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Objectives: Radiology reports are typically made in narrative form; this is a barrier to the implementation of advanced applications for data analysis or a decision support. We developed a system that generates structured reports for chest x-ray radiography.Methods: Based on analyzing existing reports, we determined the fundamental sentence structure of findings as compositions of procedure, region, finding, and diagnosis. We categorized the observation objects into lung, mediastinum, bone, soft tissue, and pleura and chest wall. The terms of region, finding, and diagnosis were associated with each other. We expressed the terms and the relations between the terms using a resource description framework (RDF) and developed a reporting system based on it. The system shows a list of terms in each category, and modifiers can be entered using templates that are linked to each term. This system guides users to select terms by highlighting associated terms. Fifty chest x-rays with abnormal findings were interpreted by five radiologists and reports were made either by the system or by the free-text method.Results: The system decreased the time needed to make a report by 12.5% compared with the free-text method, and the sentences generated by the system were well concordant with those made by free-text method (F-measure = 90%). The results of the questionnaire showed that our system is applicable to radiology reports of chest x-rays in daily clinical practice.Conclusions: The method of generating structured reports for chest x-rays was feasible, because it generated almost concordant reports in shorter time compared with the free-text method. [ABSTRACT FROM AUTHOR]

The article offers information on the development of a system that produces structured reports for chest x-ray radiography. The fundamental sentence structure of the findings were determined, the observation objects in the films were categorized, and the terms of region were associated with each other. Results indicated a 12.5% decreased time in report-making.

The purpose of our investigation was to compare the usefulness of the subjective visual assessment of ground-glass opacity (GGO) with a quantitative method that used a profile curve to determine prognosis. 96 adenocarcinomas were studied. Three diameters ([D1]-[D3]) were defined for estimating the diameter of tumours on the monitor: the distance between two points was measured using software that displays a CT density profile across the tumour. One experienced and one less experienced radiologist independently evaluated the following six parameters: the three diameters [D1]-[D3]; the solid portion of total tumour in the two different ratios ([D2]/[D1], [D3]/[D1]); and the area ratio of GGO for total opacity to subjective visual evaluation. Interobserver agreement between the two radiologists of the diameters (mean bias± 1.96 standard deviations) was as follows: [l], -0.7 ± 6 mm; [D2], 0.4 ± 4.4 mm; and [D3], -0.1 ± 4.2 mm (Bland and Altman's method). Interobserver agreement was fair in evaluating the area ratio of GGO (kappa test, K = 0.309). Univariate logistic regression analysis revealed that two ratios ([D2]/[D1], [D3]/[D1]) might be significantly useful in estimating lymph node metastasis (p < 0.026), lymph duct invasion (p <0.001) and recurrence (p <0.015). Observation of the area ratio of GGO by an experienced radiologist would be necessary for estimating lymph node metastasis (p = 0.04) and lymph duct invasion (p < 0.001). We concluded that the ratio of solid component to total tumour, which is obtainable in a more objective and simple way using profile curves obtained by software, is a more useful method of estimating prognosis than is visual assessment. [ABSTRACT FROM AUTHOR]

Rationale: Patients with a clinicopathological diagnosis of idiopathic pulmonary fibrosis (IPF) may have typical findings of usual interstitial pneumonia (UIP) on computed tomography (CT) or nonspecific or atypical findings, including those often seen in nonspecific interstitial pneumonia. Objectives: The aims of this study were to revisit the high-resolution CT findings of IPF and to clarify the correlation between the CT findings and mortality. Methods: The study included 98 patients with a histologic diagnosis of UIP and a clinical diagnosis of IPF. Two observers evaluated the CT findings independently and classified each case into one of the following three categories: (1) definite UIP, (2) consistent with UIP, or (3) suggestive of alternative diagnosis. The correlation between the CT categories and mortality was evaluated using the Kaplan-Meier method and the log-rank test, as well as Cox proportional hazards regression models. Measurements and Main Results: Thirty-three of the 98 CT scans were classified as definite UIP, 36 as consistent with UIP, 29 as suggestive of an alternative diagnosis. The mean survival was 45.7, 57.9, and 76.9 months, respectively. There was no significant difference in survival among the three categories (all P > 0.05). Traction bronchiectasis and fibrosis scores were significant predictors of outcome (hazard ratios: 1.30 and 1.10, respectively; 95% confidence intervals: 1.18-14.2 and 1.03-1.19, respectively). Conclusions: In patients with IPF and UIP pattern on the biopsy, the pattern of abnormality on thin-section CT, whether characteristic of UIP or suggestive of alternative diagnosis, does not influence prognosis. Prognosis is influenced by traction bronchiectasis and fibrosis scores. [ABSTRACT FROM AUTHOR]