File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1097/MNM.0000000000000005
- Scopus: eid_2-s2.0-84887231443
- PMID: 24100443
- WOS: WOS:000326574800007
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value
Title | Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value |
---|---|
Authors | |
Keywords | uterine sarcoma standardized uptake value PET/CT leiomyosarcoma carcinosarcoma |
Issue Date | 2013 |
Publisher | Lippincott 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? |
Abstract | OBJECTIVE: 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 Identifier | http://hdl.handle.net/10722/193174 |
ISSN | 2023 Impact Factor: 1.3 2023 SCImago Journal Rankings: 0.374 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, EYP | en_US |
dc.contributor.author | Khong, PL | en_US |
dc.contributor.author | Tse, KY | en_US |
dc.contributor.author | Chan, KKL | en_US |
dc.contributor.author | Chu, MMY | en_US |
dc.contributor.author | Ngan, HYS | en_US |
dc.date.accessioned | 2013-12-20T02:29:05Z | - |
dc.date.available | 2013-12-20T02:29:05Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.citation | Nuclear Medicine Communications, 2013, v. 34 n. 12, p. 1185-1189 | en_US |
dc.identifier.issn | 0143-3636 | - |
dc.identifier.uri | http://hdl.handle.net/10722/193174 | - |
dc.description.abstract | OBJECTIVE: 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.language | eng | en_US |
dc.publisher | Lippincott Williams & Wilkins. The Journal's web site is located at http://www.nuclearmedicinecomm.com | - |
dc.relation.ispartof | Nuclear Medicine Communications | en_US |
dc.subject | uterine sarcoma | - |
dc.subject | standardized uptake value | - |
dc.subject | PET/CT | - |
dc.subject | leiomyosarcoma | - |
dc.subject | carcinosarcoma | - |
dc.title | Differentiation of aggressive and indolent subtypes of uterine sarcoma using maximum standardized uptake value | en_US |
dc.type | Article | en_US |
dc.identifier.email | Lee, EYP: eyplee77@hku.hk | en_US |
dc.identifier.email | Khong, PL: plkhong@hkucc.hku.hk | en_US |
dc.identifier.email | Tse, KY: tseky@hkucc.hku.hk | en_US |
dc.identifier.email | Chan, KKL: kklchan@hkucc.hku.hk | en_US |
dc.identifier.email | Ngan, HYS: hysngan@hkucc.hku.hk | en_US |
dc.identifier.authority | Lee, EYP=rp01456 | en_US |
dc.identifier.authority | Khong, PL=rp00467 | en_US |
dc.identifier.authority | Chan, KKL=rp00499 | en_US |
dc.identifier.authority | Ngan, HYS=rp00346 | en_US |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1097/MNM.0000000000000005 | - |
dc.identifier.pmid | 24100443 | - |
dc.identifier.pmcid | PMC3815224 | - |
dc.identifier.scopus | eid_2-s2.0-84887231443 | - |
dc.identifier.hkuros | 226899 | en_US |
dc.identifier.hkuros | 236918 | - |
dc.identifier.volume | 34 | en_US |
dc.identifier.issue | 12 | - |
dc.identifier.spage | 1185 | en_US |
dc.identifier.epage | 1189 | en_US |
dc.identifier.isi | WOS:000326574800007 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0143-3636 | - |