Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology
Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ito, Kotaro [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Anmerkung: |
© The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Oral radiology - Heidelberg : Springer, 1985, 38(2021), 3 vom: 29. Juli, Seite 315-324 |
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| Übergeordnetes Werk: |
volume:38 ; year:2021 ; number:3 ; day:29 ; month:07 ; pages:315-324 |
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| DOI / URN: |
10.1007/s11282-021-00558-y |
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SPR047290064 |
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| 245 | 1 | 0 | |a Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology |
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| 520 | |a Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. | ||
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| 700 | 1 | |a Andreu-Arasa, V. Carlota |4 aut | |
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| 700 | 1 | |a Kaneda, Takashi |4 aut | |
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10.1007/s11282-021-00558-y doi (DE-627)SPR047290064 (SPR)s11282-021-00558-y-e DE-627 ger DE-627 rakwb eng Ito, Kotaro verfasserin (orcid)0000-0002-1177-8331 aut Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 Kondo, Takumi aut Andreu-Arasa, V. Carlota aut Li, Baojun aut Hirahara, Naohisa aut Muraoka, Hirotaka aut Sakai, Osamu aut Kaneda, Takashi aut Enthalten in Oral radiology Heidelberg : Springer, 1985 38(2021), 3 vom: 29. Juli, Seite 315-324 (DE-627)392236508 (DE-600)2157096-6 1613-9674 nnns volume:38 year:2021 number:3 day:29 month:07 pages:315-324 https://dx.doi.org/10.1007/s11282-021-00558-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2021 3 29 07 315-324 |
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10.1007/s11282-021-00558-y doi (DE-627)SPR047290064 (SPR)s11282-021-00558-y-e DE-627 ger DE-627 rakwb eng Ito, Kotaro verfasserin (orcid)0000-0002-1177-8331 aut Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 Kondo, Takumi aut Andreu-Arasa, V. Carlota aut Li, Baojun aut Hirahara, Naohisa aut Muraoka, Hirotaka aut Sakai, Osamu aut Kaneda, Takashi aut Enthalten in Oral radiology Heidelberg : Springer, 1985 38(2021), 3 vom: 29. Juli, Seite 315-324 (DE-627)392236508 (DE-600)2157096-6 1613-9674 nnns volume:38 year:2021 number:3 day:29 month:07 pages:315-324 https://dx.doi.org/10.1007/s11282-021-00558-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2021 3 29 07 315-324 |
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10.1007/s11282-021-00558-y doi (DE-627)SPR047290064 (SPR)s11282-021-00558-y-e DE-627 ger DE-627 rakwb eng Ito, Kotaro verfasserin (orcid)0000-0002-1177-8331 aut Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 Kondo, Takumi aut Andreu-Arasa, V. Carlota aut Li, Baojun aut Hirahara, Naohisa aut Muraoka, Hirotaka aut Sakai, Osamu aut Kaneda, Takashi aut Enthalten in Oral radiology Heidelberg : Springer, 1985 38(2021), 3 vom: 29. Juli, Seite 315-324 (DE-627)392236508 (DE-600)2157096-6 1613-9674 nnns volume:38 year:2021 number:3 day:29 month:07 pages:315-324 https://dx.doi.org/10.1007/s11282-021-00558-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2021 3 29 07 315-324 |
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10.1007/s11282-021-00558-y doi (DE-627)SPR047290064 (SPR)s11282-021-00558-y-e DE-627 ger DE-627 rakwb eng Ito, Kotaro verfasserin (orcid)0000-0002-1177-8331 aut Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 Kondo, Takumi aut Andreu-Arasa, V. Carlota aut Li, Baojun aut Hirahara, Naohisa aut Muraoka, Hirotaka aut Sakai, Osamu aut Kaneda, Takashi aut Enthalten in Oral radiology Heidelberg : Springer, 1985 38(2021), 3 vom: 29. Juli, Seite 315-324 (DE-627)392236508 (DE-600)2157096-6 1613-9674 nnns volume:38 year:2021 number:3 day:29 month:07 pages:315-324 https://dx.doi.org/10.1007/s11282-021-00558-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2021 3 29 07 315-324 |
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10.1007/s11282-021-00558-y doi (DE-627)SPR047290064 (SPR)s11282-021-00558-y-e DE-627 ger DE-627 rakwb eng Ito, Kotaro verfasserin (orcid)0000-0002-1177-8331 aut Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 Kondo, Takumi aut Andreu-Arasa, V. Carlota aut Li, Baojun aut Hirahara, Naohisa aut Muraoka, Hirotaka aut Sakai, Osamu aut Kaneda, Takashi aut Enthalten in Oral radiology Heidelberg : Springer, 1985 38(2021), 3 vom: 29. Juli, Seite 315-324 (DE-627)392236508 (DE-600)2157096-6 1613-9674 nnns volume:38 year:2021 number:3 day:29 month:07 pages:315-324 https://dx.doi.org/10.1007/s11282-021-00558-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 38 2021 3 29 07 315-324 |
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Ito, Kotaro @@aut@@ Kondo, Takumi @@aut@@ Andreu-Arasa, V. Carlota @@aut@@ Li, Baojun @@aut@@ Hirahara, Naohisa @@aut@@ Muraoka, Hirotaka @@aut@@ Sakai, Osamu @@aut@@ Kaneda, Takashi @@aut@@ |
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Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. 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Ito, Kotaro |
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Ito, Kotaro misc Computed tomography misc Maxillary sinus misc Maxillary sinusitis misc Odontogenic maxillary sinusitis Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology |
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Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology Computed tomography (dpeaa)DE-He213 Maxillary sinus (dpeaa)DE-He213 Maxillary sinusitis (dpeaa)DE-He213 Odontogenic maxillary sinusitis (dpeaa)DE-He213 |
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Ito, Kotaro Kondo, Takumi Andreu-Arasa, V. Carlota Li, Baojun Hirahara, Naohisa Muraoka, Hirotaka Sakai, Osamu Kaneda, Takashi |
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quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology |
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Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology |
| abstract |
Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 |
| abstractGer |
Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 |
| abstract_unstemmed |
Objectives The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). Methods Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann–Whitney U test. Results Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. Conclusions CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices. © The Author(s), under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology and Springer Nature Singapore Pte Ltd. 2021 |
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Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology |
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Kondo, Takumi Andreu-Arasa, V. Carlota Li, Baojun Hirahara, Naohisa Muraoka, Hirotaka Sakai, Osamu Kaneda, Takashi |
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Kondo, Takumi Andreu-Arasa, V. Carlota Li, Baojun Hirahara, Naohisa Muraoka, Hirotaka Sakai, Osamu Kaneda, Takashi |
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| score |
7.401311 |