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Article: Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value

TitleDifferentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value
Authors
Keywordsuterine sarcoma
standardized uptake value
PET/CT
leiomyosarcoma
carcinosarcoma
Issue Date2013
PublisherLippincott Williams & Wilkins. The Journal's web site is located at http://www.nuclearmedicinecomm.com
Citation
Nuclear Medicine Communications, 2013, v. 34 n. 12, p. 1185-1189 How to Cite?
AbstractOBJECTIVE: The aim of the study was to elucidate the differential metabolic activities in aggressive and indolent subtypes of uterine sarcomas, which may aid in managing these heterogeneous tumours. METHODS: We retrospectively analysed the PET/computed tomography scans of consecutive patients (N=18) diagnosed with uterine sarcoma at our unit. The patients were divided into indolent (N=4) and aggressive (N=14) tumour groups, and the maximum standardized uptake values (SUVmax) of all lesions (n=134) were measured. The SUVmax of the lesions were compared between the two tumour groups using the Mann-Whitney U-test. We calculated the optimal cutoff value as determined by receiver operating characteristic analysis. A P-value less than 0.05 was considered statistically significant. RESULTS: The mean SUVmax of aggressive (n=104) and indolent tumours (n=30) were significantly different (8.0±7.3 vs. 1.9±0.9 respectively; P < 0.001). A cutoff of SUVmax greater than 4.0 was able to exclude indolent tumours, with 100% specificity and positive predictive value (sensitivity 72%, negative predictive value 50% and accuracy 78%; area under the curve 97%). By applying this same cutoff value on the most metabolic active lesion in each patient, we were able to correctly classify all but one patient into either the aggressive or indolent tumour group with 100% specificity and positive predictive value (sensitivity 93%, negative predictive value 80% and accuracy 94%). CONCLUSION: Aggressive and indolent uterine sarcoma subtypes have differential metabolic activities that can be used to classify them and this can aid in patient management for preoperative surgical planning and treatment stratification. © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins.
Persistent Identifierhttp://hdl.handle.net/10722/193174
ISSN
2015 Impact Factor: 1.453
2015 SCImago Journal Rankings: 0.690
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLee, EYPen_US
dc.contributor.authorKhong, PLen_US
dc.contributor.authorTse, KYen_US
dc.contributor.authorChan, KKLen_US
dc.contributor.authorChu, MMYen_US
dc.contributor.authorNgan, HYSen_US
dc.date.accessioned2013-12-20T02:29:05Z-
dc.date.available2013-12-20T02:29:05Z-
dc.date.issued2013en_US
dc.identifier.citationNuclear Medicine Communications, 2013, v. 34 n. 12, p. 1185-1189en_US
dc.identifier.issn0143-3636-
dc.identifier.urihttp://hdl.handle.net/10722/193174-
dc.description.abstractOBJECTIVE: The aim of the study was to elucidate the differential metabolic activities in aggressive and indolent subtypes of uterine sarcomas, which may aid in managing these heterogeneous tumours. METHODS: We retrospectively analysed the PET/computed tomography scans of consecutive patients (N=18) diagnosed with uterine sarcoma at our unit. The patients were divided into indolent (N=4) and aggressive (N=14) tumour groups, and the maximum standardized uptake values (SUVmax) of all lesions (n=134) were measured. The SUVmax of the lesions were compared between the two tumour groups using the Mann-Whitney U-test. We calculated the optimal cutoff value as determined by receiver operating characteristic analysis. A P-value less than 0.05 was considered statistically significant. RESULTS: The mean SUVmax of aggressive (n=104) and indolent tumours (n=30) were significantly different (8.0±7.3 vs. 1.9±0.9 respectively; P < 0.001). A cutoff of SUVmax greater than 4.0 was able to exclude indolent tumours, with 100% specificity and positive predictive value (sensitivity 72%, negative predictive value 50% and accuracy 78%; area under the curve 97%). By applying this same cutoff value on the most metabolic active lesion in each patient, we were able to correctly classify all but one patient into either the aggressive or indolent tumour group with 100% specificity and positive predictive value (sensitivity 93%, negative predictive value 80% and accuracy 94%). CONCLUSION: Aggressive and indolent uterine sarcoma subtypes have differential metabolic activities that can be used to classify them and this can aid in patient management for preoperative surgical planning and treatment stratification. © 2013 Wolters Kluwer Health | Lippincott Williams & Wilkins.-
dc.languageengen_US
dc.publisherLippincott Williams & Wilkins. The Journal's web site is located at http://www.nuclearmedicinecomm.com-
dc.relation.ispartofNuclear Medicine Communicationsen_US
dc.subjectuterine sarcoma-
dc.subjectstandardized uptake value-
dc.subjectPET/CT-
dc.subjectleiomyosarcoma-
dc.subjectcarcinosarcoma-
dc.titleDifferentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake valueen_US
dc.typeArticleen_US
dc.identifier.emailLee, EYP: eyplee77@hku.hken_US
dc.identifier.emailKhong, PL: plkhong@hkucc.hku.hken_US
dc.identifier.emailTse, KY: tseky@hkucc.hku.hken_US
dc.identifier.emailChan, KKL: kklchan@hkucc.hku.hken_US
dc.identifier.emailNgan, HYS: hysngan@hkucc.hku.hken_US
dc.identifier.authorityLee, EYP=rp01456en_US
dc.identifier.authorityKhong, PL=rp00467en_US
dc.identifier.authorityChan, KKL=rp00499en_US
dc.identifier.authorityNgan, HYS=rp00346en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1097/MNM.0000000000000005-
dc.identifier.pmid24100443-
dc.identifier.pmcidPMC3815224-
dc.identifier.scopuseid_2-s2.0-84887231443-
dc.identifier.hkuros226899en_US
dc.identifier.hkuros236918-
dc.identifier.volume34en_US
dc.identifier.issue12-
dc.identifier.spage1185en_US
dc.identifier.epage1189en_US
dc.identifier.isiWOS:000326574800007-
dc.publisher.placeUnited States-

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