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PLoS Med. 2019 May 28;16(5):e1002810. doi: 10.1371/journal.pmed.1002810. eCollection 2019 May.

Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study.

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Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Department of Mathematics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tennessee, United States of America.
Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Department of Neurological Surgery, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
Department of Electrical Engineering, Rowan University, Glassboro, New Jersey, United States of America.



Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas.


We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials.


The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life.

Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: HFS and NB are co-founders of MRIMATH LLC. LBN serves on the scientific advisory boards for Abbvie, Blue Earth Diagnostics, Karyopharm, and Kiyatec and the Data safety and monitoring board for UPENN and Ziopharm. JM is 1) the Recipient of funds related to structured buyout of an oncolytic virus company, Catherex, Inc, by Amgen. 2) Equity holder in an oncolytic virus company, Treovor, Inc. 3) Equity holder in an oncolytic virus company, Aettis, Inc. 4) Board Member, UAB Health System and UAB Health Services Foundation. 5) Research grant holder from NIH and Gateway to conduct clinical trials for malignant glioma using oncolytic viruses. these funding sources were not involved in the study under submission. 6) Employment: UAB SOM and UAB Health Services Foundation. 7) Patent applications for oncolytic virus and administration techniques thereof not applicable to this paper.

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