{"id":80331,"date":"2016-09-26T12:00:21","date_gmt":"2016-09-26T11:00:21","guid":{"rendered":"https:\/\/www.transcend.org\/tms\/?p=80331"},"modified":"2016-09-25T18:05:41","modified_gmt":"2016-09-25T17:05:41","slug":"computer-program-beats-doctors-at-spotting-brain-cancer","status":"publish","type":"post","link":"https:\/\/www.transcend.org\/tms\/2016\/09\/computer-program-beats-doctors-at-spotting-brain-cancer\/","title":{"rendered":"Computer Program Beats Doctors at Spotting Brain Cancer"},"content":{"rendered":"<p><a href=\"https:\/\/www.transcend.org\/tms\/wp-content\/uploads\/2016\/09\/Computer-program-beats-doctors-at-spotting-brain-cancer.jpg\" ><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-80332\" src=\"https:\/\/www.transcend.org\/tms\/wp-content\/uploads\/2016\/09\/Computer-program-beats-doctors-at-spotting-brain-cancer.jpg\" alt=\"computer-program-beats-doctors-at-spotting-brain-cancer\" width=\"500\" height=\"333\" srcset=\"https:\/\/www.transcend.org\/tms\/wp-content\/uploads\/2016\/09\/Computer-program-beats-doctors-at-spotting-brain-cancer.jpg 320w, https:\/\/www.transcend.org\/tms\/wp-content\/uploads\/2016\/09\/Computer-program-beats-doctors-at-spotting-brain-cancer-300x200.jpg 300w\" sizes=\"auto, (max-width: 500px) 100vw, 500px\" \/><\/a><\/p>\n<p><em>21 Sep 2016 &#8211; <\/em>A computer program developed by a team of researchers led by an Indian American scientist has outperformed physicians in diagnosing brain cancer. The program was nearly twice as accurate as two neuroradiologists in determining whether abnormal tissue seen on magnetic resonance images were dead brain cells caused by radiation, called radiation necrosis, or if brain cancer had returned, reported a study published online in the American Journal of Neuroradiology Sept. 15.<\/p>\n<p>\u201cOne of the biggest challenges with the evaluation of brain tumor treatment is distinguishing between the confounding effects of radiation and cancer recurrence,\u201d said Pallavi Tiwari, an assistant professor at Case Western Reserve University in Cleveland, Ohio. \u201cOn an MRI, they look very similar,\u201d she said. With further confirmation of its accuracy, radiologists using their expertise and the program may eliminate unnecessary and costly biopsies Tiwari said.<\/p>\n<p>Brain biopsies are currently the only definitive test but are highly invasive and risky, causing considerable morbidity and mortality. To develop the program, the researchers employed machine learning algorithms in conjunction with radiomics, the term used for features extracted from images using computer algorithms.<\/p>\n<p>The team trained the computer to identify radiomic features that discriminate between brain cancer and radiation necrosis, using routine follow-up MRI scans from 43 patients. The team then developed algorithms to find the most discriminating radiomic features, in this case, textures that cannot be seen by simply eyeballing the images.<\/p>\n<p>\u201cWhat the algorithms see that the radiologists don\u2019t are the subtle differences in quantitative measurements of tumour heterogeneity and breakdown in microarchitecture on MRI, which are higher for tumour recurrence,\u201d Tiwari said.<\/p>\n<p>In the direct comparison, two physicians and the computer programs analyzed MRI scans from 15 patients from University of Texas Southwest Medical Center. One neuroradiologist diagnosed seven patients correctly, and the second physician correctly diagnosed eight patients. The computer program was correct on 12 of the 15, the study said.<\/p>\n<p><a target=\"_blank\" href=\"http:\/\/theunn.com\/2016\/09\/computer-program-beats-doctors-at-spotting-brain-cancer\/\" >Go to Original \u2013 theunn.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>21 Sep 2016 &#8211; A computer program developed by a team of researchers led by an Indian American scientist has outperformed physicians in diagnosing brain cancer. The program was nearly twice as accurate as two neuroradiologists.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[216],"tags":[],"class_list":["post-80331","post","type-post","status-publish","format-standard","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/posts\/80331","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/comments?post=80331"}],"version-history":[{"count":0,"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/posts\/80331\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/media?parent=80331"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/categories?post=80331"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.transcend.org\/tms\/wp-json\/wp\/v2\/tags?post=80331"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}