Basal cell adenocarcinoma, considered to be the malignant counterpart of basal cell adenoma, is a rare, low-grade malignant tumor of the salivary glands, accounting for 1-2% of salivary gland malignancies. It predominantly affects the parotid gland, while involvement of the minor salivary glands is exceptionally rare. This report presented a case of basal cell adenocarcinoma involving the left retromolar trigone in a 54-year-old woman. The initial provisional diagnosis suggested a benign or low-grade malignant salivary tumor. Advanced magnetic resonance imagingtechniques, including diffusion-weighted imaging and apparent diffusion coefficient analysis, aided in the preoperative prediction of malignancy, and an incisional biopsy confirmed the diagnosis of basal cell adenocarcinoma. This caseunderscored the challenge of distinguishing basal cell adenocarcinoma from benign salivary tumors, as clinical and imaging features often overlap. Surgical excision remains the primary treatment, yielding favorable outcomes;however, long-term follow-up is crucial due to the risk of recurrence.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Background/Aims: Multiple myeloma (MM) predominantly affects elderly individuals, but studies on older patients with MM are limited. The clinical characteristics and survival outcomes of patients with MM aged 80 years or over were retrospectively analyzed. Methods: This retrospective multicenter study was conducted to investigate the clinical characteristics, treatment patterns, and survival outcomes of patients aged 80 years or over who were newly diagnosed with MM at five academic hospitals in Daegu, Korea, between 2010 and 2019. Results: A total of 127 patients with a median age of 83 years (range, 80–93 yr) were enrolled: 52 (40.9%) with Eastern Cooperative Oncology Group Performance Status (ECOG PS) > 2, 84 (66.1%) with International Staging System (ISS) stage III disease, and 93 (73.2%) with a Charlson comorbidity index (CCI) > 4. Chemotherapy was administered to 86 patients (67.7%). The median overall survival was 9.3 months. Overall survival was significantly associated with ECOG PS > 2 (HR 2.26, 95% CI 1.43–3.59), ISS stage III (HR 1.99, 95% CI 1.18–3.34), and chemotherapy (HR 0.34, 95% CI 0.21–0.55). There was no statistically significant difference in event-free survival according to the type of anti-myeloma chemotherapy administered. The early mortality (EM) rate was 28.3%. Conclusions Even in patients with MM aged 80 years or over, chemotherapy can result in better survival outcomes than supportive care. Patients aged ≥ 80 years should not be excluded from chemotherapy based on age alone. However, reducing EM in elderly patients with newly diagnosed MM remains challenging.

Purpose: Recent development in perioperative treatment of resectable non–small cell lung cancer (NSCLC) have changed the landscape of early lung cancer management. The ADAURA trial has demonstrated the efficacy of adjuvant osimertinib treatment in resectable NSCLC patients; however, studies are required to show which subgroup of patients are at a high risk of relapse and require adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor treatment. This study evaluated risk factors for postoperative relapse among patients who underwent complete resection. Materials and Methods: Data were obtained from the Korean Association for Lung Cancer Registry (KALC-R), a database created using a retrospective sampling survey by the Korean Central Cancer Registry (KCCR) and the Lung Cancer Registration Committee. Results: A total of 3,176 patients who underwent curative resection was evaluated. The mean observation time was approximately 35.4 months. Among stage I to IIIA NSCLC patients, the EGFR-mutant subgroup included 867 patients, and 75.2%, 11.2%, and 11.8% were classified as stage I, stage II, and stage III, respectively. Within the EGFR-mutant subgroup, 44 (5.1%) and 121 (14.0%) patients showed early and late recurrence, respectively. Multivariate analysis on association with postoperative relapse among the EGFR-mutant subgroup showed that age, pathologic N and TNM stages, pleural invasion status, and surgery type were independent significant factors. Conclusion Among the population that underwent complete resection for early NSCLC with EGFR mutation, patients with advanced stage, pleural invasion, or limited resection are more likely to show postoperative relapse.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Background/Aims: Multiple myeloma (MM) predominantly affects elderly individuals, but studies on older patients with MM are limited. The clinical characteristics and survival outcomes of patients with MM aged 80 years or over were retrospectively analyzed. Methods: This retrospective multicenter study was conducted to investigate the clinical characteristics, treatment patterns, and survival outcomes of patients aged 80 years or over who were newly diagnosed with MM at five academic hospitals in Daegu, Korea, between 2010 and 2019. Results: A total of 127 patients with a median age of 83 years (range, 80–93 yr) were enrolled: 52 (40.9%) with Eastern Cooperative Oncology Group Performance Status (ECOG PS) > 2, 84 (66.1%) with International Staging System (ISS) stage III disease, and 93 (73.2%) with a Charlson comorbidity index (CCI) > 4. Chemotherapy was administered to 86 patients (67.7%). The median overall survival was 9.3 months. Overall survival was significantly associated with ECOG PS > 2 (HR 2.26, 95% CI 1.43–3.59), ISS stage III (HR 1.99, 95% CI 1.18–3.34), and chemotherapy (HR 0.34, 95% CI 0.21–0.55). There was no statistically significant difference in event-free survival according to the type of anti-myeloma chemotherapy administered. The early mortality (EM) rate was 28.3%. Conclusions Even in patients with MM aged 80 years or over, chemotherapy can result in better survival outcomes than supportive care. Patients aged ≥ 80 years should not be excluded from chemotherapy based on age alone. However, reducing EM in elderly patients with newly diagnosed MM remains challenging.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Background/Aims: Multiple myeloma (MM) predominantly affects elderly individuals, but studies on older patients with MM are limited. The clinical characteristics and survival outcomes of patients with MM aged 80 years or over were retrospectively analyzed. Methods: This retrospective multicenter study was conducted to investigate the clinical characteristics, treatment patterns, and survival outcomes of patients aged 80 years or over who were newly diagnosed with MM at five academic hospitals in Daegu, Korea, between 2010 and 2019. Results: A total of 127 patients with a median age of 83 years (range, 80–93 yr) were enrolled: 52 (40.9%) with Eastern Cooperative Oncology Group Performance Status (ECOG PS) > 2, 84 (66.1%) with International Staging System (ISS) stage III disease, and 93 (73.2%) with a Charlson comorbidity index (CCI) > 4. Chemotherapy was administered to 86 patients (67.7%). The median overall survival was 9.3 months. Overall survival was significantly associated with ECOG PS > 2 (HR 2.26, 95% CI 1.43–3.59), ISS stage III (HR 1.99, 95% CI 1.18–3.34), and chemotherapy (HR 0.34, 95% CI 0.21–0.55). There was no statistically significant difference in event-free survival according to the type of anti-myeloma chemotherapy administered. The early mortality (EM) rate was 28.3%. Conclusions Even in patients with MM aged 80 years or over, chemotherapy can result in better survival outcomes than supportive care. Patients aged ≥ 80 years should not be excluded from chemotherapy based on age alone. However, reducing EM in elderly patients with newly diagnosed MM remains challenging.