title: A quantitative microscopic approach to predict local recurrence based on in vivo intraoperative imaging of sarcoma tumor margins.
abstract: The goal of resection of soft tissue sarcomas located in the extremity is to preserve limb function while completely excising the tumor with a margin of normal tissue. With surgery alone, one-third of patients with soft tissue sarcoma of the extremity will have local recurrence due to microscopic residual disease in the tumor bed. Currently, a limited number of intraoperative pathology-based techniques are used to assess margin status; however, few have been widely adopted due to sampling error and time constraints. To aid in intraoperative diagnosis, we developed a quantitative optical microscopy toolbox, which includes acriflavine staining, fluorescence microscopy, and analytic techniques called sparse component analysis and circle transform to yield quantitative diagnosis of tumor margins. A series of variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82 and 75%. The utility of this approach was tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78 and 82%. For comparison, if pathology was used to predict local recurrence in this data set, it would achieve a sensitivity of 29% and a specificity of 71%. These results indicate a robust approach for detecting microscopic residual disease, which is an effective predictor of local recurrence.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina.
authors.forename: Jenna L
authors.initials: JL
authors.lastname: Mueller
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina.
authors.forename: Henry L
authors.initials: HL
authors.lastname: Fu
authors.affiliation: Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, North Carolina.
authors.forename: Jeffrey K
authors.initials: JK
authors.lastname: Mito
authors.affiliation: Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, North Carolina.
authors.forename: Melodi J
authors.initials: MJ
authors.lastname: Whitley
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina.
authors.forename: Rhea
authors.initials: R
authors.lastname: Chitalia
authors.affiliation: Department of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina.
authors.forename: Alaattin
authors.initials: A
authors.lastname: Erkanli
authors.affiliation: Department of Pathology, University of North Carolina School of Medicine, Chapel Hill, North Carolina.
authors.forename: Leslie
authors.initials: L
authors.lastname: Dodd
authors.affiliation: Department of Pathology, Duke University Medical Center, Durham, North Carolina.
authors.forename: Diana M
authors.initials: DM
authors.lastname: Cardona
authors.affiliation: Department of Pathology, Duke University Medical Center, Durham, North Carolina.
authors.forename: Joseph
authors.initials: J
authors.lastname: Geradts
authors.affiliation: Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin.
authors.forename: Rebecca M
authors.initials: RM
authors.lastname: Willett
authors.affiliation: Department of Pharmacology & Cancer Biology, Duke University School of Medicine, Durham, North Carolina.|Department of Radiation Oncology, Duke University School of Medicine, Durham, North Carolina.
authors.forename: David G
authors.initials: DG
authors.lastname: Kirsch
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina.
authors.forename: Nimmi
authors.initials: N
authors.lastname: Ramanujam
mesh_terms: D000818:Animals; D001859:Bone Neoplasms / Q000473:pathology / Q000601:surgery*; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007430:Intraoperative Care; D051379:Mice; D018365:Neoplasm, Residual / Q000175:diagnosis*; D011446:Prospective Studies; D012509:Sarcoma / Q000473:pathology / Q000601:surgery*; D012680:Sensitivity and Specificity
keywords: image analysis; intraoperative imaging; logistic models; optical fluorescence imaging; soft tissue sarcoma