3 research outputs found

    Inter- and intra-operator variations in manual segmentation of hippocampus from MRI

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    Purpose: We evaluate inter- and intra-operator variations in manual segmentation of hippocampus and present their potential sources. Hippocampal atrophy is common in mesial temporal lobe epilepsy (mTLE). Effective diagnosis and treatment of mTLE depends on accurate and efficient segmentation of hippocampus from magnetic resonance imaging (MRI) data. Manual segmentation by expert radiologists remains the gold standard, although automated segmentation methods exist. Methods: Hippocampus was segmented in MRI of 118 unilateral mTLE patients and 25 non-epileptic subjects (65 males, 78 females; mean age 39 years) by three operators (M1, M2, M3) manually and by three software tools (FreeSurfer, LocalInfo, ABSS) automatically. Segmentation results were evaluated using 7 volume-, voxel-, and distance-based performance measures. Inter-operator variation was evaluated by comparing the segmentation results of the three operators. Intra-operator variation was evaluated by comparing manual and automatic segmentation results. Segmentation results were used to lateralize epileptogenicity in mTLE patients. Results: Ranking of performance measures differed when using M3 segmentations as ground truth rather than M1 or M2 segmentations. The standard deviation tended to be higher when using M3 as ground truth and M1 or M2 as test segmentation. Variation in performance measures and increased standard deviation when using M3 as ground truth are indicative of inter-operator variability. Standard deviations were larger when using M2 segmentations as ground truth and automated segmentations as test segmentation, rather than M1 or M3. Large standard deviations between M2 segmentations and automated segmentations are indicative of intra-operator variation. Among automated segmentation methods, ABSS produced segmentations most similar to manual segmentations, but FreeSurfer and LocalInfo lateralized epileptogenicity more accurately. Conclusions: Part of inter-operator variation might be due to temporal separation of M3 segmentations from M1 and M2 segmentations (M3 performed segmentations a few years before operators M1 and M2). Inter-operator variation will likely reduce if all operators segment within the same time frame, reducing discrepancies in training of operators. Intra-operator variation can likely be mitigated with additional oversight by a neuroradiologist. Inter- and intra-operator variability may generate inconsistencies in outcomes. Future automated segmentation techniques may integrate neural-network-based (ABSS) and atlas-based (FreeSurfer and LocalInfo) segmentation techniques for optimal performance

    Effect of seizure timing on long-term survival in patients with brain tumor

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    OBJECTIVE: Seizures often occur in patients with primary brain tumor (BT). The aim of this study was to determine if there is an association between the time of occurrence of seizures during the course of BT and survival of these patients. METHODS: This retrospective cohort study at Henry Ford Hospital, an urban tertiary referral center, included all patients who were diagnosed with primary BTs at Henry Ford Health System between January 2006 and December 2014. Timing of seizure occurrence, if occurred at presentation or after the tumor diagnosis during follow-up period, in different grades of BTs, and survival of these patients were analyzed. RESULTS: Of the 901 identified patients, 662 (53% male; mean age: 56 years) were included in final analysis, and seizures occurred in 283 patients (43%). Patients with World Health Organization (WHO) grade III BT with seizures as a presenting symptom only had better survival (adjusted hazard ratio (HR): 0.27; 95% confidence interval (CI), 0.11-0.67; P = 0.004). Seizures that occurred after tumor diagnosis only (adjusted HR: 2.11; 95% CI, 1.59-2.81; P \u3c 0.001) in patients with WHO grade II tumors (adjusted HR: 3.41; 95% CI, 1.05-11.1; P = 0.041) and WHO grade IV tumors (adjusted HR: 2.14; 95% CI, 1.58-2.90; P \u3c 0.001) had higher mortality. Seizures that occurred at presentation and after diagnosis also had higher mortality (adjusted HR: 1.34; 95% CI, 1.00-1.80; P = 0.049), in patients with meningioma (adjusted HR: 6.19; 95% CI, 1.30-29.4; P = 0.021) and grade III tumors (adjusted HR: 6.19; 95% CI, 2.56-15.0; P \u3c 0.001). CONCLUSION: Seizures occurred in almost half of the patients with BTs. The association between seizures in patients with BT and their survival depends on the time of occurrence of seizures, if occurring at presentation or after tumor diagnosis, and the type of tumor. Better survival was noted in patients with WHO grade III BTs who had seizures at presentation at the time of diagnosis, while higher mortality was noted in WHO grade II tumors who had seizure at presentation and after tumor diagnosis, and in grade IV tumors after tumor diagnosis

    Inter- and intra-operator variations in manual segmentation of hippocampus from MRI

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    Purpose: We evaluate inter- and intra-operator variations in manual segmentation of hippocampus and present their potential sources. Hippocampal atrophy is common in mesial temporal lobe epilepsy (mTLE). Effective diagnosis and treatment of mTLE depends on accurate and efficient segmentation of hippocampus from magnetic resonance imaging (MRI) data. Manual segmentation by expert radiologists remains the gold standard, although automated segmentation methods exist. Methods: Hippocampus was segmented in MRI of 118 unilateral mTLE patients and 25 non-epileptic subjects (65 males, 78 females; mean age 39 years) by three operators (M1, M2, M3) manually and by three software tools (FreeSurfer, LocalInfo, ABSS) automatically. Segmentation results were evaluated using 7 volume-, voxel-, and distance-based performance measures. Inter-operator variation was evaluated by comparing the segmentation results of the three operators. Intra-operator variation was evaluated by comparing manual and automatic segmentation results. Segmentation results were used to lateralize epileptogenicity in mTLE patients. Results: Ranking of performance measures differed when using M3 segmentations as ground truth rather than M1 or M2 segmentations. The standard deviation tended to be higher when using M3 as ground truth and M1 or M2 as test segmentation. Variation in performance measures and increased standard deviation when using M3 as ground truth are indicative of inter-operator variability. Standard deviations were larger when using M2 segmentations as ground truth and automated segmentations as test segmentation, rather than M1 or M3. Large standard deviations between M2 segmentations and automated segmentations are indicative of intra-operator variation. Among automated segmentation methods, ABSS produced segmentations most similar to manual segmentations, but FreeSurfer and LocalInfo lateralized epileptogenicity more accurately. Conclusions: Part of inter-operator variation might be due to temporal separation of M3 segmentations from M1 and M2 segmentations (M3 performed segmentations a few years before operators M1 and M2). Inter-operator variation will likely reduce if all operators segment within the same time frame, reducing discrepancies in training of operators. Intra-operator variation can likely be mitigated with additional oversight by a neuroradiologist. Inter- and intra-operator variability may generate inconsistencies in outcomes. Future automated segmentation techniques may integrate neural-network-based (ABSS) and atlas-based (FreeSurfer and LocalInfo) segmentation techniques for optimal performance
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