Alison S. Smith

Application of a computerized language lateralization index from FMRI by a group of clinical neuroradiologists.

BACKGROUND AND PURPOSE: Deriving accurate language lateralization from fMRI studies in the clinical context can be difficult, with 10%–20% incorrect conclusions. Most interpretations are qualitative, performed by neuroimaging experts. Quantitative lateralization has been widely described but with little implementation in the clinical setting and is disadvantaged by the use of arbitrary threshold techniques. We investigated the application and utility of a nonthreshold CLI, in a clinical setting, as applied by a group of practicing neuroradiologists. MATERIALS AND METHODS: Twenty-two patients with known language lateralization (11 left and 11 nonleft dominant) had their images reviewed by 8 neuroradiologists in 2 settings, all randomized, once by using a CLI and once without using a CLI. For each review, neuroradiologists recorded their impressions of lateralization for each language sequence, the overall lateralization conclusion, their impression of scan quality and noise, and the subjective confidence in their conclusion. RESULTS: The inter-rater κ for lateralization was 0.64, which increased to 0.70 with the use of CLI. The group accuracy of overall lateralization was 78%, which increased to 81% with the use of a CLI. Using a CLI removed 2 instances of significant errors, with a neuroradiologists impression of left lateralization in a patient with known right lateralization. Using a CLI had no effect on examinations with conclusions formed with either high confidence or no confidence. CONCLUSIONS: Although the overall clinical benefit of a CLI is modest, the most significant impact is to reduce the most harmful misclassification errors, particularly in fMRI examinations that are suboptimal.

Effect of a prescan patient-radiologist encounter on functional MR image quality.

BACKGROUND AND PURPOSE: A substantial number of clinical fMRI examinations inadequately assess language localization or lateralization, usually due to patient movement and suboptimal participation. We hypothesized that a prescan interview of the patient by the radiologist would reduce the fraction of nondiagnostic scans. MATERIALS AND METHODS: A single noise score for each acquisition was produced from time-series data on the basis of a weighted sum of 22 factors. Scores were recorded as the following quartiles: 0–5 = excellent, 5–10 = adequate, 10–15= marginal, and >15 = unacceptable. This measure was evaluated for 202 consecutive fMRI patients: 96 without and 106 with a physician prescan interview. The data were analyzed to compute the fraction of all nondiagnostic sequences and entire studies and were compared between the 2 groups. Image-noise characteristics included the SDs of linear and angular displacements of the head and the number of time-series outliers caused by focal motion. RESULTS: Of 999 sequences acquired, 539 had a prescan interview. The mean noise score significantly decreased for both individual sequence (from 7.9 to 6.3, P = <.001) and study-based (from 7.7 to 6.2, P = .05) methods. The fraction of sequences or studies scored as unacceptable decreased for sequence-based (from 15.2% to 10.9%, P = .04) and study-based (from 9.4% to 1.9%, P = .02) analyses. SDs of head motion decreased for linear (by 12%–14%, P < .01) and angular displacement (by 38%–48%, P < .001). The number of time-series spikes decreased by 10% (P = .004). CONCLUSIONS: We report that a prescan physician-patient interview modestly but significantly reduces fMRI noise scores. These results support the newly added billable costs of professional intervention before fMRI scans.