Campeau, Norbert

Abstract Functional MRI (fMRI) is widely used to spatially localize neural activity in the brain associated with functional stimuli. Functional MR Elastography (fMRE) has recently been introduced as a complementary approach that measures the mechanical response to functional stimulus. The hypothesis of the current study is that the stiffness change in fMRE is proportional to the underlying neural activity. This hypothesis is tested by measuring the median stiffness change in the visual cortex as a function of luminance-matched contrast intensity of a checkerboard visual stimulus in 16 healthy subjects. The fMRE signal in the visual cortex was observed to be proportional to the contrast intensity of the visual stimulus. In regions of activation, fMRE signal increased in the range of 2 ± 1% to 5.8 ± 1% and fMRI signal increased by the expected 0.4 ± 0.2% to 0.9 ± 0.2%, for contrast levels of 5% to 100%, respectively. In conclusion, this study shows that the fMRE signal in the visual cortex can be directly modulated by the contrast intensity of a visual stimulus. The presence of some overlap between fMRI and fMRE regions of activation may suggest two distinct mechanisms governing the fMRI and fMRE signals, which will be investigated in future studies.

Abstract Purpose To demonstrate T 2 ‐weighted (single‐echo) spin‐echo (SE) imaging with near‐optimal acquisition efficiency by applying SNR‐efficient RF slice encoding and spiral readout. Methods A quadratic‐phase (frequency swept) excitation RF pulse replaced the conventional excitation in T 2 ‐weighted SE sequence to excite a thick slab that is internally spatially encoded by a variable phase along the slice direction. Highly overlapping slabs centered at every desired slice location were acquired in multiple passes, such that the entire imaging volume was excited by contiguous slabs in any given pass. Following 90° excitation, each slab was refocused with a conventional 180° RF to produce a SE signal, followed by a spiral in‐out readout. A noise‐insensitive reconstruction removed the quadratic phase in the spatial frequency domain, yielding desired slice resolution and improved SNR. Results Increasing the RF frequency sweep (hence, excitation width) allowed more frequent encoding of each slice over the multiple passes, improving final image SNR, until crosstalk ensued at excessive slab widths compared to their center‐to‐center spacing. With an optimized slab width, the proposed technique used all passes to acquire every prescribed slice, with substantially improved SNR over conventional SE or 2D‐turbo‐spin‐echo (TSE) scans. Quantitative SNR measurements indicated similar SNR as 3D‐TSE, but radiologist scoring favored 3D‐TSE, mainly because of spiral‐related artifacts and possibly because of regularized reconstructions in 3D‐TSE. Conclusion Using SNR‐efficient slice excitation scheme and spiral readout helped eliminate SNR and temporal inefficiencies in conventional T 2 ‐weighted imaging, yielding SNR independent of TR or number of passes.

Background Computed tomography (CT) angiography collateral score (CTA-CS) is an important clinical outcome predictor following mechanical thrombectomy for ischemic stroke with large vessel occlusion (LVO). The present multireader study aimed to evaluate the performance of e-CTA software for automated assistance in CTA-CS scoring. Materials and Methods Brain CTA images of 56 patients with anterior LVO were retrospectively processed. Twelve readers of various clinical training, including junior neuroradiologists, senior neuroradiologists, and neurologists graded collateral flow using visual CTA-CS scale in two sessions separated by a washout period. Reference standard was the consensus of three expert readers. Duration of reading time, inter-rater reliability, and statistical comparison of readers’ performance metrics were analyzed between the e-CTA assisted and unassisted sessions. Results e-CTA assistance resulted in significant increase in mean accuracy (58.6% to 67.5%, p = 0.003), mean F1 score (0.574 to 0.676, p = 0.002), mean precision (58.8% to 68%, p = 0.007), and mean recall (58.7% to 69.9%, p = 0.002), especially with slight filling deficit (CTA-CS 2 and 3). Mean reading time was reduced across all readers (103.4 to 59.7 s, p = 0.001), and inter-rater agreement in CTA-CS assessment was increased (Krippendorff's alpha 0.366 to 0.676). Optimized occlusion laterality detection was also noted with mean accuracy (92.9% to 96.8%, p = 0.009). Conclusion Automated assistance for CTA-CS using e-CTA software provided helpful decision support for readers in terms of improving scoring accuracy and reading efficiency for physicians with a range of experience and training backgrounds and leading to significant improvements in inter-rater agreement.

Introduction There is increased interest in the use of artificial intelligence-based (AI) software packages in the evaluation of neuroimaging studies for acute ischemic stroke. We studied whether, compared to standard image interpretation without AI, Brainomix e-ASPECTS software improved interobserver agreement and accuracy in detecting ASPECTS regions affected in anterior circulation LVO. Methods We included 60 consecutive patients with anterior circulation LVO who had TICI 3 revascularization within 60 minutes of their baseline CT. A total of 16 readers, including senior neuroradiologists, junior neuroradiologists and vascular neurologists participated. Readers interpreted CT scans on independent workstations and assessed final ASPECTS and evaluated whether each individual ASPECTS region was affected. Two months later, readers again evaluated the CT scans, but with assistance of e-ASPECTS software. We assessed interclass correlation coefficient for total ASPECTS and interobserver agreement with Fleiss’ Kappa for each ASPECTS region with and without assistance of the e-ASPECTS. We also assessed accuracy for the readers with and without e-ASPECTS assistance. In our assessment of accuracy, ground truth was the 24 hour CT in this cohort of patients who had prompt and complete revascularization. Results Interclass correlation coefficient for total ASPECTS without e-ASPECTS assistance was 0.395, indicating fair agreement compared, to 0.574 with e-ASPECTS assistance, indicating good agreement (P < 0.01). There was significant improvement in inter-rater agreement with e-ASPECTS assistance for each individual region with the exception of M6 and caudate. The e-ASPECTS software had higher accuracy than the overall cohort of readers (with and without e-ASPECTS assistance) for every region except the caudate. Conclusions Use of Brainomix e-ASPECTS software resulted in significant improvements in inter-rater agreement and accuracy of ASPECTS score evaluation in a large group of neuroradiologists and neurologists. e-ASPECTS software was more predictive of final infarct/ASPECTS than the overall group interpreting the CT scans with and without e-ASPECTS assistance.