BACKGROUND: The purpose of this study was to evaluate the use of high-resolution chest computed tomography (HRCT) to distinguish hypersensitivity pneumonitis (HP) from other diffuse parenchymal lung diseases (DPLDs). METHODS: We examined 130 consecutive patients admitted to our hospital with DPLDs proved by HRCT. Patients underwent clinical and paraclinical examinations. Two readers interpreted 111 HRCT scans using predefined criteria. RESULTS: The findings in patients with HP were compared to those with other DPLDs (non-HP) by univariate and multivariate analyses. Five independent radiological predictors were identified and were given a weight according to their regression coefficient: ground-glass attenuation nodules (4 points), homogeneous ground-glass opacity (3 points), patchy ground-glass opacity (2 points), absence of adenopathy (2 points), and absence of linear/reticular patterns (2 points). A total score (that we called "diagnostic index") of 5 offered the best trade-off between sensitivity and specificity. At this point of the ROC curve, the sensitivity, specificity, and likelihood ratio were 74%, 90% and 7.7, respectively. Given a pre-test probability of HP of 34% (i.e., 38 HP / 111 patients), the post-test probability was 79%. CONCLUSION: Our results provide evidence that HRCT can accurately distinguish HP from other DPLDs.
BACKGROUND: The purpose of this study was to evaluate the use of high-resolution chest computed tomography (HRCT) to distinguish hypersensitivitypneumonitis (HP) from other diffuse parenchymal lung diseases (DPLDs). METHODS: We examined 130 consecutive patients admitted to our hospital with DPLDs proved by HRCT. Patients underwent clinical and paraclinical examinations. Two readers interpreted 111 HRCT scans using predefined criteria. RESULTS: The findings in patients with HP were compared to those with other DPLDs (non-HP) by univariate and multivariate analyses. Five independent radiological predictors were identified and were given a weight according to their regression coefficient: ground-glass attenuation nodules (4 points), homogeneous ground-glass opacity (3 points), patchy ground-glass opacity (2 points), absence of adenopathy (2 points), and absence of linear/reticular patterns (2 points). A total score (that we called "diagnostic index") of 5 offered the best trade-off between sensitivity and specificity. At this point of the ROC curve, the sensitivity, specificity, and likelihood ratio were 74%, 90% and 7.7, respectively. Given a pre-test probability of HP of 34% (i.e., 38 HP / 111 patients), the post-test probability was 79%. CONCLUSION: Our results provide evidence that HRCT can accurately distinguish HP from other DPLDs.
Authors: Thibaud Soumagne; Marie-Laure Chardon; Gaël Dournes; Lucie Laurent; Bruno Degano; François Laurent; Jean Charles Dalphin Journal: PLoS One Date: 2017-06-14 Impact factor: 3.240
Authors: Ganesh Raghu; Martine Remy-Jardin; Christopher J Ryerson; Jeffrey L Myers; Michael Kreuter; Martina Vasakova; Elena Bargagli; Jonathan H Chung; Bridget F Collins; Elisabeth Bendstrup; Hassan A Chami; Abigail T Chua; Tamera J Corte; Jean-Charles Dalphin; Sonye K Danoff; Javier Diaz-Mendoza; Abhijit Duggal; Ryoko Egashira; Thomas Ewing; Mridu Gulati; Yoshikazu Inoue; Alex R Jenkins; Kerri A Johannson; Takeshi Johkoh; Maximiliano Tamae-Kakazu; Masanori Kitaichi; Shandra L Knight; Dirk Koschel; David J Lederer; Yolanda Mageto; Lisa A Maier; Carlos Matiz; Ferran Morell; Andrew G Nicholson; Setu Patolia; Carlos A Pereira; Elisabetta A Renzoni; Margaret L Salisbury; Moises Selman; Simon L F Walsh; Wim A Wuyts; Kevin C Wilson Journal: Am J Respir Crit Care Med Date: 2020-08-01 Impact factor: 30.528