Background: and Purpose The Treat Stroke to Target (TST) was a randomized clinical trial involving French and Korean patients demonstrating that a lower low-density lipoprotein cholesterol (LDL-C, <70 mg/dL) target group (LT) experienced fewer cerebro-cardiovascular events than a higher target (90–110 mg/dL) group (HT). However, whether these results can be applied to Asian patients with different ischemic stroke subtypes remains unclear. Methods: Patients from 14 South Korean centers were analyzed separately. Patients with ischemic stroke or transient ischemic attack with evidence of atherosclerosis were randomized into LT and HT groups. The primary endpoint was a composite of ischemic stroke, myocardial infarction, coronary or cerebral revascularization, and cardiovascular death. Results: Among 712 enrolled patients, the mean LDL-C level was 71.0 mg/dL in 357 LT patients and 86.1 mg/dL in 355 HT patients. The primary endpoint occurred in 24 (6.7%) of LT and in 31 (8.7%) of HT group patients (adjusted hazard ratio [HR]=0.78; 95% confidence interval [CI]=0.45–1.33, P=0.353). Cardiovascular events alone occurred significantly less frequently in the LT than in the HT group (HR 0.26, 95% CI 0.09–0.80, P=0.019), whereas there were no significant differences in ischemic stroke events (HR 1.12, 95% CI 0.60–2.10, P=0.712). The benefit of LT was less apparent in patients with small vessel disease and intracranial atherosclerosis than in those with extracranial atherosclerosis. Conclusion In contrast to the French TST, the outcomes in Korean patients were neutral. Although LT was more effective in preventing cardiovascular diseases, it was not so in stroke prevention, probably attributed to the differences in stroke subtypes. Further studies are needed to elucidate the efficacy of statins and appropriate LDL-C targets in Asian patients with stroke.

Purpose: There is few evidence regarding the optimal salvage treatment options for loco-reginal recurrence of esophageal cancer. This study aimed to evaluate the clinical outcomes of salvage radiotherapy (RT) in patients with loco-regional recurrence (LRR) after surgery for esophageal cancer. Materials and Methods: We retrospectively reviewed 147 esophageal cancer patients who received salvage RT for loco-regional recurrence between 1996 and December 2019. A total dose of 60 Gy in 20 fractions was used for RT alone and 60-70 Gy in 30-35 fractions for concurrent chemoradiotherapy (CCRT). Results: The patients’ median age was 65 years (range, 41 to 86 years). The median disease-free interval was 13.5 months (1.0 to 97.4 months). After a median 18.8 months follow-up, the 2-year overall survival (OS) and progression-free survival (PFS) rates were 38.1% and 25.9%, respectively. The median OS and PFS were 18.8 and 8.4 months, respectively. The CCRT could not improve OS compared to RT (p=0.336), but there was a trend of better PFS in the CCRT group. Regarding toxicities, the rate of grade 3 or higher toxicity was 10.9% occurring in 16 patients, and it was higher in patients who received CCRT than in the RT alone group (19.6% vs. 6.3%, p=0.023). Conclusion Salvage RT alone as well as CCRT could be effective in patients with locoregionally recurrent esophageal cancer.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Purpose: There is few evidence regarding the optimal salvage treatment options for loco-reginal recurrence of esophageal cancer. This study aimed to evaluate the clinical outcomes of salvage radiotherapy (RT) in patients with loco-regional recurrence (LRR) after surgery for esophageal cancer. Materials and Methods: We retrospectively reviewed 147 esophageal cancer patients who received salvage RT for loco-regional recurrence between 1996 and December 2019. A total dose of 60 Gy in 20 fractions was used for RT alone and 60-70 Gy in 30-35 fractions for concurrent chemoradiotherapy (CCRT). Results: The patients’ median age was 65 years (range, 41 to 86 years). The median disease-free interval was 13.5 months (1.0 to 97.4 months). After a median 18.8 months follow-up, the 2-year overall survival (OS) and progression-free survival (PFS) rates were 38.1% and 25.9%, respectively. The median OS and PFS were 18.8 and 8.4 months, respectively. The CCRT could not improve OS compared to RT (p=0.336), but there was a trend of better PFS in the CCRT group. Regarding toxicities, the rate of grade 3 or higher toxicity was 10.9% occurring in 16 patients, and it was higher in patients who received CCRT than in the RT alone group (19.6% vs. 6.3%, p=0.023). Conclusion Salvage RT alone as well as CCRT could be effective in patients with locoregionally recurrent esophageal cancer.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background: and Purpose The Treat Stroke to Target (TST) was a randomized clinical trial involving French and Korean patients demonstrating that a lower low-density lipoprotein cholesterol (LDL-C, <70 mg/dL) target group (LT) experienced fewer cerebro-cardiovascular events than a higher target (90–110 mg/dL) group (HT). However, whether these results can be applied to Asian patients with different ischemic stroke subtypes remains unclear. Methods: Patients from 14 South Korean centers were analyzed separately. Patients with ischemic stroke or transient ischemic attack with evidence of atherosclerosis were randomized into LT and HT groups. The primary endpoint was a composite of ischemic stroke, myocardial infarction, coronary or cerebral revascularization, and cardiovascular death. Results: Among 712 enrolled patients, the mean LDL-C level was 71.0 mg/dL in 357 LT patients and 86.1 mg/dL in 355 HT patients. The primary endpoint occurred in 24 (6.7%) of LT and in 31 (8.7%) of HT group patients (adjusted hazard ratio [HR]=0.78; 95% confidence interval [CI]=0.45–1.33, P=0.353). Cardiovascular events alone occurred significantly less frequently in the LT than in the HT group (HR 0.26, 95% CI 0.09–0.80, P=0.019), whereas there were no significant differences in ischemic stroke events (HR 1.12, 95% CI 0.60–2.10, P=0.712). The benefit of LT was less apparent in patients with small vessel disease and intracranial atherosclerosis than in those with extracranial atherosclerosis. Conclusion In contrast to the French TST, the outcomes in Korean patients were neutral. Although LT was more effective in preventing cardiovascular diseases, it was not so in stroke prevention, probably attributed to the differences in stroke subtypes. Further studies are needed to elucidate the efficacy of statins and appropriate LDL-C targets in Asian patients with stroke.

Purpose: There is few evidence regarding the optimal salvage treatment options for loco-reginal recurrence of esophageal cancer. This study aimed to evaluate the clinical outcomes of salvage radiotherapy (RT) in patients with loco-regional recurrence (LRR) after surgery for esophageal cancer. Materials and Methods: We retrospectively reviewed 147 esophageal cancer patients who received salvage RT for loco-regional recurrence between 1996 and December 2019. A total dose of 60 Gy in 20 fractions was used for RT alone and 60-70 Gy in 30-35 fractions for concurrent chemoradiotherapy (CCRT). Results: The patients’ median age was 65 years (range, 41 to 86 years). The median disease-free interval was 13.5 months (1.0 to 97.4 months). After a median 18.8 months follow-up, the 2-year overall survival (OS) and progression-free survival (PFS) rates were 38.1% and 25.9%, respectively. The median OS and PFS were 18.8 and 8.4 months, respectively. The CCRT could not improve OS compared to RT (p=0.336), but there was a trend of better PFS in the CCRT group. Regarding toxicities, the rate of grade 3 or higher toxicity was 10.9% occurring in 16 patients, and it was higher in patients who received CCRT than in the RT alone group (19.6% vs. 6.3%, p=0.023). Conclusion Salvage RT alone as well as CCRT could be effective in patients with locoregionally recurrent esophageal cancer.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background: and Purpose The Treat Stroke to Target (TST) was a randomized clinical trial involving French and Korean patients demonstrating that a lower low-density lipoprotein cholesterol (LDL-C, <70 mg/dL) target group (LT) experienced fewer cerebro-cardiovascular events than a higher target (90–110 mg/dL) group (HT). However, whether these results can be applied to Asian patients with different ischemic stroke subtypes remains unclear. Methods: Patients from 14 South Korean centers were analyzed separately. Patients with ischemic stroke or transient ischemic attack with evidence of atherosclerosis were randomized into LT and HT groups. The primary endpoint was a composite of ischemic stroke, myocardial infarction, coronary or cerebral revascularization, and cardiovascular death. Results: Among 712 enrolled patients, the mean LDL-C level was 71.0 mg/dL in 357 LT patients and 86.1 mg/dL in 355 HT patients. The primary endpoint occurred in 24 (6.7%) of LT and in 31 (8.7%) of HT group patients (adjusted hazard ratio [HR]=0.78; 95% confidence interval [CI]=0.45–1.33, P=0.353). Cardiovascular events alone occurred significantly less frequently in the LT than in the HT group (HR 0.26, 95% CI 0.09–0.80, P=0.019), whereas there were no significant differences in ischemic stroke events (HR 1.12, 95% CI 0.60–2.10, P=0.712). The benefit of LT was less apparent in patients with small vessel disease and intracranial atherosclerosis than in those with extracranial atherosclerosis. Conclusion In contrast to the French TST, the outcomes in Korean patients were neutral. Although LT was more effective in preventing cardiovascular diseases, it was not so in stroke prevention, probably attributed to the differences in stroke subtypes. Further studies are needed to elucidate the efficacy of statins and appropriate LDL-C targets in Asian patients with stroke.

Background: and Purpose Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. Methods: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. Results: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%–60.7% and 73.7%–74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen’s kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. Conclusion Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.