Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes

G. Maffeis; A. Pifferi; A. Dalla Mora; L. Di Sieno; R. Cubeddu; A. Tosi; E. Conca; A. Giudice; A. Ruggeri; S. Tisa; A. Flocke; B. Rosinski; J.-M Dinten; M. Perriollat; C. Fraschini; J. Lavaud; S. Arridge; G. Di Sciacca; A. Farina; P. Panizza; E. Venturini; P. Gordebeke; Paola Taroni

doi:10.1117/12.2648945

7 March 2023 Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes

G. Maffeis, A. Pifferi, A. Dalla Mora, L. Di Sieno, R. Cubeddu, A. Tosi, E. Conca, A. Giudice, A. Ruggeri, S. Tisa, A. Flocke, B. Rosinski, J.-M Dinten, M. Perriollat, C. Fraschini, J. Lavaud, S. Arridge, G. Di Sciacca, A. Farina, P. Panizza, E. Venturini, P. Gordebeke, Paola Taroni

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Proceedings Volume 12376, Optical Tomography and Spectroscopy of Tissue XV; 123760K (2023) https://doi.org/10.1117/12.2648945
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

A machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography. The Mann-Whitney test indicates oxy-hemoglobin (p-value = 0.0007) and lipids (0.0387) as the most significant constituents for lesion classification, but work is in progress for further analysis. Together with sensitivity (91%), specificity (75%) and the Area Under the ROC Curve (0.83), special metrics for imbalanced datasets (27% of malignant lesions) are applied to the machine learning outcome: balanced accuracy (83%) and Matthews Correlation Coefficient (0.65). The initial results underline the promising informative content of optical data.

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G. Maffeis, A. Pifferi, A. Dalla Mora, L. Di Sieno, R. Cubeddu, A. Tosi, E. Conca, A. Giudice, A. Ruggeri, S. Tisa, A. Flocke, B. Rosinski, J.-M Dinten, M. Perriollat, C. Fraschini, J. Lavaud, S. Arridge, G. Di Sciacca, A. Farina, P. Panizza, E. Venturini, P. Gordebeke, and Paola Taroni "Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes", Proc. SPIE 12376, Optical Tomography and Spectroscopy of Tissue XV, 123760K (7 March 2023); https://doi.org/10.1117/12.2648945

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