Interstitial Lung Disease (ILD) encompasses a wide array of diseases that share some common radiologic characteristics. When diagnosing such diseases, radiologists can be affected by heavy workload and fatigue thus decreasing diagnostic accuracy. Automatic segmentation is the first step in implementing a Computer Aided Diagnosis (CAD) that will help radiologists to improve diagnostic accuracy thereby reducing manual interpretation. Automatic segmentation proposed uses an initial thresholding and morphology based segmentation coupled with feedback that detects large deviations with a corrective segmentation. This feedback is analogous to a control system which allows detection of abnormal or severe lung disease and provides a feedback to an online segmentation improving the overall performance of the system. This feedback system encompasses a texture paradigm. In this study we studied 48 males and 48 female patients consisting of 15 normal and 81 abnormal patients. A senior radiologist chose the five levels needed for ILD diagnosis. The results of segmentation were displayed by showing the comparison of the automated and ground truth boundaries (courtesy of ImgTracer™ 1.0, AtheroPoint™ LLC, Roseville, CA, USA). The left lung's performance of segmentation was 96.52% for Jaccard Index and 98.21% for Dice Similarity, 0.61 mm for Polyline Distance Metric (PDM), -1.15% for Relative Area Error and 4.09% Area Overlap Error. The right lung's performance of segmentation was 97.24% for Jaccard Index, 98.58% for Dice Similarity, 0.61 mm for PDM, -0.03% for Relative Area Error and 3.53% for Area Overlap Error. The segmentation overall has an overall similarity of 98.4%. The segmentation proposed is an accurate and fully automated system.
Rationale: Neuroendocrine cell hyperplasia of infancy (NEHI) is an important form of children's interstitial and diffuse lung disease for which the diagnostic strategy has evolved. The prevalence of comorbidities in NEHI that may influence treatment has not been previously assessed.Objectives: To evaluate a previously unpublished NEHI clinical score for assistance in diagnosis of NEHI and to assess comorbidities in NEHI.Methods: We performed a retrospective chart review of 199 deidentified patients with NEHI from 11 centers. Data were collected in a centralized Research Electronic Data Capture registry and we performed descriptive statistics.Results: The majority of patients with NEHI were male (66%). The sensitivity of the NEHI Clinical Score was 87% (95% confidence interval [CI], 0.82-0.91) for all patients from included centers and 93% (95% CI, 0.86-0.97) for those with complete scores (e.g., no missing data). Findings were similar when we limited the population to the 75 patients diagnosed by lung biopsy (87%; 95% CI, 0.77-0.93). Of those patients evaluated for comorbidities, 51% had gastroesophageal reflux, 35% had aspiration or were at risk for aspiration, and 17% had evidence of immune system abnormalities.Conclusions: The NEHI Clinical Score is a sensitive tool for clinically evaluating NEHI; however, its specificity has not yet been addressed. Clinicians should consider evaluating patients with NEHI for comorbidities, including gastroesophageal reflux, aspiration, and immune system abnormalities, because these can contribute to the child's clinical picture and may influence clinical course and treatment.