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

BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.

The use of cannabidiol for seizure management in patients with brain tumor-related epilepsy.

Epilepsy, commonly encountered by patients with brain tumors, is often refractory to standard therapies. Our aim was to examine the safety and efficacy of pharmaceutical grade cannabidiol (CBD; Epidiolex; Greenwich Biosciences) in those patients with epilepsy with concomitant tumors enrolled in The University of Alabama at Birmingham CBD Program (NCT02700412 and NCT02695537). Of the three patients with refractory seizures and a history of a primary brain tumor, two had improvement in seizure frequency and all three had improvement in seizure severity. These pilot results suggest that CBD should be further studied for the treatment of brain tumor-related epilepsy.

History of electromyography and nerve conduction studies: A tribute to the founding fathers.

The early development of nerve conduction studies (NCS) and electromyography (EMG) was linked to the discovery of electricity. This relationship had been concluded by observing the effect of applying electricity to the body of an animal and discovering that nerves and muscles themselves could produce electricity. We attempt to review the historical evolution of NCS and EMG over the last three centuries by reviewing the landmark publications of Galvani, Adrian, Denny-Brown, Larrabee, and Lambert. In 1771, Galvani showed that electrical stimulation of animal muscle tissue produced contraction and, thereby, the concept of animal electricity was born. In 1929, Adrian devised a method to record a single motor unit potential by connecting concentric needle electrodes to an amplifier and a loud speaker. In 1938, Denny-Brown described the fasciculation potentials and separated them from fibrillations. Toward the end of World War II, Larrabee began measuring the compound muscle action potential in healthy and injured nerves of war victims. In 1957, Lambert and Eaton described the electrophysiologic features of a new myasthenic syndrome associated with lung carcinoma. Overall, research on this topic was previously undertaken by neurophysiologists and then later by neurologists, with Adrian most likely being the first neurologist to be involved. The field greatly benefited from the invention of equipment that was capable of amplifying small bioelectrical currents by the beginning of the 20th century. Significant scientific and technical advances were later made during and after World War II which provided a large patient population with nerve injuries to study.