Risk factors of stent migration in esophageal cancer patients who underwent fully-covered self-expanding metal stents for malignant dysphagia or tracheoesophageal fistula.

BACKGROUND: More than 50% of esophageal cancer patients are diagnosed with advanced diseases and commonly experience dysphagia, some of whom even have tracheoesophageal fistula. Self-expandable metal stent (SEMS) is one of the recommended palliative methods, although complications such as chest pain and stent migration are not uncommon. The goal of this study was to examine the predictors of stent migration. METHODS: We conducted a retrospective cohort study to include patients with esophageal cancer and dysphagia/tracheoesophageal fistula. Clinicopathological information, stent characteristics and patient outcomes were collected for analysis, while side-effects of SEMS were recorded, potential predictors were examined, and patients' nutritional outcomes were compared in the migration and non-migration groups. RESULTS: A total of 54 patients with esophageal cancer who received fully covered SEMS between 2013 and 2022 were included. We found tumor across the esophagogastric junction (adjusted odds ratio (OR) = 32.64, P = 0.01) and the female sex (adjusted OR = 12.5, P = 0.02) were significant predictors for stent migration. There was a decreasing tendency in body mass index/body weight in migration and non-migration groups, but the former had a steeper downslope. CONCLUSION: Fully covered SEMS is a safe and effective strategy to palliate dysphagia or fistula. Tumor across esophagogastric junction and the female sex were higher risk predictors of stent migration. A careful patient selection would optimize the effects of SEMS placement, especially in those with short-expected lifespan.

Low-dose CT screening among never-smokers with or without a family history of lung cancer in Taiwan: a prospective cohort study.

BACKGROUND: In Taiwan, lung cancers occur predominantly in never-smokers, of whom nearly 60% have stage IV disease at diagnosis. We aimed to assess the efficacy of low-dose CT (LDCT) screening among never-smokers, who had other risk factors for lung cancer. METHODS: The Taiwan Lung Cancer Screening in Never-Smoker Trial (TALENT) was a nationwide, multicentre, prospective cohort study done at 17 tertiary medical centres in Taiwan. Eligible individuals had negative chest radiography, were aged 55-75 years, had never smoked or had smoked fewer than 10 pack-years and stopped smoking for more than 15 years (self-report), and had one of the following risk factors: a family history of lung cancer; passive smoke exposure; a history of pulmonary tuberculosis or chronic obstructive pulmonary disorders; a cooking index of 110 or higher; or cooking without using ventilation. Eligible participants underwent LDCT at baseline, then annually for 2 years, and then every 2 years up to 6 years thereafter, with follow-up assessments at each LDCT scan (ie, total follow-up of 8 years). A positive scan was defined as a solid or part-solid nodule larger than 6 mm in mean diameter or a pure ground-glass nodule larger than 5 mm in mean diameter. Lung cancer was diagnosed through invasive procedures, such as image-guided aspiration or biopsy or surgery. Here, we report the results of 1-year follow-up after LDCT screening at baseline. The primary outcome was lung cancer detection rate. The p value for detection rates was estimated by the χ2 test. Univariate and multivariable logistic regression analyses were used to assess the association between lung cancer incidence and each risk factor. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of LDCT screening were also assessed. This study is registered with ClinicalTrials.gov, NCT02611570, and is ongoing. FINDINGS: Between Dec 1, 2015, and July 31, 2019, 12 011 participants (8868 females) were enrolled, of whom 6009 had a family history of lung cancer. Among 12 011 LDCT scans done at baseline, 2094 (17·4%) were positive. Lung cancer was diagnosed in 318 (2·6%) of 12 011 participants (257 [2·1%] participants had invasive lung cancer and 61 [0·5%] had adenocarcinomas in situ). 317 of 318 participants had adenocarcinoma and 246 (77·4%) of 318 had stage I disease. The prevalence of invasive lung cancer was higher among participants with a family history of lung cancer (161 [2·7%] of 6009 participants) than in those without (96 [1·6%] of 6002 participants). In participants with a family history of lung cancer, the detection rate of invasive lung cancer increased significantly with age, whereas the detection rate of adenocarcinoma in situ remained stable. In multivariable analysis, female sex, a family history of lung cancer, and age older than 60 years were associated with an increased risk of lung cancer and invasive lung cancer; passive smoke exposure, cumulative exposure to cooking, cooking without ventilation, and a previous history of chronic lung diseases were not associated with lung cancer, even after stratification by family history of lung cancer. In participants with a family history of lung cancer, the higher the number of first-degree relatives affected, the higher the risk of lung cancer; participants whose mother or sibling had lung cancer were also at an increased risk. A positive LDCT scan had 92·1% sensitivity, 84·6% specificity, a PPV of 14·0%, and a NPV of 99·7% for lung cancer diagnosis. INTERPRETATION: TALENT had a high invasive lung cancer detection rate at 1 year after baseline LDCT scan. Overdiagnosis could have occurred, especially in participants diagnosed with adenocarcinoma in situ. In individuals who do not smoke, our findings suggest that a family history of lung cancer among first-degree relatives significantly increases the risk of lung cancer as well as the rate of invasive lung cancer with increasing age. Further research on risk factors for lung cancer in this population is needed, particularly for those without a family history of lung cancer. FUNDING: Ministry of Health and Welfare of Taiwan.

Multitask deep learning on mammography to predict extensive intraductal component in invasive breast cancer.

OBJECTIVES: To develop a multitask deep learning (DL) algorithm to automatically classify mammography imaging findings and predict the existence of extensive intraductal component (EIC) in invasive breast cancer. METHODS: Mammograms with invasive breast cancers from 2010 to 2019 were downloaded for two radiologists performing image segmentation and imaging findings annotation. Images were randomly split into training, validation, and test datasets. A multitask approach was performed on the EfficientNet-B0 neural network mainly to predict EIC and classify imaging findings. Three more models were trained for comparison, including a single-task model (predicting EIC), a two-task model (predicting EIC and cell receptor status), and a three-task model (combining the abovementioned tasks). Additionally, these models were trained in a subgroup of invasive ductal carcinoma. The DeLong test was used to examine the difference in model performance. RESULTS: This study enrolled 1459 breast cancers on 3076 images. The EIC-positive rate was 29.0%. The three-task model was the best DL model with an area under the curve (AUC) of EIC prediction of 0.758 and 0.775 at the image and breast (patient) levels, respectively. Mass was the most accurately classified imaging finding (AUC = 0.915), followed by calcifications and mass with calcifications (AUC = 0.878 and 0.824, respectively). Cell receptor status prediction was less accurate (AUC = 0.625-0.653). The multitask approach improves the model training compared to the single-task model, but without significant effects. CONCLUSIONS: A mammography-based multitask DL model can perform simultaneous imaging finding classification and EIC prediction. CLINICAL RELEVANCE STATEMENT: The study results demonstrated the potential of deep learning to extract more information from mammography for clinical decision-making. KEY POINTS: • Extensive intraductal component (EIC) is an independent risk factor of local tumor recurrence after breast-conserving surgery. • A mammography-based deep learning model was trained to predict extensive intraductal component close to radiologists' reading. • The developed multitask deep learning model could perform simultaneous imaging finding classification and extensive intraductal component prediction.

Recurrent Exacerbations and Evolution into Polymyositis in a Patient with Interstitial Pneumonia with Autoimmune Features: A Case Report and Literature Review.

Interstitial pneumonia with autoimmune features (IPAF) is a new disease entity proposed in 2015. Numerous questions regarding IPAF require clarification, including diagnostic criteria, standard managements for stable disease and exacerbation, and prognosis. We report a case of a 67-year-old Asian woman who presented with progressive dyspnea. Chest computed tomography (CT) scans revealed nonspecific interstitial pneumonia. Serologic testing indicated positive anti-Jo-1 without presence of extrathoracic manifestations. An IPAF diagnosis was made after a multidisciplinary discussion. The patient experienced a severe exacerbation requiring mechanical ventilation, and she was successfully salvaged with methylprednisolone pulse therapy and single-dose cyclophosphamide. During the one-year follow-up, she reported bilateral leg muscle weakness with noticeably elevated serum creatine kinase, suggesting polymyositis. The development of malignancy was also noted 15 months after the initial presentation, and the patient eventually died. This report demonstrated successful salvage treatment with glucocorticoid pulse therapy for IPAF with acute exacerbation. However, the maintenance therapy failed to control disease progression. The treatment strategies for exacerbation and stable disease in IPAF remain unknown and need further studies. Given the high risk of evolution into a defined connective tissue disease (CTD), regular evaluation of the clinical features and biomarkers of CTDs is essential for patients with IPAF.

Elevated intramuscular adipose tissue content with a high Ishak fibrosis stage (>3) had a negative effect on liver regeneration in cirrhotic patients undergoing portal vein embolization.

This study investigated the relationship between body composition parameters and changes in future liver remnant volume (FLRV) in hepatocellular carcinoma (HCC) patients undergoing portal vein embolization (PVE) in preparation for right hepatectomy. This retrospective study enrolled 21 patients between May 2013 and October 2020. Body composition parameters, including skeletal muscle attenuation (SMA), skeletal muscle mass index (SMI), intramuscular adipose tissue content (IMAC), and visceral-to-subcutaneous adipose tissue area ratio (VSR), were measured by computed tomography (CT) prior to PVE. Liver volumetry was measured before and at least 5 weeks after PVE. The mean interval between two CT volumetries was 9.1 ± 4.9 weeks, the mean value of increase in FLRV (ΔFLRV) was 236.0 ± 118.3 cm3 , the ratio of increased FLRV (ΔFLRV%) was 55.7 ± 29.4%, and the rate of increased FLRV was 31.0 ± 18.8 (cm3 /week). Subjects with high IMAC showed significantly lower (p = 0.044) ΔFLRV% than those with normal IMAC. Furthermore, ΔFLRV% was linearly reduced (p for trend = 0.043) among those with low Ishak fibrosis stage (<3) + normal IMAC (76.1 ± 36.8%), those with low Ishak fibrosis stage (<3) + high IMAC or high Ishak fibrosis stage (>3) + normal IMAC (54.0 ± 24.1%), and those with high Ishak fibrosis stage (>3) + low IMAC (28.7 ± 1.6%) (p for trend = 0.043). Our data indicated that high IMAC with a high Ishak fibrosis stage (>3) had a significant negative effect on ΔFLRV%.

Integration of Clinical and CT-Based Radiomic Features for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Breast Cancer.

The purpose of the present study was to examine the potential of a machine learning model with integrated clinical and CT-based radiomics features in predicting pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) in breast cancer. Contrast-enhanced CT was performed in 329 patients with breast tumors (n = 331) before NST. Pyradiomics was used for feature extraction, and 107 features of seven classes were extracted. Feature selection was performed on the basis of the intraclass correlation coefficient (ICC), and six ICC thresholds (0.7−0.95) were examined to identify the feature set resulting in optimal model performance. Clinical factors, such as age, clinical stage, cancer cell type, and cell surface receptors, were used for prediction. We tried six machine learning algorithms, and clinical, radiomics, and clinical−radiomics models were trained for each algorithm. Radiomics and clinical−radiomics models with gray level co-occurrence matrix (GLCM) features only were also built for comparison. The linear support vector machine (SVM) regression model trained with radiomics features of ICC ≥0.85 in combination with clinical factors performed the best (AUC = 0.87). The performance of the clinical and radiomics linear SVM models showed statistically significant difference after correction for multiple comparisons (AUC = 0.69 vs. 0.78; p < 0.001). The AUC of the radiomics model trained with GLCM features was significantly lower than that of the radiomics model trained with all seven classes of radiomics features (AUC = 0.85 vs. 0.87; p = 0.011). Integration of clinical and CT-based radiomics features was helpful in the pretreatment prediction of pCR to NST in breast cancer.

Long-Term Study on Therapeutic Strategy for Treatment of Eisenmenger Syndrome Patients: A Case Series Study.

Eisenmenger syndrome (ES) refers to congenital heart diseases (CHD) with reversal flow associated with increased pulmonary pressure and irreversible pulmonary vascular remodeling. Previous reports showed limited therapeutic strategies in ES. In this study, 5 ES patients (2 males and 3 females), who had been followed regularly at our institution from 2010 to 2019, were retrospectively reviewed. We adopted an add-on combination of sildenafil, bosentan, and iloprost and collected the clinical characteristics and outcomes as well as findings of echocardiography, computed tomography, pulmonary perfusion-ventilation scans, positron emission tomography, and biomarkers. The age of diagnosis in these ES patients ranged from 23 to 54 years (38.2 ± 11.1 years; mean ± standard deviation), and they were followed for 7 to 17 years. Their mean pulmonary arterial pressure and pulmonary vascular resistance index were 56.4 ± 11.3 mmHg and 24.7 ± 8.5 WU.m2, respectively. Intrapulmonary arterial thrombosis was found in 4 patients, ischemic stroke was noted in 2 patients, and increased glucose uptake of the right ventricle was observed in 4 patients. No patient mortality was seen within 5 years of follow-up. Subsequently, 2 patients died of right ventricular failure, 1 died of sepsis related to brain abscess, and another died of sudden death. The life span of these patients was 44-62 years. Although these patients showed longer survival, the beneficial data on specific-target pharmacologic interventions in ES is still preliminary. Thus, larger trials are warranted, and the study of cardiac remodeling in ES from various CHD should be explored.

Unique Pulmonary Hypertension in Young Children: A Case Series Study.

Pediatric pulmonary hypertension (PH) has a similar clinical presentation to the adult disease but is associated with several additional disorders and challenges that require a specific approach for their fulminant course. With improved care for premature infants, various forms of pulmonary vascular disease have been found in children that did not previously exist. Pediatric PH can begin in utero, resulting in pulmonary vascularity growth abnormalities that may persist into adulthood. Here, we retrospectively reviewed several unique pediatric PH cases from 2000 to 2020 at Kaohsiung Medical University Hospital, Taiwan, a tertiary teaching hospital. Their comorbidities varied and included surfactant dysfunction, bronchopulmonary dysplasia, premature closure of the ductus arteriosus, high levels of renin and aldosterone, and Swyer-James-Macleod syndrome. Their clinical profiles, radiological characteristics, echocardiography, pulmonary angiogram, and therapeutic regimens were recorded. Further, because the underlying causes of pediatric PH were complex and markedly different according to age, adult PH classification may not be applicable to pediatric PH in all settings. We also classified these cases using different systems, including the Panama classification and the Sixth World Symposium on PH, and compared their advantages and disadvantages.

Automatic assessment of bone age in Taiwanese children: A comparison of the Greulich and Pyle method and the Tanner and Whitehouse 3 method.

Proper bone age assessment is crucial for the clinical diagnosis and evaluation of treatment responses. We investigated the applicability of Greulich and Pyle (GP), and Tanner and Whitehouse 3 (TW3) methods for children in modern Taiwan, using computer-aided diagnosis. Hand and wrist radiographs were obtained from 611 children (3-17 years) who came to our emergency department due to trauma. Ages 0 to 2 years old were excluded because of a limited number of cases. Skeletal maturation was assessed using the BoneXpert (version 2.5.4.1 automated software), which determines GP and TW3 bone age. The two scoring systems were evaluated for comparing the chronological ages in each subgroup. In boys, mean GP bone age vs mean chronological ages were delayed for ages 3 to 11 and advanced for age 12 to 17. In girls, mean GP bone age vs mean chronological ages was delayed for ages 4 to 8 and 17, and advanced for ages 3 and 9 to 17. In boys, the mean TW3 bone ages vs mean chronological ages were delayed for ages 5 to 10 except age 8, and advanced for ages 3 to 4, 8, and 11 to 15. In girls, the mean TW3 bone ages vs mean chronological ages were delayed for ages 4 to 12, and advanced for ages 3 and 13 to 14. By using the BoneXpert automatic software, we established bone age reference standards for children in Taiwan. Clinical application of GP and TW3 scoring methods can be adjusted according to our results to better assess bone age.

Association between Geriatric Nutrition Risk Index and Skeletal Muscle Mass Index with Bone Mineral Density in Post-Menopausal Women Who Have Undergone Total Thyroidectomy.

BACKGROUND: Osteoporosis is highly prevalent in postmenopausal women and may result in fractures and disabilities. Total thyroidectomy has also been associated with loss of bone mass. The aim of this cross-sectional study was to evaluate associations among nutritional status, skeletal muscle index and markers of bone turnover to bone mineral density in postmenopausal women who had undergone total thyroidectomy. METHODS: Fifty postmenopausal women who had undergone total thyroidectomy were included. Body composition was measured using dual-energy X-ray absorptiometry (DXA). The Geriatric Nutritional Risk Index (GNRI) was calculated using baseline body weight and serum albumin level. Skeletal muscle mass index was calculated as the appendicular skeletal muscle mass (ASM) divided by the height squared and assessed using DXA. RESULTS: Multivariate stepwise linear regression analysis showed that a low GNRI was significantly associated with low lumbar spine bone mineral density (BMD) and T-score, and that a low ASM/height2 was significantly associated with low femoral neck BMD and T-score. A low vitamin D level was significantly associated with low femoral neck BMD and T-score and low total hip BMD and T-score. A high bone alkaline phosphatase (ALP) level was significantly associated with low femoral neck T-score and low total hip BMD and T-score. A low insulin-like growth factor-1 (IGF-1) was significantly associated with low total hip BMD and T-score. CONCLUSION: In the postmenopausal women who had undergone total thyroidectomy in this study, BMD was positively associated with GNRI, skeletal muscle mass index, and levels of vitamin D and serum IGF-1, and inversely associated with bone ALP level. Nutritional status, skeletal muscle mass index and bone turnover biomarkers can be used to early identify patients with a high risk of osteoporosis in this high-risk group.

Cost-effectiveness of stereotactic vacuum-assisted biopsy for nonpalpable breast lesions.

PURPOSE: To examine the potential cost-savings of stereotactic vacuum-assisted biopsy (SVAB) over open surgical biopsy (OSB) in diagnosis of nonpalpable lesions on mammography and to estimate the cost-saving effect on lesions at different levels of malignant probability. METHODS: This retrospective study was approved by our Institutional Review Board. We retrospectively reviewed 276 (33.8 %) SVAB and 541 (66.2 %) OSB medical records at a medical center. Direct costs included patients' self-paid and national health insurance claim charges. Indirect costs were calculated using sick days, average salary, and age-adjusted employment rate. One-way and two-way sensitivity analyses were conducted. Lesion classification was determined by the assessment categories of Breast Imaging Reporting and Data System (BI-RADS), 4th or 5th editions. RESULTS: SVAB decreased the direct cost by $90.3 (10.1 %) per diagnosis. The indirect cost was decreased by $560.2 (96.0 %). Overall, SVAB saved 43.9 % of resource utilization for each biopsy. Taking the cost of the subsequent malignant surgery into account, from the healthcare providers' perspective, SVAB was cost-effective if a lesion had less than 19 % likelihood of malignancy. From the societal perspective, SVAB reduced productivity loss for all the lesions. Based on the positive predictive value of the BI-RADS categories, SVAB was more suitable for the lesions of category 4A and category 3, resulting in greater savings in both medical and societal resources. CONCLUSIONS: SVAB is a cost-effective diagnostic option for nonpalpable breast lesions. The cost-saving effect is greater for the lesions of category 4A and category 3.

Post-infectious Bronchiolitis Obliterans: HRCT, DECT, Pulmonary Scintigraphy Images, and Clinical Follow-up in Eight Children.

Background: Bronchiolitis obliterans (BO), first mentioned in 1901, is a severe and rare chronic lung disease in children. BO has various etiologies and the most common in children is post-infectious BO (PIBO). High resolution CT (HRCT) is an often-used image tool for the diagnosis of BO, and pulmonary scintigraphy is an alternative tool that can functionally evaluate BO. Recently, dual-energy computed tomography (DECT) have also been applied to BO for its accuracy and safety. Here we described the characteristics of HRCT, pulmonary scintigraphy, DECT, and the clinical profiles of patients with PIBO. Methods: This is a retrospective and descriptive study. Data were collected from patients diagnosed with PIBO from 2014 to 2019 in the Pediatric Cardiopulmonary Outpatient Clinics of Kaohsiung Medical University Hospital. The diagnosis was based on clinical, chest X-ray, and HRCT findings. Clinical profile, radiological characteristics, and images of pulmonary scintigraphy were documented. Results: Eight children (4 boys and 4 girls) were diagnosed with PIBO at a mean age of 25.8 months (range 15 to 41 months). Two of our patients developed pulmonary hypertension. The most common HRCT finding is mosaic pattern, where match ventilation/perfusion (V/Q) defects is a general feature in pulmonary scintigraphy. DECT pulmonary blood vasculature images revealed various degrees of decreased perfusion and is compatible with the decreased perfusion on pulmonary scintigraphy. Conclusion: The therapeutic strategy of PIBO is still lacking of standardization. HRCT and V/Q scans are important image tools in diagnosis and follow-up of BO. DECT may be used in BO patients as it has no additional radiation exposure and add value on functional information of HRCT.

Influence of Alternate Hot and Cold Thermal Stimulation in Cortical Excitability in Healthy Adults: An fMRI Study.

Stroke rehabilitation using alternate hot and cold thermal stimulation (altTS) has been reported to improve motor function in hemiplegia; however, the influence of brain excitability induced by altTS remains unclear. This study examined cortical activation induced by altTS in healthy adults, focusing on motor-related areas. This involved a repeated crossover experimental design with two temperature settings (innocuous altTS with alternate heat-pain and cold-pain thermal and noxious altTS with alternate heat and cold thermal) testing both arms (left side and right side). Thirty-one healthy, right-handed participants received four episodes of altTS on four separate days. Functional magnetic resonance imaging scans were performed both before and after each intervention to determine whether altTS intervention affects cortical excitability, while participants performed a finger-tapping task during scanning. The findings revealed greater response intensity of cortical excitability in participants who received noxious altTS in the primary motor cortex, supplementary motor cortex, and somatosensory cortex than in those who received innocuous altTS. Moreover, there was more motor-related excitability in the contra-lateral brain when heat was applied to the dominant arm, and more sensory-associated excitability in the contra-lateral brain when heat was applied to the nondominant arm. The findings highlight the effect of heat on cortical excitability and provide insights into the application of altTS in stroke rehabilitation.

Accuracy and outcomes of stereotactic vacuum-assisted breast biopsy for diagnosis and management of nonpalpable breast lesions.

Stereotactic vacuum-assisted biopsy (SVAB) is an alternative method of breast biopsy for nonpalpable lesions detected by mammography. Considering the diagnostic effectiveness, a direct comparison of SVAB and open surgical biopsy (OSB) is lacking. We performed a retrospective review of 276 (33.8%) SVAB and 541 (66.2%) OSB to compare the diagnostic accuracy and the total number of procedures the patients underwent. The negative predictive values of OSB and SVAB were 99.77% and 99.61%, and their false-negative rates were 0.96% and 4.76%, respectively. SVAB, as the first-line biopsy method, obviated 92.3% of operations. All malignancies diagnosed using SVAB could be treated with single therapeutic surgery. By contrast, 48% of malignancies of OSB group received two operations. Breast Imaging Reporting and Data System (BI-RADS) category used at the study correlated well with the percentage of malignancy and can thus be used to predict biopsy results. Our study concluded that SVAB is reliable for diagnosing nonpalpable breast lesions and is the better biopsy method for categories 3 and 4A lesions, which reduces the benign surgery rate. For lesions with a higher likelihood of malignancy, BI-RADS 4B, 4C and 5, SVAB has an advantage over OSB, which lowers the total number of operations for malignancy treatment.

Convex border of peripheral non-small cell lung cancer on CT images as a potential indicator of pleural invasion.

The aim of the study is to evaluate the use of the tumor border in peripheral non-small cell lung cancer (NSCLC) as an indicator of pleural invasion.This retrospective study was performed at a single tertiary center. The analysis of 136 patients with peripheral NSCLC included 101 (74.3%) patients with pathologically proven pleural invasion and 35 (25.7%) patients without pleural invasion. The tumor borders on conventional computed tomography (CT) were classified into 5 types on lung window setting: type 1, S or reverse S border with a blunt angle; type 2, sharp angle; type 3, concave border with a blunt angle; type 4, straight border with a perpendicular angle; and type 5, convex border with a perpendicular or blunt angle. In patients with more than 1 tumor border type, the priority was type 5, 4, 3, 2, and 1. Blunt angle, pleural contact >3 cm, and adjacent pleural thickening were also recorded for comparison with pleural invasion of peripheral tumors.Tumor border types 2 and 5 significantly differed between patients with and without pleural invasion (P = .001 and P < .001, respectively). Patients with and without pleural invasion did not significantly differ in tumor border type 1, tumor border type 3, tumor border type 4, blunt angle, pleural contact >3 cm, or pleural thickening. Tumor border type 5 was a moderate indicator of pleural invasion with positive LR, 5.20; accuracy, 57%; sensitivity, 45%; specificity, 91%; PPV, 94%; and NPV, 36%. Tumor border type 2 was a weak indicator of pleural invasion with positive LR, 0.51; accuracy, 34%; sensitivity, 34%; specificity, 34%; PPV, 60%; and NPV, 15%.Tumor border type 5 has a high PPV and high specificity for predicting pleural invasion by peripheral NSCLC.

Comparison of LCModel and SAGE in Analysis of Brain Metabolite Concentrations-A study of Patients with Mild Cognitive Impairment.

PURPOSE: The purpose of this study was to compare brain metabolite concentration ratios determined by LCModel and Spectroscopy Analysis by General Electric (SAGE) quantitative methods to elucidate the advantages and disadvantages of each method. MATERIALS AND METHODS: A total of 10 healthy volunteers and 10 patients with mild cognitive impairment (MCI) were recruited in this study. A point-resolved spectroscopy (PRESS) sequence was used to obtain the brain magnetic resonance spectroscopy (MRS) spectra of the volunteers and patients, as well as the General Electric (GE) MRS-HD-sphere phantom. The brain metabolite concentration ratios were estimated based on the peak area obtained from both LCModel and SAGE software. Three brain regions were sampled for each volunteer or patient, and 20 replicates were acquired at different times for the phantom analysis. RESULTS: The metabolite ratios of the GE phantom were estimated to be myo-inositol (mI)/creatine (Cr): 0.70 ± 0.01, choline (Cho)/Cr: 0.37 ± 0.00, N-acetylaspartate (NAA)/Cr: 1.26 ± 0.02, and NAA/mI: 1.81 ± 0.04 by LCModel, and mI/Cr: 0.88 ± 0.15, Cho/Cr: 0.35 ± 0.01, NAA/Cr: 1.33 ± 0.03, and NAA/mI: 1.55 ± 0.26 by SAGE. In the healthy volunteers and MCI patients, the ratios of mI/Cr and Cho/Cr estimated by LCModel were higher than those estimated by SAGE. In contrast, the ratio of NAA/Cr estimated by LCModel was lower than that estimated by SAGE. CONCLUSION: Both methods were acceptable in estimating brain metabolite concentration ratios. However, LCModel was marginally more accurate than SAGE because of its full automation, basis set, and user independency.