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1.
Skeletal Radiol ; 50(1): 79-85, 2021 Jan.
Article in English | MEDLINE | ID: mdl-32621061

ABSTRACT

OBJECTIVE: To determine association of body composition measurements on CT and PET with progression of smoldering myeloma to multiple myeloma. METHODS: A retrospective cohort study in 65 patients with smoldering myeloma and PET/CT at diagnosis was performed at a tertiary cancer center. Subjects were between 38 and 87 years of age (mean 64) and included 37 males. Primary outcome was progression-free survival as a function of bone, fat, and muscle metrics on CT and PET (measured at the level of L4 pedicles) and clinical confounders. CT metrics included attenuation of L4 and retroperitoneal fat and various indices derived from the psoas muscle. PET measures included SUVmax and SUVmean of L4, retroperitoneal fat, and psoas. Cox proportional hazards modeling was performed with entry and retention criteria of p < 0.1 and p < 0.05, respectively. RESULTS: SUVmax and SUVmean were associated for each compartment (R2 = 0.78-0.84), and SUVmean (SUV) was used for subsequent analyses. SUV of the L4 vertebral body was associated with attenuation of the L4 vertebral body (p = 0.0032). There was no association between SUV and CT for muscle and fat compartments. In the subset of patients with bone marrow biopsy results (n = 43), there was no association between SUV of L4 and plasma cell concentration on core biopsy or flow cytometry (p = 0.089 and 0.072, respectively). The final Cox model showed association with albumin (HR 0.29, 95%CI 0.088-0.93, p = 0.038), M protein (HR 1.31, 95%CI 1.021-1.68, p = 0.034), and SUV of L4 (HR 1.99, 95%CI 1.037-3.82, p = 0.039). CONCLUSION: SUV of L4 is a prognostic indicator in patients with smoldering myeloma.


Subject(s)
Fluorodeoxyglucose F18 , Multiple Myeloma , Bone Marrow , Humans , Male , Multimodal Imaging , Multiple Myeloma/diagnostic imaging , Positron Emission Tomography Computed Tomography , Positron-Emission Tomography , Radiopharmaceuticals , Retrospective Studies
2.
J Surg Res ; 208: 26-32, 2017 02.
Article in English | MEDLINE | ID: mdl-27993214

ABSTRACT

BACKGROUND: Unplanned excision of soft tissue sarcomas (STS) is an important quality of care issue given the morbidity related to tumor bed excision. Since not all patients harbor residual disease at the time of reexcision, we sought to determine predictors of residual STS following unplanned excision. METHODS: We identified 76 patients from a prospective database (January 1, 2008-September 30, 2014) who received a diagnosis of primary STS following unplanned excision on the trunk or extremities. We used univariable and multivariable analyses to evaluate predictors of residual STS as the primary endpoint. We calculated the sensitivity, specificity, and accuracy of interval magnetic resonance imaging (MRI) to predict residual sarcoma at reexcision. RESULTS: Mean age was 52 y, and 63.2% were male. 50% had fragmented unplanned excision. Among patients undergoing reexcision, residual STS was identified in 70%. On univariable analysis, MRI showing gross disease and fragmented excision were significant predictors of residual STS (odds ratio, 10.59; 95% CI, 2.14-52.49; P = 0.004 and odds ratio, 3.61; 95% CI, 1.09-11.94; P = 0.035, respectively). On multivariable analysis, tumor size predicted distant recurrence and overall survival. When we combined equivocal and positive MRI, the sensitivity and specificity of MRI for predicting residual STS were 86.7% (95% CI, 73.2%-95.0%) and 57.9% (95% CI, 33.5%-79.8%), with an overall accuracy of 78.1% (95% CI, 66.0%-87.5%). CONCLUSIONS: About 70% of patients undergoing repeat excision after unplanned excision of STS harbor residual sarcoma. Although interval MRI and fragmented excision appear to be the most significant predictors of residual STS, the accuracy of MRI remains modest, especially given the incidence of equivocal MRI.


Subject(s)
Margins of Excision , Sarcoma/surgery , Soft Tissue Neoplasms/surgery , Adolescent , Adult , Aged , Aged, 80 and over , Child , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Neoplasm, Residual , Proportional Hazards Models , Sarcoma/diagnostic imaging , Soft Tissue Neoplasms/diagnostic imaging , Young Adult
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