Form Factors as Potential Imaging Biomarkers to Differentiate Benign vs. Malignant Lung Lesions on CT Scans
Francesco Bianconi,
Isabella Palumbo,
Mario Luca Fravolini,
Maria Rondini,
Matteo Minestrini,
Giulia Pascoletti,
Susanna Nuvoli,
Angela Spanu,
Michele Scialpi,
Cynthia Aristei,
Barbara Palumbo
Affiliations
Francesco Bianconi
Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06125 Perugia, Italy
Isabella Palumbo
Section of Radiation Oncology, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy
Mario Luca Fravolini
Department of Engineering, Università degli Studi di Perugia, Via Goffredo Duranti 93, 06125 Perugia, Italy
Maria Rondini
Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, Università degli Studi di Sassari, Viale San Pietro 8, 07100 Sassari, Italy
Matteo Minestrini
Section of Nuclear Medicine and Health Physics, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy
Giulia Pascoletti
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy
Susanna Nuvoli
Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, Università degli Studi di Sassari, Viale San Pietro 8, 07100 Sassari, Italy
Angela Spanu
Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, Università degli Studi di Sassari, Viale San Pietro 8, 07100 Sassari, Italy
Michele Scialpi
Division of Diagnostic Imaging, Department of Medicine and Surgery, Piazza Lucio Severi 1, 06132 Perugia, Italy
Cynthia Aristei
Section of Radiation Oncology, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy
Barbara Palumbo
Section of Nuclear Medicine and Health Physics, Department of Medicine and Surgery, Università degli Studi di Perugia, Piazza Lucio Severi 1, 06132 Perugia, Italy
Indeterminate lung nodules detected on CT scans are common findings in clinical practice. Their correct assessment is critical, as early diagnosis of malignancy is crucial to maximise the treatment outcome. In this work, we evaluated the role of form factors as imaging biomarkers to differentiate benign vs. malignant lung lesions on CT scans. We tested a total of three conventional imaging features, six form factors, and two shape features for significant differences between benign and malignant lung lesions on CT scans. The study population consisted of 192 lung nodules from two independent datasets, containing 109 (38 benign, 71 malignant) and 83 (42 benign, 41 malignant) lung lesions, respectively. The standard of reference was either histological evaluation or stability on radiological followup. The statistical significance was determined via the Mann–Whitney U nonparametric test, and the ability of the form factors to discriminate a benign vs. a malignant lesion was assessed through multivariate prediction models based on Support Vector Machines. The univariate analysis returned four form factors (Angelidakis compactness and flatness, Kong flatness, and maximum projection sphericity) that were significantly different between the benign and malignant group in both datasets. In particular, we found that the benign lesions were on average flatter than the malignant ones; conversely, the malignant ones were on average more compact (isotropic) than the benign ones. The multivariate prediction models showed that adding form factors to conventional imaging features improved the prediction accuracy by up to 14.5 pp. We conclude that form factors evaluated on lung nodules on CT scans can improve the differential diagnosis between benign and malignant lesions.