Estimating Brain Lesion Volume Change in Multiple Sclerosis by Subtraction of Magnetic Resonance Images

Real-World Validation of Coregistration and Structured Reporting for Magnetic Resonance Imaging Monitoring in Multiple Sclerosis

OBJECTIVE

The objectives of this research were to assess the effectiveness of computer-assisted detection reading (CADR) and structured reports in monitoring patients with multiple sclerosis (MS) and to evaluate the role of radiology technicians in this context.

METHODS

Eighty-seven patients with MS who underwent at least 2 sequential magnetic resonance imaging (MRI) follow-ups analyzed by 2 radiologists and a technician. Progression of disease (POD) was identified through the emergence of T2 fluid-attenuated inversion recovery white matter hyperintensities or contrast enhancements and evaluated both qualitatively (progression vs stability) and quantitatively (count of new white matter hyperintensities).

RESULTS

CADR increased the accuracy by 11%, enhancing interobserver consensus on qualitative progression and saving approximately 2 minutes per examination. Although structured reports did not improve these metrics, it may improve clinical communication and permit technicians to achieve approximately 80% accuracy in MRI readings.

CONCLUSIONS

The use of CADR improves the accuracy, agreement, and interpretation time in MRI follow-ups of MS. With the help of computer tools, radiology technicians could represent a significant aid in the follow-up of these patients.

Magnetic resonance imaging subtraction vs. pre- and post-contrast 3D gradient recalled echo fat suppressed imaging for evaluation of the canine and feline brain

Subtraction magnetic resonance imaging (MRI) has been reported to increase accuracy in the diagnosis of meningeal and inflammatory brain diseases in small animals. 3D T1W gradient recalled echo (GRE) techniques have been proposed as a suitable alternative to conventional spin echo sequences in imaging the canine brain. The aim of this study was to compare subtraction images and paired pre- and post-contrast 3D T1W GRE fat suppressed (FS) images in canine and feline MRI studies using clinical diagnosis as the gold standard. Paired pre- and post-contrast T1W 3D FS GRE images and individual subtraction images of 100 small animal patients were randomized and independently evaluated by 2 blinded observers. Diagnosis categories were "normal," "inflammatory," "neoplastic," and "other." Clinical diagnosis was made in the same categories and served as the gold standard. Image interpretation results were compared to the clinical diagnosis. Interobserver agreement was determined. Clinically, 41 studies were categorized as "normal," 18 as "inflammatory," 28 as "neoplastic," and 13 as "other." The agreement of the pre- and post-contrast GRE images with the gold standard was significantly higher than that of the subtraction images (k = 0.7491 vs. k = 0.5924; p = 0.0075). The largest sources of error were misinterpretation of "other" as "normal" and "normal" as "inflammatory." There was no significant difference between the two observers (p = 0.8820). Based on this study, subtraction images do not provide an advantage to paired pre- and post-contrast FS GRE images when evaluating the canine and feline brain.

Neuroimaging lesion assessment by pseudo-subtraction of overlaid semi-transparent volumes: A technical description and feasibility series

Assessing and reporting clinical images constitutes the mainstay of clinical neuroradiology. Continually increasing numbers of neuroradiology referrals and follow-up examinations call for reproducible, accurate, and rapid workflows. Readily available and easy to use, advanced workstation tools such as co-registration of volume series can be used to overlay volume series from two different time points as semi-transparent images, with an inverse color scale. By overlaying semi-transparent inverse color maps, stationary findings will be shaded out in grey, whereas progressing or regressing lesions will be highlighted as white or black in the resulting pseudo-subtraction map. Pseudosubtraction in longitudinal neuroradiology imaging might enhance workflow and imaging assessment.

Follow-up MRI in multiple sclerosis patients: automated co-registration and lesion color-coding improves diagnostic accuracy and reduces reading time

OBJECTIVES

In multiple sclerosis (MS), the heterogeneous and numerous appearances of lesions may impair diagnostic accuracy. This study investigates if a combined automated co-registration and lesion color-coding method (AC) improves assessment of MS follow-up MRI compared with conventional reading (CR).

METHODS

We retrospectively assessed 70 follow-up MRI of 53 patients. Heterogeneous datasets of diverse scanners and institutions were used. Two readers determined presence of (a) progression, (b) regression, (c) mixed change, or (d) stable disease between the two examinations using corresponding FLAIR sequences in CR and AC-assisted reading. Consensus reference reading was provided by two blinded radiologists. Kappa statistics tested interrater agreement, McNemar's test dichotomous variables, and Wilcoxon's test continuous variables (statistical significance p ≤ 0.05).

RESULTS

The cohort comprised 41 female and 12 male patients with a mean age of 40 (± 14) years. Average rating time was reduced from 78 (± 36) to 44 (±22) s with the AC approach (p < 0.001). The time needed to start and match datasets with AC was 14 (± 1) s. Compared with CR, AC improved interrater agreement, both between raters (0.52 vs. 0.67) and between raters and consensus reference reading (0.47/0.5 vs. 0.83/0.78). Compared with CR, the diagnostic accuracy increased from 67 to 90% (reader 1, p < 0.01) and from 70 to 87% (reader 2, p < 0.05) in the AC-assisted reading.

CONCLUSIONS

Compared with CR, automated co-registration and lesion color-coding of MS-associated FLAIR-lesions in follow-up MRI increased diagnostic accuracy and reduced the time required for follow-up evaluation significantly. The AC algorithm therefore appears to be helpful to improve MS follow-up assessments in clinical routine.

KEY POINTS

• Automated co-registration and lesion color-coding increases diagnostic accuracy in the assessment of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding reduces reading time of MRI follow-up examinations in patients with multiple sclerosis. • Automated co-registration and lesion color-coding improved interrater agreement in the assessment of MRI follow-up examinations in patients with multiple sclerosis.

Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method

BACKGROUND AND PURPOSE

MR imaging is the key examination in the follow-up of patients with MS, by identification of new high-signal T2 brain lesions. However, identifying new lesions when scrolling through 2 follow-up MR images can be difficult and time-consuming. Our aim was to compare an automated coregistration-fusion reading approach with the standard approach by identifying new high-signal T2 brain lesions in patients with multiple sclerosis during follow-up MR imaging.

MATERIALS AND METHODS

This prospective monocenter study included 94 patients (mean age, 38.9 years) treated for MS with dimethyl fumarate from January 2014 to August 2016. One senior neuroradiologist and 1 junior radiologist checked for new high-signal T2 brain lesions, independently analyzing blinded image datasets with automated coregistration-fusion or the standard scroll-through approach with a 3-week delay between the 2 readings. A consensus reading with a second senior neuroradiologist served as a criterion standard for analyses. A Poisson regression and logistic and γ regressions were used to compare the 2 methods. Intra- and interobserver agreement was assessed by the κ coefficient.

RESULTS

There were significantly more new high-signal T2 lesions per patient detected with the coregistration-fusion method (7 versus 4, P < .001). The coregistration-fusion method detected significantly more patients with at least 1 new high-signal T2 lesion (59% versus 46%, P = .02) and was associated with significantly faster overall reading time (86 seconds faster, P < .001) and higher reader confidence (91% versus 40%, P < 1 × 10^-4). Inter- and intraobserver agreement was excellent for counting new high-signal T2 lesions.

CONCLUSIONS

Our study showed that an automated coregistration-fusion method was more sensitive for detecting new high-signal T2 lesions in patients with MS and reducing reading time. This method could help to improve follow-up care.

Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions

Purpose

To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new lesions and discriminates between enhancing and nonenhancing lesions in multiple sclerosis (MS).

Methods

Thirty three MS patients who had MRIs at two different time points with at least one new Gd-enhancing lesion on the 2nd MRI were included in the study. For a reference standard, new lesions were identified by two neuroradiologists on T2w and post-Gd T1w images with the help of T2w + SDC. The diagnostic accuracy of the proposed method based on QSM and T2w + SDC lesion detection (T2w + SDC + QSM) for assessing lesion enhancement status was determined. Receiver operating characteristic (ROC) analysis was performed to compute the optimal lesion susceptibility cutoff value.

Results

A total of 165 new lesions (54 enhancing, 111 nonenhancing) were identified. The sensitivity and specificity of T2w + SDC + QSM in predicting lesion enhancement status were 90.7% and 85.6%, respectively. For lesions ≥50 mm³, ROC analysis showed an optimal QSM cutoff value of 13.5 ppb with a sensitivity of 88.4% and specificity of 88.6% (0.93, 95% CI, 0.87–0.99). For lesions ≥15 mm³, the optimal QSM cutoff was 15.4 ppb with a sensitivity of 77.9% and specificity of 94.0% (0.93, 95% CI, 0.89–0.97).

Conclusion

The proposed T2w + SDC + QSM method is highly accurate for identifying and predicting the enhancement status of new MS lesions without the use of Gd injection.

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T2w + SDC has high sensitivity and accuracy in detecting new MS lesions.

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T2w + SDC + QSM is highly accurate in discriminating between new enhancing and new nonenhancing lesions.

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T2w + SDC + QSM can form the basis of an imaging protocol without Gadolinium injection for routine surveillance of MS patients.

T1w dark blood imaging improves detection of contrast enhancing lesions in multiple sclerosis

PURPOSE

In multiple sclerosis (MS) the sensitivity for detection of contrast enhancing lesions (CEL) in T1-weighted scans is essential for diagnostics and therapy decisions. The purpose of our study was to evaluate the sensitivity of T1w MPRAGE scans in comparison to T1w dark blood technique (T1-DB) for CEL in MS.

MATERIALS AND METHODS

3T MR imaging was performed in 37 MS patients, including T2-weighted imaging, T1w MPRAGE before and after gadolinium injection (unenhanced-T1 and T1-CE) and T1-DB imaging. After gadolinium application, the T1-DB scan was performed prior to T1-CE. From unenhanced-T1 and T1-CE scans, subtraction images (T1-SUB) were calculated. The number of CEL was determined separately on T1-CE and T1-DB by two raters independently. Lesions only detected on T1-DB scans then were verified on T1-SUB. Only lesions detected by both raters were included in further analysis.

RESULTS

In 16 patients, at least one CEL was detected by both rater, either on T1-CE or T1-DB. All lesions that were detected on T1-CE were also detected on T1-DB images. The total number of contrast enhancing lesions detected on T1-DB images (n = 54) by both raters was significantly higher than the corresponding number of lesions identified on T1-CE (n = 27) (p = 0.01); all of these lesions could be verified on SUB images. In 21 patients, no CEL was detected in any of the sequences.

CONCLUSIONS

The application of T1-DB technique increases the sensitivity for CEL in MS, especially for those lesions that show only subtle increase in intensity after Gadolinium application but remain hypo- or iso-intense to surrounding tissue.

Detection of Focal Longitudinal Changes in the Brain by Subtraction of MR Images

BACKGROUND AND PURPOSE

The detection of new subtle brain pathology on MR imaging is a time-consuming and error-prone task for the radiologist. This article introduces and evaluates an image-registration and subtraction method for highlighting small changes in the brain with a view to minimizing the risk of missed pathology and reducing fatigue.

MATERIALS AND METHODS

We present a fully automated algorithm for highlighting subtle changes between multiple serially acquired brain MR images with a novel approach to registration and MR imaging bias field correction. The method was evaluated for the detection of new lesions in 77 patients undergoing cardiac surgery, by using pairs of fluid-attenuated inversion recovery MR images acquired 1-2 weeks before the operation and 6-8 weeks postoperatively. Three radiologists reviewed the images.

RESULTS

On the basis of qualitative comparison of pre- and postsurgery FLAIR images, radiologists identified 37 new ischemic lesions in 22 patients. When these images were accompanied by a subtraction image, 46 new ischemic lesions were identified in 26 patients. After we accounted for interpatient and interradiologist variability using a multilevel statistical model, the likelihood of detecting a lesion was 2.59 (95% CI, 1.18-5.67) times greater when aided by the subtraction algorithm (P = .017). Radiologists also reviewed the images significantly faster (P < .001) by using the subtraction image (mean, 42 seconds; 95% CI, 29-60 seconds) than through qualitative assessment alone (mean, 66 seconds; 95% CI, 46-96 seconds).

CONCLUSIONS

Use of this new subtraction algorithm would result in considerable savings in the time required to review images and in improved sensitivity to subtle focal pathology.