MRI Follow‐up of Astrocytoma: Automated Coregistration and Color‐Coding of FLAIR Sequences Improves Diagnostic Accuracy With Comparable Reading Time

Abstract

Background MRI follow‐up is widely used for longitudinal assessment of astrocytoma, yet reading can be tedious and error‐prone, in particular when changes are subtle. Purpose/Hypothesis To determine the effect of automated, color‐coded coregistration (AC) of fluid attenuated inversion recovery (FLAIR) sequences on diagnostic accuracy, certainty, and reading time compared to conventional follow‐up MRI assessment of astrocytoma patients. Study Type Retrospective. Population In all, 41 patients with neuropathologically confirmed astrocytoma. Field Strength/Sequence 1.0–3.0T/FLAIR Assessment The presence or absence of tumor progression was determined based on FLAIR sequences, contrast‐enhanced T1 sequences, and clinical data. Three radiologists assessed 47 MRI study pairs in a conventional reading (CR) and in a second reading supported by AC after 6 weeks. Readers determined the presence/absence of tumor progression and indicated diagnostic certainty on a 5‐point Likert scale. Reading time was recorded by an independent assessor. Statistical Tests The Wilcoxon test was used to assess reading time and diagnostic certainty. Differences in diagnostic accuracy, sensitivity, and specificity were analyzed with the McNemar mid‐p test. Results Readers attained significantly higher overall sensitivity (0.86 vs. 0.75; P < 0.05) and diagnostic accuracy (0.84 vs. 0.73; P < 0.05) for detection of progressive nonenhancing tumor burden when using AC compared to CR. There was a strong trend towards higher specificity within the AC‐augmented reading, yet without statistical significance (0.83 vs. 0.71; P = 0.08). Sensitivity for unequivocal disease progression was similarly high in both approaches (AC: 0.94, CR: 0.92), while for marginal disease progressions, it was significantly higher in AC (AC: 0.78, CR: 0.58; P < 0.05). Reading time including application loading time was comparable (AC: 38.1 ± 16.8 sec, CR: 36.0 ± 18.9 s; P = 0.25). Data Conclusion Compared to CR, AC improves comparison of FLAIR signal hyperintensity at MRI follow‐up of astrocytoma patients, allowing for a significantly higher diagnostic accuracy, particularly for subtle disease progression at a comparable reading time. Evidence Level 3 Technical Efficacy Stage 6 J. Magn. Reson. Imaging 2020;52:1197–1206.

Automated Color-Coding of Lesion Changes in Contrast-Enhanced 3D T1-Weighted Sequences for MRI Follow-up of Brain Metastases

“…In our study, we found a higher overall reading time including application loading times when using the ACC software, a finding that contrasts with previous studies reporting comparable or shorter reading times with this software. 15,16 While the shorter time required for the readout itself is in line with previous studies, the overall higher assessment time we found is most likely because we used 3D image acquisitions, which require higher processing power. The time required for loading and processing the images for ACC is certainly, in part, dependent on the computing power of the workstation and servers used.…”

“…Our results are in line with previous studies investigating different software using similar concepts of automated coregistration and highlighting of lesion changes as well as studies using the same software for longitudinal evaluation of lesion changes in FLAIR images. 13,15,16,18 Galletto Pregliasco et al 15 found a higher sensitivity and subjective confidence in the detection of new lesions on MR imaging of patients with multiple sclerosis using automated coregistration and a colored overlay map to depict lesion development. Lennartz et al 16 reported a higher sensitivity and diagnostic accuracy for the longitudinal assessment of astrocytomas in FLAIR sequences, in particular for subtle changes.…”

“…13,15,16,18 Galletto Pregliasco et al 15 found a higher sensitivity and subjective confidence in the detection of new lesions on MR imaging of patients with multiple sclerosis using automated coregistration and a colored overlay map to depict lesion development. Lennartz et al 16 reported a higher sensitivity and diagnostic accuracy for the longitudinal assessment of astrocytomas in FLAIR sequences, in particular for subtle changes. Compared with astrocytomas, the assessment of brain metastases may be much more challenging and burdensome, particularly when there are a high number of lesions.…”

“…[13][14][15] Other studies applied similar techniques to the neuro-oncologic followup of patients with astrocytomas and high-grade gliomas. [16][17][18] On the basis of these previous results, our hypothesis was that application of ACC at the follow-up assessment of brain metastases would yield comparable diagnostic benefits. Therefore, the purpose of this study was to compare the assessment of gadoliniumenhanced, 3D T1-weighted MR imaging follow-up examinations of patients with brain metastases between a conventional reading approach and an approach using ACC.…”

Subtraction Maps Derived from Longitudinal Magnetic Resonance Imaging in Patients with Glioma Facilitate Early Detection of Tumor Progression

“…Despite an evident need for compensation strategies, recent high innovation on the MRI technology side and related demands remain mostly unanswered by diagnostic image assessment, which is still widely based on simple visual reading. In keeping with this imbalance, we are aware of only one previous study for neurooncological imaging that evaluated an approach based on SMs that was seamlessly integrated in the routine setting [32]. However, in this previous retrospective study, a smaller cohort consisting of 41 patients with different entities of glioma was considered, and these patients were scanned with various, inhomogeneous MRI protocols on various scanners from different manufacturers, with field strengths of scanners ranging between 1 and 3 Tesla [32].…”