• Journal of the Korean Society of Radiology
• /
• v.83 no.2
• /
• pp.344-359
• /
• 2022

Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

• Journal of the Korean Society of Radiology
• /
• v.83 no.2
• /
• pp.331-343
• /
• 2022

Purpose To systematically compare the performance of liver imaging reporting and data system treatment response (LR-TR) with the modified Response Evaluation Criteria in Solid Tumors (mRECIST) for diagnosing viable hepatocellular carcinoma (HCC) treated with locoregional therapy (LRT). Materials and Methods Original studies of intra-individual comparisons between the diagnostic performance of LR-TR and mRECIST using dynamic contrast-enhanced CT or MRI were searched in MEDLINE and EMBASE, up to August 25, 2021. The reference standard for tumor viability was surgical pathology. The meta-analytic pooled sensitivity and specificity of the viable category using each criterion were calculated using a bivariate random-effects model and compared using bivariate meta-regression. Results For five eligible studies (430 patients with 631 treated observations), the pooled per-lesion sensitivities and specificities were 58% (95% confidence interval [CI], 45%-70%) and 93% (95% CI, 88%-96%) for the LR-TR viable category and 56% (95% CI, 42%-69%) and 86% (95% CI, 72%-94%) for the mRECIST viable category, respectively. The LR-TR viable category provided significantly higher pooled specificity (p < 0.01) than the mRECIST but comparable pooled sensitivity (p = 0.53). Conclusion The LR-TR algorithm demonstrated better specificity than mRECIST, without a significant difference in sensitivity for the diagnosis of pathologically viable HCC after LRT.

• Journal of the Korean Society of Radiology
• /
• v.82 no.3
• /
• pp.670-681
• /
• 2021

Purpose This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference. Materials and Methods Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference. Results At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU. Conclusion For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

• Journal of the Korean Society of Radiology
• /
• v.83 no.6
• /
• pp.1342-1353
• /
• 2022

Purpose We compared the radiation dose and image quality between the 2nd generation and the 3rd generation dual-source single-energy (DSSE) and dual-source dual-energy (DSDE) CT of the abdomen. Materials and Methods We included patients undergoing follow-up abdominal CT after partial or radical nephrectomy in the first 10 months of 2019 (2nd generation DS CT) and the first 10 months of 2020 (3rd generation DS CT). We divided the 320 patients into 4 groups (A, 2nd generation DSSE CT; B, 2nd generation DSDE CT; C, 3rd generation DSSE CT; and D, 3rd generation DSDE CT) (n = 80 each) matched by sex and body mass index. Radiation dose and image quality (objective and subjective qualities) were compared between the groups. Results The mean size-specific dose estimation of 3rd generation DSDE CT group was significantly lower than that of the 2nd generation DSSE CT (42.5%, p = 0.013) and 2nd generation DSDE CT (46.9%, p = 0.015) groups. Interobserver agreement was excellent for the overall image quality (intraclass correlation coefficient [ICC]: 0.8867) and image artifacts (ICC: 0.9423). Conclusion Our results showed a considerable reduction in the radiation dose while maintaining high image quality with 3rd generation DSDE CT as compared to the 2nd generation DSDE CT and 2nd generation DSSE CT.

• Journal of the Korean Society of Radiology
• /
• v.81 no.4
• /
• pp.886-898
• /
• 2020

Purpose The purpose of our study was to evaluate digital breast tomosynthesis as a breast cancer screening modality for women with gynecologic cancer. Materials and Methods This retrospective study included patients with underlying gynecologic malignancies who underwent screening digital breast tomosynthesis for breast cancer. The cancer detection rate, recall rate, sensitivity, specificity, and positive predictive value (PPV) were calculated. PPV1 was defined as the percentage of all positive screening exams that have a tissue diagnosis of cancer within a year. PPV2 was defined as the percentage of all diagnostic exams (and Breast Imaging Reporting and Data System category 4, 5 from screening setting) with a recommendation for tissue diagnosis that have cancer within a year. PPV3 was defined as the percentage of all known biopsies actually performed that resulted in a tissue diagnosis of cancer within the year. For each case of screen-detected cancer, we analyzed the age, type of underlying gynecologic malignancy, breast density, imaging features, final Breast Imaging Reporting and Data System assessment, histologic type, T and N stages, molecular subtype, and Ki-67 index. Results Among 508 patients, 7 with breast cancer were identified after a positive result. The cancer detection rate was 13.8 per 1000 screening exams, and the recall rate was 17.9%. The sensitivity was 100%, and the specificity was 83.2%. The false negative rate was 0 per 1000 exams. The PPV1, PPV2, and PPV3 were 7.7, 31.8, and 31.8, respectively. Conclusion Digital breast tomosynthesis may be a promising breast cancer screening modality for women with gynecologic cancer, based on the high cancer detection rate, high sensitivity, high PPV, and high detection rate of early-stage cancer observed in our study.

• Journal of the Korean Society of Radiology
• /
• v.82 no.3
• /
• pp.654-669
• /
• 2021

Purpose To evaluate the accuracy of MRI in predicting the pathological complete response (pCR) and the residual tumor size of breast cancer after neoadjucant chemotherapy (NAC), and to determine the factors affecting the accuarcy. Materials and Methods Eighty-eight breast cancer patients who underwent surgery after NAC at our center between 2010 and 2017 were included in this study. pCR was defined as the absence of invasive cancer on pathological evaluation. The maximum diameter of the residual tumor on post-NAC MRI was compared with the tumor size of the surgical specimen measured pathologically. Statistical analysis was performed to elucidate the factors affecting pCR and the residual tumor size-discrepancy between the MRI and the pathological measurements. Results The pCR rate was 10%. The diagnostic accuracy of MRI and the area under the curve for predicting pCR were 90.91% and 0.8017, respectively. The residual tumor sizes obtained using MRI and pathological measurements showed a strong correlation (r = 0.9, p < 0.001), especially in patients with a single mass lesion (p = 0.047). The size discrepancy between MRI and the pathological measurements was significantly greater in patients with the luminal type (p = 0.023) and multifocal tumors/non-mass enhancement on pre-NAC MRI (p = 0.047). Conclusion MRI is an accurate tool for evaluating pCR and residual tumor size in breast cancer patients who receive NAC. Tumor subtype and initial MRI features affect the accuracy of MRI.

• Journal of the Korean Society of Radiology
• /
• v.81 no.2
• /
• pp.365-378
• /
• 2020

Purpose This study was performed to determine whether the T1 relaxation time of gadoxetic acid-enhanced liver MR imaging is useful for detecting and staging liver fibrosis in patients with chronic liver disease. Materials and Methods One hundred and three patients with suspected focal liver lesion underwent MR imaging and Fibroscan. Fibroscan was chosen as the reference standard for classifying liver fibrosis. T1 relaxation times were acquired before (preT1), 20 minutes after (postT1) contrast administration, and reduction rate of T1 relaxation time (rrT1) on transverse 3D VIBE (volumetric interpolated breath-hold examination) sequence using 3T MR imaging. The optimal cut-off values for the fibrosis staging were determined with ROC analysis. Results PreT1 and postT1 increased and rrT1 decreased constantly with increasing severity of liver fibrosis according to the METAVIR score (F0-F4). There were statistically significant differences between F2 and F3 in preT1 (F2, 836.0 ± 74.7 ms; F3, 888.6 ± 77.5 ms, p < 0.05) and between F3 and F4 in postT1 (F3, 309.0 ± 80.2 ms; F4, 406.6 ± 147.7 ms, p < 0.05) and rrT1 (F3, 65.4 ± 7.7%; F4, 57.3 ± 11.4%, p < 0.05). ROC analysis revealed that combination test (preT1 + postT1) was the best test for predicting liver fibrosis. Conclusion PreT1 and postT1 increased constantly with increasing severity of liver fibrosis. T1 mapping in gadoxetic acid-enhanced liver MR imaging could be a helpful complementary sequence to determine the liver fibrosis stage.

• Journal of the Korean Society of Radiology
• /
• v.82 no.5
• /
• pp.1196-1206
• /
• 2021

Purpose To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). Materials and Methods A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30-50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions. Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. Results The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. Conclusion The constructed standard dataset can be utilized for evaluating the machine-learning-based AI algorithm for CDSS.

• Journal of the Korean Society of Radiology
• /
• v.81 no.5
• /
• pp.1151-1163
• /
• 2020

Purpose This study aimed to evaluate changes of subprosthetic pannus on cardiac CT and determine its relationship to echocardiographic findings in patients with mechanical aortic valve replacement (AVR). Materials and Methods Between April 2011 and November 2017, 17 AVR patients (56.8 ± 8.9 years, 12% male) who showed pannus formation on CT and had undergone both follow-up CT and echocardiography were included. The mean interval from AVR to the date of pannus detection was 10.5 ± 7.1 years. In the initial and follow-up CT and echocardiography, the pannus extent and echocardiographic parameters were compared using paired t-tests. The relationship between the opening angle of the prosthetic valve and the pannus extent was evaluated using Pearson correlation analysis. Results The pannus extent was significantly increased on CT (p < 0.05). The peak velocity (3.9 ± 0.8 m/s vs. 4.2 ± 0.8 m/s, p = 0.03) and mean pressure gradient (36.4 ± 15.5 mm Hg vs. 42.1 ± 15.8 mm Hg, p = 0.03) were significantly increased. The mean opening angles of the mechanical aortic leaflets were slightly decreased, but there was no statistical significance (73.1 ± 8.3° vs. 69.4 ± 12.1°, p = 0.12). The opening angle of the prosthetic leaflets was inversely correlated with the pannus extent (r = -0.57, p < 0.001). Conclusion The pannus extent increases over time, increasing transvalvular peak velocity and the pressure gradient. CT can be used to evaluate the pannus extent associated with hemodynamic changes that need to be managed by surgical intervention.

• Journal of the Korean Society of Radiology
• /
• v.81 no.2
• /
• pp.395-408
• /
• 2020

Purpose To evaluate the value of clinicopathologic factors and imaging features of primary breast cancer in predicting early recurrence after the primary treatment. Materials and Methods We enrolled 480 patients who had been followed-up after breast-conserving surgery and adjuvant therapy from January 2010 to December 2014 at our hospital. Early recurrence was defined as recurrence within 3 years after completion of primary treatment, and univariate and multivariate logistic regression analyses were performed to determine the clinicopathologic and imaging predictive factors of early recurrence. Results In the univariate analysis, among the clinicopathologic factors, advanced stage (p = 0.021), high histologic grade (p < 0.001), estrogen receptor negative (p = 0.002), high Ki-67 proliferation index (p = 0.017), and triple-negative breast cancer (p = 0.019), and among the imaging features, multifocality (p < 0.001), vessels in the rim on Doppler ultrasonography (US) (p = 0.012), and rim enhancement (p < 0.001) on magnetic resonance imaging of the breast were significantly associated with early recurrence. In the multivariate analysis, advanced stage [odds ratio (OR) = 3.47; 95% confidence interval (CI) 1.12-10.73; p = 0.031] and vessels in the rim on Doppler US (OR = 3.32; 95% CI 1.38-8.02; p = 0.008) were the independent predictive factors of early recurrence. Conclusion Vascular findings in the rim of the primary breast cancer on Doppler US before treatment is a radiologic independent predictive factor of early recurrence after the primary treatment.