Semiautomatic regional segmentation to measure orbital fat volumes in thyroid-associated ophthalmopathy. A validation study (656 views) (PDF restricted 265 views)
Neuroradiol J (ISSN: 1971-4009, 1971-4009print, 1971-4009linking), 2013 Aug; 26(4): 373-379.
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Paper type: Journal Article, Clinical Trial, Validation Studies
Impact factor: 2.16, 5-year impact factor: 2.304
Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-84884711917&partnerID=40&md5=61e04db53b2edda52d151d2887c8bf4f
Keywords: Graves, Orbitopathy, Mri Segmentation, Orbital Quadrant Definition, Regional Orbital Fat Quantification, Semiautomatic Numeric Segmentation, Validation, Adipose Tissue, Adult, Article, Clinical Article, Controlled Study, Endocrine Ophthalmopathy, Female, Graves Disease, Human, Measurement, Nuclear Magnetic Resonance Imaging, Validation Study, Exophthalmos, Graves Ophthalmopathy, Middle Aged, Reproducibility Of Results, Adipose Tissue Pathology, Exophthalmos Pathology, Graves Ophthalmopathy Pathology, Magnetic Resonance Imaging Methods Standards, Orbit Pathology, Graves' Orbitopathy
Affiliations:
*** IBB - CNR ***
Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
Department of Advanced Biomedical Sciences, Neuroradiology, Federico II University, Naples, Italy
Department of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II University, Naples, Italy
Naples, Italy - marco. comerci@ibb. cnr. it.
Consiglio Nazionale delle Ricerche
Universita degli Studi di Napoli Federico II
References:
Not available.
Neuroradiol J (ISSN: 1971-4009, 1971-4009print, 1971-4009linking), 2013 Aug; 26(4): 373-379.
Export to BibTeX Export to EndNote
Paper type: Journal Article, Clinical Trial, Validation Studies
Impact factor: 2.16, 5-year impact factor: 2.304
Url: http://www.scopus.com/inward/record.url?eid=2-s2.0-84884711917&partnerID=40&md5=61e04db53b2edda52d151d2887c8bf4f
Keywords: Graves, Orbitopathy, Mri Segmentation, Orbital Quadrant Definition, Regional Orbital Fat Quantification, Semiautomatic Numeric Segmentation, Validation, Adipose Tissue, Adult, Article, Clinical Article, Controlled Study, Endocrine Ophthalmopathy, Female, Graves Disease, Human, Measurement, Nuclear Magnetic Resonance Imaging, Validation Study, Exophthalmos, Graves Ophthalmopathy, Middle Aged, Reproducibility Of Results, Adipose Tissue Pathology, Exophthalmos Pathology, Graves Ophthalmopathy Pathology, Magnetic Resonance Imaging Methods Standards, Orbit Pathology, Graves' Orbitopathy
Affiliations:
*** IBB - CNR ***
Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
Department of Advanced Biomedical Sciences, Neuroradiology, Federico II University, Naples, Italy
Department of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II University, Naples, Italy
Naples, Italy - marco. comerci@ibb. cnr. it.
Consiglio Nazionale delle Ricerche
Universita degli Studi di Napoli Federico II
References:
Not available.
Semiautomatic regional segmentation to measure orbital fat volumes in thyroid-associated ophthalmopathy. A validation study
This study was designed to validate a novel semi-automated segmentation method to measure regional intra-orbital fat tissue volume in Graves' ophthalmopathy. Twenty-four orbits from 12 patients with Graves' ophthalmopathy, 24 orbits from 12 controls, ten orbits from five MRI study simulations and two orbits from a digital model were used. Following manual region of interest definition of the orbital volumes performed by two operators with different levels of expertise, an automated procedure calculated intra-orbital fat tissue volumes (global and regional, with automated definition of four quadrants). In patients with Graves' disease, clinical activity score and degree of exophthalmos were measured and correlated with intra-orbital fat volumes. Operator performance was evaluated and statistical analysis of the measurements was performed. Accurate intra-orbital fat volume measurements were obtained with coefficients of variation below 5\\%. The mean operator difference in total fat volume measurements was 0.56\\%. Patients had significantly higher intra-orbital fat volumes than controls (p<0.001 using Student's t test). Fat volumes and clinical score were significantly correlated (p<0.001). The semi-automated method described here can provide accurate, reproducible intra-orbital fat measurements with low inter-operator variation and good correlation with clinical data.
This study was designed to validate a novel semi-automated segmentation method to measure regional intra-orbital fat tissue volume in Graves' ophthalmopathy. Twenty-four orbits from 12 patients with Graves' ophthalmopathy, 24 orbits from 12 controls, ten orbits from five MRI study simulations and two orbits from a digital model were used. Following manual region of interest definition of the orbital volumes performed by two operators with different levels of expertise, an automated procedure calculated intra-orbital fat tissue volumes (global and regional, with automated definition of four quadrants). In patients with Graves' disease, clinical activity score and degree of exophthalmos were measured and correlated with intra-orbital fat volumes. Operator performance was evaluated and statistical analysis of the measurements was performed. Accurate intra-orbital fat volume measurements were obtained with coefficients of variation below 5\\%. The mean operator difference in total fat volume measurements was 0.56\\%. Patients had significantly higher intra-orbital fat volumes than controls (p<0.001 using Student's t test). Fat volumes and clinical score were significantly correlated (p<0.001). The semi-automated method described here can provide accurate, reproducible intra-orbital fat measurements with low inter-operator variation and good correlation with clinical data.
Semiautomatic regional segmentation to measure orbital fat volumes in thyroid-associated ophthalmopathy. A validation study
| ▼ Relaxometry based MRI limb segmentation |
| ▼ Software development of digital MRI brain phantom |
Semiautomatic regional segmentation to measure orbital fat volumes in thyroid-associated ophthalmopathy. A validation study
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Quarantelli M
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Eur Radiol (ISSN: 0938-7994linking), 2023 Nov 17; N/D: N/D-N/D.
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Le Moli R, Muscia V, Tumminia A, Frittitta L, Buscema M, Palermo F, Sciacca L, Squatrito S, Vigneri R
* Type 2 diabetic patients with Graves' disease have more frequent and severe Graves' orbitopathy (992 views)
Nutrition (ISSN: 0939-4753, 1590-3729electronic), 2015; 25(5): 452-457.
Impact Factor: 3.39
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* Searching for the grail: may machine learning be a road to clinical use of brain MRI segmentation? (0 views)
Eur Radiol (ISSN: 0938-7994linking), 2023 Nov 17; N/D: N/D-N/D.
Impact Factor:
View Export to BibTeX Export to EndNote
Le Moli R, Muscia V, Tumminia A, Frittitta L, Buscema M, Palermo F, Sciacca L, Squatrito S, Vigneri R
* Type 2 diabetic patients with Graves' disease have more frequent and severe Graves' orbitopathy (992 views)
Nutrition (ISSN: 0939-4753, 1590-3729electronic), 2015; 25(5): 452-457.
Impact Factor: 3.39
View Export to BibTeX Export to EndNote
2 Records (2 excluding Abstracts).
Total impact factor: 3.39 (3.39 excluding Abstracts).
Total 5 year impact factor: 3.451 (3.451 excluding Abstracts).
Total impact factor: 3.39 (3.39 excluding Abstracts).
Total 5 year impact factor: 3.451 (3.451 excluding Abstracts).
656 views. Last view on Friday 13 September 2024, 15:08:32
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