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1.
Eur J Radiol Open ; 8: 100325, 2021.
Article in English | MEDLINE | ID: mdl-33521170

ABSTRACT

BACKGROUND: Granulomatous Lung Diseases (GLD) encompasses a wide range of infectious and non-infectious conditions characterized by chronic inflammatory response. However, different GLD may share similar imaging findings. In this context, the purpose of this study was to outline the etiological profile and their imaging features in patients with GLD who underwent lung biopsy. METHODS: Patients with granulomatous lesions in lung biopsies and previous chest CT performed from 2014 to 2017 at our institution had imaging data reviewed by three blinded radiologists. The imaging features were analyzed according to the Fleischner Society glossary. Categorical data were represented by absolute (n) and relative (%) frequency. The contingency matrices were analyzed by Pearson's Chi-square test. Interreader agreement was assessed by calculating the intraclass correlation coefficient, using kappa (κ) statistic. RESULTS: Thirty-eight of 75 (50.7%) patients were women with a mean age of 59 ± 39 years. Infection was the most common cause of GLD (47/75, 62.7%) and Histoplasma capsulatum (27/75, 36%) was the most prevalent etiology. Nodular pattern was the most common imaging feature in histoplasmosis cases (25/27, 92.6%), whereas it occurred in half of cases (24/48) of GLD of other causes (p < 0.05). Among patients with tuberculosis, the second etiology of GLD in our study population, the most common imaging pattern was centrilobular micronodules (3/7, 42.9%), significantly more frequent than in other causes of GLD (6/68, 8.8%). Interreader agreement in detecting imaging features was almost perfect (κ = 0.88-1.00), except the nodular pattern, which had substantial agreement (κ = 0.73). CONCLUSIONS: In our study population, the main etiologies found in patients with granulomatous disease who underwent lung biopsy were fungal or mycobacterial disease, specially histoplasmosis and tuberculosis, and nodular pattern with focal distribution was the most common imaging finding which was detected with substantial interreader agreement.

2.
Int. braz. j. urol ; 45(4): 724-731, July-Aug. 2019. tab, graf
Article in English | LILACS | ID: biblio-1019880

ABSTRACT

ABSTRACT Objectives To evaluate the diagnostic performance and interobserver agreement of PI-RADS v2. Materials and Methods In this Institutional Review Board approved single-center retrospective study, 98 patients with clinically suspected PCa who underwent 3-T multiparametric MRI followed by MRI/TRUS fusion-guided prostate biopsy were included from June 2013 to February 2015. Two radiologists (R1 and R2) with 8 and 1 years of experience in abdominal radiology reviewed the MRI scans and assigned PI-RADS v2 scores in all prostate zones. PI-RADS v2 were compared to MRI/TRUS fusion-guided biopsy results, which were classified as negative, PCa, and significant PCa (sPCa). Results Sensitivity, specificity, NPV, PPV and accuracy for PCa was 85.7% (same for all metrics) for R1 and 81.6%, 79.6%, 81.2%, 80.0% and 80.6% for R2. For detecting sPCa, the corresponding values were 95.3%, 85.4%, 95.9%, 83.7% and 89.8% for R1 and 93.0%, 81.8%, 93.7%, 86.7% and 86.7% for R2. There was substantial interobserver agreement in assigning PI-RADS v2 score as negative (1, 2, 3) or positive (4, 5) (Kappa=0.78). On multivariate analysis, PI-RADS v2 (p <0.001) was the only independent predictor of sPCa compared with age, abnormal DRE, prostate volume, PSA and PSA density. Conclusions Our study population demonstrated that PI-RADS v2 had high diagnostic accuracy, substantial interobserver agreement, and it was the only independent predictor of sPCa.


Subject(s)
Humans , Male , Aged , Prostatic Neoplasms/diagnostic imaging , Magnetic Resonance Imaging/methods , Prostatic Neoplasms/pathology , Reference Values , Brazil , Logistic Models , Observer Variation , Reproducibility of Results , Retrospective Studies , Risk Factors , Sensitivity and Specificity , Prostate-Specific Antigen/blood , Statistics, Nonparametric , Risk Assessment , Neoplasm Grading , Image-Guided Biopsy/methods , Middle Aged
3.
Int Braz J Urol ; 45(4): 724-731, 2019.
Article in English | MEDLINE | ID: mdl-31136114

ABSTRACT

OBJECTIVES: To evaluate the diagnostic performance and interobserver agreement of PI-RADS v2. MATERIALS AND METHODS: In this Institutional Review Board approved single-center retrospective study, 98 patients with clinically suspected PCa who underwent 3-T multiparametric MRI followed by MRI/TRUS fusion-guided prostate biopsy were included from June 2013 to February 2015. Two radiologists (R1 and R2) with 8 and 1 years of experience in abdominal radiology reviewed the MRI scans and assigned PI-RADS v2 scores in all prostate zones. PI-RADS v2 were compared to MRI/TRUS fusion-guided biopsy results, which were classified as negative, PCa, and significant PCa (sPCa). RESULTS: Sensitivity, specificity, NPV, PPV and accuracy for PCa was 85.7% (same for all metrics) for R1 and 81.6%, 79.6%, 81.2%, 80.0% and 80.6% for R2. For detecting sPCa, the corresponding values were 95.3%, 85.4%, 95.9%, 83.7% and 89.8% for R1 and 93.0%, 81.8%, 93.7%, 86.7% and 86.7% for R2. There was substantial interobserver agreement in assigning PI-RADS v2 score as negative (1, 2, 3) or positive (4, 5) (Kappa=0.78). On multivariate analysis, PI-RADS v2 (p <0.001) was the only independent predictor of sPCa compared with age, abnormal DRE, prostate volume, PSA and PSA density. CONCLUSIONS: Our study population demonstrated that PI-RADS v2 had high diagnostic accuracy, substantial interobserver agreement, and it was the only independent predictor of sPCa.


Subject(s)
Magnetic Resonance Imaging/methods , Prostatic Neoplasms/diagnostic imaging , Aged , Brazil , Humans , Image-Guided Biopsy/methods , Logistic Models , Male , Middle Aged , Neoplasm Grading , Observer Variation , Prostate-Specific Antigen/blood , Prostatic Neoplasms/pathology , Reference Values , Reproducibility of Results , Retrospective Studies , Risk Assessment , Risk Factors , Sensitivity and Specificity , Statistics, Nonparametric
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