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Research Paper
Medical Hyperspectral Imaging to Facilitate Residual Tumor Identification During Surgery
Svetlana V. Panasyuk, Shi Yang, Douglas V. Faller, Duyen Ngo, Robert A. Lew, Jenny E. Freeman and Adrianne E. Rogers
volume 6 | issue 3
March 2007Pages: 439 - 446
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Introduction: Adequate evaluation of breast tumor resection at surgery continues to be
an important issue in surgical care, as over 30% of postoperative tumors recur locally
unless radiation is used to destroy remaining tumor cells in the field. Medical
Hyperspectral Imaging (MHSI) delivers near-real time images of biomarkers in tissue,
providing an assessment of pathophysiology and the potential to distinguish different
tissues based on spectral characteristics.
Method: We have used an experimental DMBA-induced rat breast tumor model to
examine the intraoperative utility of MHSI, in distinguishing tumor from normal breast
and other tissues. Rats bearing tumors underwent surgical exposure and MHSI imaging,
followed by partial resection of the tumors, then MHSI imaging of the resection bed, and
finally total resection of tumors and of grossly normal-appearing glands. Resected tissue
underwent gross examination, MHSI imaging, and histopathological evaluation.
Results: An algorithm based on spectral characteristics of tissue types was developed
to distinguish between tumor and normal tissues. Tissues including tumor, blood
vessels, muscle, and connective tissue were clearly identified and differentiated by
MHSI. Fragments of residual tumor 0.5 - 1 mm in size intentionally left in the operative
bed were readily identified. MHSI demonstrated a sensitivity of 89% and a specificity of
94% for detection of residual tumor, comparable to that of histopathological examination
of the tumor bed (85% and 92%, respectively).
Conclusion: We conclude that MHSI may be useful in identifying small residual tumor
in a tumor resection bed and for indicating areas requiring more extensive resection and
more effective biopsy locations to the surgeon.
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We now provide open access to journal articles published online for one year or more. This article may be downloaded at the following link:
Download PDFIf the document does not open, please right-click on the link (control-click on a Macintosh) and select the option to save the file to disk.