دورية أكاديمية
أعرض في EDS

Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study.

التفاصيل البيبلوغرافية
العنوان: Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study.
المؤلفون: Liu J; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA., Jakary A; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA., Villanueva-Meyer JE; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA., Butowski NA; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA., Saloner D; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.; Radiology Service, VA Medical Center, San Francisco, CA 94121, USA., Clarke JL; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.; Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA., Taylor JW; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.; Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA., Oberheim Bush NA; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.; Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA., Chang SM; Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA., Xu D; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.; UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA., Lupo JM; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA.; UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA.
المصدر: Cancers [Cancers (Basel)] 2024 Apr 17; Vol. 16 (8). Date of Electronic Publication: 2024 Apr 17.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101526829 Publication Model: Electronic Cited Medium: Print ISSN: 2072-6694 (Print) Linking ISSN: 20726694 NLM ISO Abbreviation: Cancers (Basel) Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI
مستخلص: This study aimed to develop a rapid, 1 mm 3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t -test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types ( p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.
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معلومات مُعتمدة: R21CA238137 United States NH NIH HHS
فهرسة مساهمة: Keywords: automatic lesion detection; gliomas; macromolecular proton fraction; multi-contrast; multi-parametric mapping; two-compartment model
تواريخ الأحداث: Date Created: 20240427 Latest Revision: 20240429
رمز التحديث: 20240429
مُعرف محوري في PubMed: PMC11049314
DOI: 10.3390/cancers16081524
PMID: 38672606
قاعدة البيانات: MEDLINE
الوصف
تدمد:2072-6694
DOI:10.3390/cancers16081524