A Feasibility Study Assessing Quantitative Indocyanine Green Angiographic Predictors of Reconstructive Complications Following Nipple-sparing Mastectomy

Overview

Journal JPRAS Open

Specialty General Surgery

Date 2024 Mar 1

PMID 38425697

Authors

J Dalli

C L Nguyen

A Jindal

J P Epperlein

N P Hardy

C Pulitano

S Warrier

R A Cahill

Affiliations

Soon will be listed here.

Abstract

Introduction: Immediate post-mastectomy breast reconstruction offers benefits; however, complications can compromise outcomes. Intraoperative indocyanine green fluorescence angiography (ICGFA) may mitigate perfusion-related complications (PRC); however, its interpretation remains subjective. Here, we examine and develop methods for ICGFA quantification, including machine learning (ML) algorithms for predicting complications.

Methods: ICGFA video recordings of flap perfusion from a previous study of patients undergoing nipple-sparing mastectomy (NSM) with either immediate or staged immediate (delayed by a week due to perfusion insufficiency) reconstructions were analysed. Fluorescence intensity time series data were extracted, and perfusion parameters were interrogated for overall/regional associations with postoperative PRC. A naïve Bayes ML model was subsequently trained on a balanced data subset to predict PRC from the extracted meta-data.

Results: The analysable video dataset of 157 ICGFA featured females (average age 48 years) having oncological/risk-reducing NSM with either immediate (n=90) or staged immediate (n=26) reconstruction. For those delayed, peak brightness at initial ICGFA was lower (p<0.001) and significantly improved (both quicker-onset and brighter p=0.001) one week later. The overall PRC rate in reconstructed patients (n=116) was 11.2%, with such patients demonstrating significantly dimmer (overall, p=0.018, centrally, p=0.03, and medially, p=0.04) and slower-onset (p=0.039) fluorescent peaks with shallower slopes (p=0.012) than uncomplicated patients with ICGFA. Importantly, such relevant parameters were converted into a whole field of view heatmap potentially suitable for intraoperative display. ML predicted PRC with 84.6% sensitivity and 76.9% specificity.

Conclusion: Whole breast quantitative ICGFA assessment reveals statistical associations with PRC that are potentially exploitable via ML.

References

Reintgen C, Leavitt A, Pace E, Molas-Pierson J, Mast B . Risk Factor Analysis for Mastectomy Skin Flap Necrosis: Implications for Intraoperative Vascular Analysis. Ann Plast Surg. 2016; 76 Suppl 4:S336-9. DOI: 10.1097/SAP.0000000000000740. View

Mandrekar J . Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010; 5(9):1315-6. DOI: 10.1097/JTO.0b013e3181ec173d. View

Yoon A, Qi J, Brown D, Kim H, Hamill J, Erdmann-Sager J . Outcomes of immediate versus delayed breast reconstruction: Results of a multicenter prospective study. Breast. 2017; 37:72-79. PMC: 5902735. DOI: 10.1016/j.breast.2017.10.009. View

Hardy N, Dalli J, Khan M, Andrejevic P, Neary P, Cahill R . Inter-user variation in the interpretation of near infrared perfusion imaging using indocyanine green in colorectal surgery. Surg Endosc. 2021; 35(12):7074-7081. DOI: 10.1007/s00464-020-08223-x. View

Frey J, Salibian A, Choi M, Karp N . Mastectomy Flap Thickness and Complications in Nipple-Sparing Mastectomy: Objective Evaluation using Magnetic Resonance Imaging. Plast Reconstr Surg Glob Open. 2017; 5(8):e1439. PMC: 5585433. DOI: 10.1097/GOX.0000000000001439. View

Hassan A, Biaggi A, Asaad M, Andejani D, Liu J, Offodile Nd A . Development and Assessment of Machine Learning Models for Individualized Risk Assessment of Mastectomy Skin Flap Necrosis. Ann Surg. 2022; 278(1):e123-e130. DOI: 10.1097/SLA.0000000000005386. View

Lutken C, Achiam M, Osterkamp J, Svendsen M, Nerup N . Quantification of fluorescence angiography: Toward a reliable intraoperative assessment of tissue perfusion - A narrative review. Langenbecks Arch Surg. 2020; 406(2):251-259. DOI: 10.1007/s00423-020-01966-0. View

Chetta M, Aliu O, Zhong L, Sears E, Waljee J, Chung K . Reconstruction of the Irradiated Breast: A National Claims-Based Assessment of Postoperative Morbidity. Plast Reconstr Surg. 2016; 139(4):783-792. PMC: 5373960. DOI: 10.1097/PRS.0000000000003168. View

Zenn M . Staged immediate breast reconstruction. Plast Reconstr Surg. 2015; 135(4):976-979. DOI: 10.1097/PRS.0000000000001089. View

10.

Senkus E, Kyriakides S, Ohno S, Penault-Llorca F, Poortmans P, Rutgers E . Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2015; 26 Suppl 5:v8-30. DOI: 10.1093/annonc/mdv298. View

11.

Stam W, Goedknegt L, Ingwersen E, Schoonmade L, Bruns E, Daams F . The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review. Surgery. 2021; 171(4):1014-1021. DOI: 10.1016/j.surg.2021.10.002. View

12.

Phillips B, Lanier S, Conkling N, Wang E, Dagum A, Ganz J . Intraoperative perfusion techniques can accurately predict mastectomy skin flap necrosis in breast reconstruction: results of a prospective trial. Plast Reconstr Surg. 2012; 129(5):778e-788e. DOI: 10.1097/PRS.0b013e31824a2ae8. View

13.

Diana M, Agnus V, Halvax P, Liu Y, Dallemagne B, Schlagowski A . Intraoperative fluorescence-based enhanced reality laparoscopic real-time imaging to assess bowel perfusion at the anastomotic site in an experimental model. Br J Surg. 2015; 102(2):e169-76. DOI: 10.1002/bjs.9725. View

14.

Wang M, Huang J, Chagpar A . Is nipple sparing mastectomy associated with increased complications, readmission and length of stay compared to skin sparing mastectomy?. Am J Surg. 2019; 219(6):1030-1035. DOI: 10.1016/j.amjsurg.2019.09.011. View

15.

Nguyen C, Tam S, Easwaralingam N, Seah J, Comerford A, Yu A . Patterns of ischaemia and reperfusion in nipple-sparing mastectomy reconstruction with indocyanine green angiography. J Plast Reconstr Aesthet Surg. 2022; 75(11):4144-4151. DOI: 10.1016/j.bjps.2022.08.006. View

16.

Munabi N, Olorunnipa O, Goltsman D, Rohde C, Ascherman J . The ability of intra-operative perfusion mapping with laser-assisted indocyanine green angiography to predict mastectomy flap necrosis in breast reconstruction: a prospective trial. J Plast Reconstr Aesthet Surg. 2014; 67(4):449-55. DOI: 10.1016/j.bjps.2013.12.040. View

17.

Kim G, Bae K, Noh G, Min W . Estimation of indocyanine green elimination rate constant k and retention rate at 15 min using patient age, weight, bilirubin, and albumin. J Hepatobiliary Pancreat Surg. 2009; 16(4):521-8. DOI: 10.1007/s00534-009-0097-3. View

18.

Kobraei E, Nimtz J, Wong L, Buseman J, Kemper P, Wright H . Risk factors for adverse outcome following skin-sparing mastectomy and immediate prosthetic reconstruction. Plast Reconstr Surg. 2012; 129(2):234e-241e. DOI: 10.1097/PRS.0b013e31823aec7f. View

19.

Liu X, Wu J, Zhou Z . Exploratory undersampling for class-imbalance learning. IEEE Trans Syst Man Cybern B Cybern. 2008; 39(2):539-50. DOI: 10.1109/TSMCB.2008.2007853. View

20.

Liu X, Guo L, Wang H, Guo J, Yang S, Duan L . Research on imbalance machine learning methods for MRWI soft tissue sarcoma data. BMC Med Imaging. 2022; 22(1):149. PMC: 9417078. DOI: 10.1186/s12880-022-00876-5. View