@article{MTMT:1654413,
	title = {Lesion probability mapping to explain clinical deficits and cognitive performance in multiple sclerosis},
	url = {https://m2.mtmt.hu/api/publication/1654413},
	author = {Kincses, Zsigmond Tamás and Ropele, S and Jenkinson, M and Khalil, M and Petrovic, K and Loitfelder, M and Langkammer, C and Aspeck, E and Wallner-Blazek, M and Fuchs, S and Jehna, M and Schmidt, R and Vécsei, László and Fazekas, F and Enzinger, C},
	doi = {10.1177/1352458510391342},
	journal-iso = {MULT SCLER J},
	journal = {MULTIPLE SCLEROSIS JOURNAL},
	volume = {17},
	unique-id = {1654413},
	issn = {1352-4585},
	abstract = {Background: Lesion dissemination in time and space represents a key feature and diagnostic marker of multiple sclerosis (MS). The correlation between magnetic resonance imaging (MRI) lesion load and disability is only modest, however. Strategic lesion location might at least partially account for this 'clinico-radiologic paradox'. Objectives: Here we used a non-parametric permutation-based approach to map lesion location probability based on MS lesions identified on T2-weighted MRI. We studied 121 patients with clinically isolated syndrome, relapsing-remitting or secondary progressive MS and correlated these maps to assessments of neurologic and cognitive functions. Results: The Expanded Disability Status Scale correlated with bilateral periventricular lesion location (LL), and sensory and coordination functional system deficits correlated with lesion accumulation in distinct anatomically plausible regions, i.e. thalamus and middle cerebellar peduncule. Regarding cognitive performance, decreased verbal fluency correlated with left parietal LL comprising the putative superior longitudinal fascicle. Delayed spatial recall correlated with _amygdalar, _left frontal and parietal LL. Delayed selective reminding correlated with bilateral frontal and temporal LL. However, only part of the spectrum of cognitive and neurological problems encountered in our cohort could be explained by specific lesion location. Conclusions: Lesion probability mapping supports the association of specific lesion locations with symptom development in MS, but only to limited extent.},
	keywords = {IMPAIRMENT; HUMAN BRAIN; Neuropsychological tests; cognition; MATTER; MULTIPLE SCLEROSIS; CARD SORTING TEST; disability; MRI; MRI PARAMETERS; NORMATIVE VALUES; FRONTAL-LOBE LESIONS; BRIEF REPEATABLE BATTERY; NEOCORTICAL VOLUME DECREASE; verbal fluency; lesion symptom mapping},
	year = {2011},
	eissn = {1477-0970},
	pages = {681-689},
	orcid-numbers = {Kincses, Zsigmond Tamás/0000-0002-1442-4475; Vécsei, László/0000-0001-8037-3672}
}

@article{MTMT:2568970,
	title = {Statistical validation of image segmentation quality based on a spatial overlap index.},
	url = {https://m2.mtmt.hu/api/publication/2568970},
	author = {Zou, KH and Warfield, SK and Bharatha, A and Tempany, CM and Kaus, MR and Haker, SJ and Wells, WM III and Jolesz, Ferenc and Kikinis, R},
	doi = {10.1016/S1076-6332(03)00671-8},
	journal-iso = {ACAD RADIOL},
	journal = {ACADEMIC RADIOLOGY},
	volume = {11},
	unique-id = {2568970},
	issn = {1076-6332},
	abstract = {RATIONALE AND OBJECTIVES: To examine a statistical validation method based on the spatial overlap between two sets of segmentations of the same anatomy. MATERIALS AND METHODS: The Dice similarity coefficient (DSC) was used as a statistical validation metric to evaluate the performance of both the reproducibility of manual segmentations and the spatial overlap accuracy of automated probabilistic fractional segmentation of MR images, illustrated on two clinical examples. Example 1: 10 consecutive cases of prostate brachytherapy patients underwent both preoperative 1.5T and intraoperative 0.5T MR imaging. For each case, 5 repeated manual segmentations of the prostate peripheral zone were performed separately on preoperative and on intraoperative images. Example 2: A semi-automated probabilistic fractional segmentation algorithm was applied to MR imaging of 9 cases with 3 types of brain tumors. DSC values were computed and logit-transformed values were compared in the mean with the analysis of variance (ANOVA). RESULTS: Example 1: The mean DSCs of 0.883 (range, 0.876-0.893) with 1.5T preoperative MRI and 0.838 (range, 0.819-0.852) with 0.5T intraoperative MRI (P < .001) were within and at the margin of the range of good reproducibility, respectively. Example 2: Wide ranges of DSC were observed in brain tumor segmentations: Meningiomas (0.519-0.893), astrocytomas (0.487-0.972), and other mixed gliomas (0.490-0.899). CONCLUSION: The DSC value is a simple and useful summary measure of spatial overlap, which can be applied to studies of reproducibility and accuracy in image segmentation. We observed generally satisfactory but variable validation results in two clinical applications. This metric may be adapted for similar validation tasks.},
	keywords = {Male; *Magnetic Resonance Imaging; Humans; *Data Interpretation, Statistical; Retrospective Studies; Analysis of Variance; Reproducibility of Results; Brain Neoplasms/*pathology; Prostatic Neoplasms/*pathology},
	year = {2004},
	eissn = {1878-4046},
	pages = {178-189}
}