Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Purpose: Focal pattern in multiple myeloma (MM) seems to be related to poorer survival and differentiation from diffuse to focal pattern on computed tomography (CT) has inter-reader variability. We postulated that a Radiomic approach could help radiologists in differentiating diffuse from focal patterns on CT.
Methods: We retrospectively reviewed imaging data of 70 patients with MM with CT, PET-CT or MRI available before bone marrow transplant. Two general radiologist evaluated, in consensus, CT images to define a focal (at least one lytic lesion >5 mm in diameter) or a diffuse (lesions <5 mm, not osteoporosis) pattern. N = 104 Radiomics features were extracted and evaluated with an open source software.
Results: The pathological group included: 22 diffuse and 39 focal patterns. After feature reduction, 9 features were different (p < 0.05) in the diffuse and focal patterns (n = 2/9 features were Shape-based: MajorAxisLength and Sphericity; n = 7/9 were Gray Level Run Length Matrix (Glrlm)). AUC of the Radiologists versus Reference Standard was 0.64 (95 % CI: (0.49-0.78) p = 0.20. AUC of the best 4 features (MajorAxisLength, Median, SizeZoneNonUniformity, ZoneEntropy) were: 0.73 (95 % CI: 0.58-0.88); 0.71 (95 % CI: 0.54-0.88); 0.79 (95 % CI: 0.66-0.92); 0.68 (95 % CI: 0.53-0.83) respectively.
Conclusion: A Radiomics approach improves radiological evaluation of focal and diffuse pattern of MM on CT.
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Source |
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http://dx.doi.org/10.1016/j.ejrad.2019.108739 | DOI Listing |
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