TY - JOUR
T1 - Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery
AU - Gong, Peijun
AU - Chin, Synn Lynn
AU - Allen, Wes M.
AU - Ballal, Helen
AU - Anstie, James D.
AU - Chin, Lixin
AU - Ismail, Hina M.
AU - Zilkens, Renate
AU - Lakhiani, Devina D.
AU - McCarthy, Matthew
AU - Fang, Qi
AU - Firth, Daniel
AU - Newman, Kyle
AU - Thomas, Caleb
AU - Li, Jiayue
AU - Sanderson, Rowan W.
AU - Foo, Ken Y.
AU - Yeomans, Chris
AU - Dessauvagie, Benjamin F.
AU - Latham, Bruce
AU - Saunders, Christobel M.
AU - Kennedy, Brendan F.
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld QME probe, designed to interrogate the surgical cavity, can detect residual cancer directly in the breast cavity in vivo during BCS. In a first-in-human study, 21 BCS patients were scanned in vivo with the QME probe by five surgeons. For validation, protocols were developed to coregister in vivo QME with postoperative histopathology of the resected tissue to assess the capability of QME to identify residual cancer. In four cavity aspects presenting cancer and 21 cavity aspects presenting benign tissue, QME detected elevated stiffness in all four cancer cases, in contrast to low stiffness observed in 19 of the 21 benign cases. The results indicate that in vivo QME can identify residual cancer by directly imaging the surgical cavity, potentially providing a reliable intraoperative solution that can enable more complete cancer excision during BCS.
AB - Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld QME probe, designed to interrogate the surgical cavity, can detect residual cancer directly in the breast cavity in vivo during BCS. In a first-in-human study, 21 BCS patients were scanned in vivo with the QME probe by five surgeons. For validation, protocols were developed to coregister in vivo QME with postoperative histopathology of the resected tissue to assess the capability of QME to identify residual cancer. In four cavity aspects presenting cancer and 21 cavity aspects presenting benign tissue, QME detected elevated stiffness in all four cancer cases, in contrast to low stiffness observed in 19 of the 21 benign cases. The results indicate that in vivo QME can identify residual cancer by directly imaging the surgical cavity, potentially providing a reliable intraoperative solution that can enable more complete cancer excision during BCS.
UR - http://www.scopus.com/inward/record.url?scp=85141888832&partnerID=8YFLogxK
U2 - 10.1158/0008-5472.CAN-22-0578
DO - 10.1158/0008-5472.CAN-22-0578
M3 - Article
C2 - 36098983
AN - SCOPUS:85141888832
SN - 0008-5472
VL - 82
SP - 4093
EP - 4104
JO - Cancer Research
JF - Cancer Research
IS - 21
ER -