Association of MRI T2 Signal Intensity With Desmoid Tumor Progression During Active Observation: A Retrospective Cohort Study.


Journal

Annals of surgery
ISSN: 1528-1140
Titre abrégé: Ann Surg
Pays: United States
ID NLM: 0372354

Informations de publication

Date de publication:
04 2020
Historique:
pubmed: 13 11 2018
medline: 5 6 2020
entrez: 13 11 2018
Statut: ppublish

Résumé

The aim of this study was to identify predictors of desmoid progression during observation. Untreated desmoids can grow, remain stable, or regress, but reliable predictors of behavior have not been identified. Primary or recurrent desmoid patients were identified retrospectively from an institutional database. In those managed with active observation who underwent serial magnetic resonance imaging (MRIs) with T2-weighted sequences, baseline tumor size was recorded, and 2 radiologists independently estimated the percentage of tumor volume showing hyperintense T2 signal at baseline. Associations of clinical or radiographic characteristics with progression-free survival (PFS; by RECIST) were evaluated by Cox regression and Kaplan-Meier statistics. Among 160 patients with desmoids, 72 were managed with observation, and 37 of these had serial MRI available for review. Among these 37 patients, median age was 35 years and median tumor size was 4.7 cm; all tumors were extra-abdominal (41% in abdominal wall). Although PFS was not associated with size, site, or age, it was strongly associated with hyperintense T2 signal in ≥90% versus <90% of baseline tumor volume (as defined by the "test" radiologist; hazard ratio = 11.3, P = 0.003). For patients in the ≥90% group (n = 20), 1-year PFS was 55%, compared with 94% in the <90% group (n = 17). The percentage of baseline tumor volume with hyperintense T2 signal defined by a validation radiologist correlated with results of the test radiologist (ρ = 0.75). The percent tumor volume characterized by hyperintense T2 signal is associated with desmoid progression during observation and may help distinguish patients who would benefit from early intervention from those who may be reliably observed.

Sections du résumé

OBJECTIVE
The aim of this study was to identify predictors of desmoid progression during observation.
SUMMARY OF BACKGROUND DATA
Untreated desmoids can grow, remain stable, or regress, but reliable predictors of behavior have not been identified.
METHODS
Primary or recurrent desmoid patients were identified retrospectively from an institutional database. In those managed with active observation who underwent serial magnetic resonance imaging (MRIs) with T2-weighted sequences, baseline tumor size was recorded, and 2 radiologists independently estimated the percentage of tumor volume showing hyperintense T2 signal at baseline. Associations of clinical or radiographic characteristics with progression-free survival (PFS; by RECIST) were evaluated by Cox regression and Kaplan-Meier statistics.
RESULTS
Among 160 patients with desmoids, 72 were managed with observation, and 37 of these had serial MRI available for review. Among these 37 patients, median age was 35 years and median tumor size was 4.7 cm; all tumors were extra-abdominal (41% in abdominal wall). Although PFS was not associated with size, site, or age, it was strongly associated with hyperintense T2 signal in ≥90% versus <90% of baseline tumor volume (as defined by the "test" radiologist; hazard ratio = 11.3, P = 0.003). For patients in the ≥90% group (n = 20), 1-year PFS was 55%, compared with 94% in the <90% group (n = 17). The percentage of baseline tumor volume with hyperintense T2 signal defined by a validation radiologist correlated with results of the test radiologist (ρ = 0.75).
CONCLUSION
The percent tumor volume characterized by hyperintense T2 signal is associated with desmoid progression during observation and may help distinguish patients who would benefit from early intervention from those who may be reliably observed.

Identifiants

pubmed: 30418203
doi: 10.1097/SLA.0000000000003073
pmc: PMC6736761
mid: NIHMS1048932
pii: 00000658-202004000-00024
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

748-755

Subventions

Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA140146
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA217694
Pays : United States

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Auteurs

Michael R Cassidy (MR)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Section of Surgical Oncology, Boston University School of Medicine, Boston, MA.

Robert A Lefkowitz (RA)

Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.

Niamh Long (N)

Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY.

Li-Xuan Qin (LX)

Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.

Amanda Kirane (A)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.

Eman Sbaity (E)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.

Meera Hameed (M)

Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.

Daniel G Coit (DG)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Department of Surgery, Weill Cornell Medical Center, New York, NY.

Murray F Brennan (MF)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Department of Surgery, Weill Cornell Medical Center, New York, NY.

Samuel Singer (S)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Department of Surgery, Weill Cornell Medical Center, New York, NY.

Aimeé M Crago (AM)

Gastric and Mixed Tumor Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
Department of Surgery, Weill Cornell Medical Center, New York, NY.

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Classifications MeSH