Conventional MRI provides important information for diagnosis and prognosis of patients with multiple sclerosis (MS) and for monitoring efficacy of treatments.1 White matter lesions (WML) show pathologically heterogeneous patterns of demyelination2 and a wide range of altered T1 values3. Quantifying damage to CNS tissue in MS patients could improve understanding of development and progress of the disease. Quantitative MRI techniques have not entered clinical routine due to limited availability of rapid acquisition techniques. One method addressing this fact is the compressed sensing magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence4,5, providing 3D T1 mapping. Alterations of qT1 reflect tissue demyelination, axonal loss, edema, and chronic inflammation that are hallmarks of disease-related pathology.
Goal of this study was to introduce a clinically interpretable marker of tissue destruction: the proposed marker aims at capturing the different degrees of qT1 change within lesions and normal-appearing white matter (NAWM).

Methods
Demographics and MR protocol
n=47 MS patients (Table 1) were scanned at 3T (Siemens MAGNETOM Prisma). Conventional T1-weighted MP-RAGE and 3D T2-weighted FLAIR images and a compressed sensing MP2RAGE research application sequence, which allows whole-brain 1mm isotropic T1 mapping in 3:20 minutes, were acquired (Table 2).
Image processing and statistics
The research application Morphobox6 was used to derive segmentation masks of brain tissues from MPRAGE images, and MS lesions were segmented on FLAIR images using a deep neural network trained on weak labels7 and fine-tuned on manual annotations. A mask for NAWM was generated by removing segmented lesions from the WM mask.
Atlases of reference T1 values for healthy brain tissues were established following 8,9. Voxel-based assessment of T1 alterations were estimated by means of z-scores, i.e., number of standard deviations away from age-/sex-matched reference mean values. Average absolute T1-z-scores were computed in NAWM and lesions. Voxels with a z-score of 2 or higher were considered deficient. The ratio of deficient voxel in the investigated tissue (i.e., NAWM or lesions) was defined as deficient volume fraction (DVF)10
Finally, Spearman correlation coefficients were calculated between T1-z-scores (NAWM or lesions) and EDSS, using a significance level of 0.05.
Results
Different lesion-morphological patterns using T1-z-scores are displayed in Figure 1. T1-z-scores allow to detect different degrees of tissue change as opposed to signal intensity in the appearance of the conventional FLAIR lesions. Figure 1 shows that individual lesion z-scores can be highly variable between lesions. The z-score distribution within lesions was either homogeneous (Figure 1A) or heterogeneous with higher z-score values in the center (Figure 1B).
Figure 2 shows the distribution of individual lesion T1-z scores.. Mean z-score in WML was 2.5 (SD 2.4).
34% of WMLs had a z-score less than 1, suggesting that for this proportion of lesions the T1 is within the range of the normative controls. The distribution of z-scores within lesions allowed comparison of variability within and between patients.
For the entire cohort, mean DVF in the NAWM was 5.6% (SD 5.9%), ranging from 0.4% to 24.7% and mean DVF in WML was 14.4% (SD 16.8%), ranging from 0.5% to 67.0%. The correlation between DVF in the NAWM and WML tissue compartments with EDSS was (r = 0.24, p = 0.11) vs. (r = 0.32, p = 0.027), as shown in Figure 3.
Discussion and Conclusion
The rapid acquisition of CS-MP2RAGE permits T1-mapping to be incorporated into clinical imaging and allows the detection of NAWM damage and severity of focal lesion damage. We identified patterns regarding extent and heterogeneity of damage within and around the lesion. 49.5% of the lesions had a mean T1-z-score greater than 2, reflecting detectable tissue damage. In contrast, tissue integrity was preserved in 34% of lesions with no or little T1 change. Capturing individual lesion T1-z-scores provides insights into the intra- and inter-patient variability of tissue destruction. T1 mapping allows the definition of a marker of tissue destruction burden (i.e., DVF). The inter-individual DVF range reflects highly variable WM involvement among patients. The weak association of DVF in WML with the EDSS score may be explained by the small sample size and unbalanced number of patients with high EDSS score in our cohort.

Cutoff z-scores defining evident tissue destruction are not yet established but are critical for clinical application11. DVF could be an easily interpretable and comparable score to quantify tissue damage across patients.