 Gy-cm² (p < 0.001) and 0.17 Gy (p < 0.001), respectively, in the low-dose group. Conclusion: Low-dose 3D RA was not inferior in image quality and reduced the radiation dose by 70%-77% compared to the conventional 3D RA in evaluating intracranial aneurysms.

• Korean Journal of Radiology
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• 제20권4호
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• pp.671-682
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• 2019

Objective: To investigate whether computed tomography (CT) and fluorine-18-labeled fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) may be applied to distinguish thymic epithelial tumors (TETs) from benign cysts in the anterior mediastinum. Materials and Methods: We included 262 consecutive patients with pathologically proven TETs and benign cysts 5 cm or smaller who underwent preoperative CT scans. In addition to conventional morphological and ancillary CT findings, the relationship between the lesion and the adjacent mediastinal pleura was evaluated qualitatively and quantitatively. Mean lesion attenuation was measured on CT images. The maximum standardized uptake value (SUVmax) was obtained with FDG-PET scans in 40 patients. CT predictors for TETs were identified with multivariate logistic regression analysis. For validation, we assessed the diagnostic accuracy and inter-observer agreement between four radiologists in a size-matched set of 24 cysts and 24 TETs using a receiver operating characteristic curve before and after being informed of the study findings. Results: The multivariate analysis showed that post-contrast attenuation of 60 Hounsfield unit or higher (odds ratio [OR], 12.734; 95% confidence interval [CI], 2.506-64.705; p = 0.002) and the presence of protrusion from the mediastinal pleura (OR, 9.855; 95% CI, 1.749-55.535; p = 0.009) were the strongest CT predictors for TETs. SUVmax was significantly higher in TETs than in cysts (5.3 ± 2.4 vs. 1.1 ± 0.3; p < 0.001). After being informed of the study findings, the readers' area under the curve improved from 0.872-0.955 to 0.949-0.999 (p = 0.066-0.149). Inter-observer kappa values for protrusion were 0.630-0.941. Conclusion: Post-contrast CT attenuation, protrusion from the mediastinal pleura, and SUVmax were useful imaging features for distinguishing TETs from cysts in the anterior mediastinum.

• Korean Journal of Radiology
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• 제21권10호
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• Journal of Cardiovascular Imaging
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• 제31권1호
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• pp.18-23
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• 2023

BACKGROUND: Three-dimensional (3D) transesophageal echocardiogram (TEE) is the gold standard for the diagnosis of degenerative mitral regurgitation (dMR) and preoperative planning for transcatheter mitral valve repair (TMVr). TEE is an invasive modality requiring anesthesia and esophageal intubation. The severe acute respiratory syndrome coronavirus 2 pandemic has limited the number of elective invasive procedures. Multi-detector computed tomographic angiography (MDCT) provides high-resolution images and 3D reconstructions to assess complex mitral anatomy. We hypothesized that MDCT would reveal similar information to TEE relevant to TMVr, thus deferring the need for a preoperative TEE in certain situations like during a pandemic. METHODS: We retrospectively analyzed data on patients who underwent or were evaluated for TMVr for dMR with preoperative MDCT and TEE between 2017 and 2019. Two TEE and 2 MDCT readers, blinded to patient outcome, analyzed: leaflet pathology (flail, degenerative, mixed), leaflet location, mitral valve area (MVA), flail width/gap, anterior-posterior (AP) and commissural diameters, posterior leaflet length, leaflet thickness, presence of mitral valve cleft and degree of mitral annular calcification (MAC). RESULTS: A total of 22 (out of 87) patients had preoperative MDCT. MDCT correctly identified the leaflet pathology in 77% (17/22), flail leaflet in 91% (10/11), MAC degree in 91% (10/11) and the dysfunctional leaflet location in 95% (21/22) of patients. There were no differences in the measurements for MVA, flail width, commissural or AP diameter, posterior leaflet length, and leaflet thickness. MDCT overestimated the measurements of flail gap. CONCLUSIONS: For preoperative TMVr planning, MDCT provided similar measurements to TEE in our study.