Salvatore Gitto1, Giorgia Grassi2, Chiara De Angelis3, Cristian Giuseppe Monaco3, Silvana Sdao4, Francesco Sardanelli5,6, Luca Maria Sconfienza6,7, Giovanni Mauri8. 1. Scuola di Specializzazione in Radiodiagnostica, Università degli Studi di Milano, via Festa del Perdono 7, 20122, Milan, Italy. sal.gitto@gmail.com. 2. Scuola di Specializzazione in Endocrinologia e Malattie del Metabolismo, Università degli Studi di Milano, Milan, Italy. 3. Scuola di Specializzazione in Radiodiagnostica, Università degli Studi di Milano, via Festa del Perdono 7, 20122, Milan, Italy. 4. Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. 5. Servizio di Radiologia, IRCCS Policlinico San Donato, San Donato Milanese, Italy. 6. Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milan, Italy. 7. Unità Operativa di Radiologia Diagnostica ed Interventistica, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy. 8. Divisione di Radiologia Interventistica, IEO, Istituto Europeo di Oncologia IRCCS, Milano, Italy.
Abstract
AIM OF THE STUDY: To compare the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for thyroid ultrasound (US) with that of a non-computer-aided radiologist in the characterization of low-to-high suspicion thyroid nodules. METHODS: This retrospective study included a consecutive series of adult patients referred for US-guided fine-needle aspiration biopsy (FNAB) of a thyroid nodule. All patients were eligible for thyroid nodule FNAB according to the current international guidelines. An interventional radiologist experienced in thyroid imaging acquired the US images subsequently used for post-processing, performed FNAB and provided the US features of each nodule. A radiology resident and an endocrinology resident in consensus performed post-processing using the CAD system to assess the same nodule characteristics. The diagnostic performance and agreement of US features between the CAD system and the radiologist were compared. RESULTS: Sixty-two patients (50 F; age 60 ± 12 years) were enrolled: 77.4% (48/62) of thyroid nodules were benign, 22.6% (14/62) were undetermined to malignant and required follow-up or surgery. Interobserver agreement between the CAD system and the radiologist was substantial for orientation (K = 0.69), fair for composition (K = 0.36), echogenicity (K = 0.36), K-TIRADS (K = 0.29), and slight for margins (K = 0.03). The radiologist demonstrated a significantly higher sensitivity than the CAD system (78.6% vs. 21.4%; P = 0.008), while there was no statistical difference in specificity (66.7% vs. 81.3%; P = 0.065). CONCLUSION: This CAD system is less sensitive than an experienced radiologist and showed slight-to-substantial agreement with the radiologist for the characterization of thyroid nodules. Although it is an innovative tool with good potential, additional efforts are needed to improve its diagnostic performance.
AIM OF THE STUDY: To compare the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for thyroid ultrasound (US) with that of a non-computer-aided radiologist in the characterization of low-to-high suspicion thyroid nodules. METHODS: This retrospective study included a consecutive series of adult patients referred for US-guided fine-needle aspiration biopsy (FNAB) of a thyroid nodule. All patients were eligible for thyroid nodule FNAB according to the current international guidelines. An interventional radiologist experienced in thyroid imaging acquired the US images subsequently used for post-processing, performed FNAB and provided the US features of each nodule. A radiology resident and an endocrinology resident in consensus performed post-processing using the CAD system to assess the same nodule characteristics. The diagnostic performance and agreement of US features between the CAD system and the radiologist were compared. RESULTS: Sixty-two patients (50 F; age 60 ± 12 years) were enrolled: 77.4% (48/62) of thyroid nodules were benign, 22.6% (14/62) were undetermined to malignant and required follow-up or surgery. Interobserver agreement between the CAD system and the radiologist was substantial for orientation (K = 0.69), fair for composition (K = 0.36), echogenicity (K = 0.36), K-TIRADS (K = 0.29), and slight for margins (K = 0.03). The radiologist demonstrated a significantly higher sensitivity than the CAD system (78.6% vs. 21.4%; P = 0.008), while there was no statistical difference in specificity (66.7% vs. 81.3%; P = 0.065). CONCLUSION: This CAD system is less sensitive than an experienced radiologist and showed slight-to-substantial agreement with the radiologist for the characterization of thyroid nodules. Although it is an innovative tool with good potential, additional efforts are needed to improve its diagnostic performance.
Authors: Anna Pisani Mainini; Cristian Monaco; Lorenzo Carlo Pescatori; Chiara De Angelis; Francesco Sardanelli; Luca Maria Sconfienza; Giovanni Mauri Journal: J Ultrasound Date: 2016-10-21
Authors: Salvatore Gitto; Giorgia Grassi; Chiara De Angelis; Cristian Giuseppe Monaco; Silvana Sdao; Francesco Sardanelli; Luca Maria Sconfienza; Giovanni Mauri Journal: Radiol Med Date: 2018-09-22 Impact factor: 3.469
Authors: U Rajendra Acharya; Oliver Faust; S Vinitha Sree; Filippo Molinari; Jasjit S Suri Journal: Comput Methods Programs Biomed Date: 2011-11-04 Impact factor: 5.428
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Authors: Salvatore Gitto; Sotirios Bisdas; Ilaria Emili; Luca Nicosia; Lorenzo Carlo Pescatori; Kunwar Bhatia; Ravi K Lingam; Francesco Sardanelli; Luca Maria Sconfienza; Giovanni Mauri Journal: Endocrine Date: 2019-03-22 Impact factor: 3.633
Authors: Salvatore Gitto; Giorgia Grassi; Chiara De Angelis; Cristian Giuseppe Monaco; Silvana Sdao; Francesco Sardanelli; Luca Maria Sconfienza; Giovanni Mauri Journal: Radiol Med Date: 2018-09-22 Impact factor: 3.469
Authors: Ilaria Celletti; Daniele Fresilli; Corrado De Vito; Marco Bononi; Sara Cardaccio; Alessia Cozzolino; Cosimo Durante; Giorgio Grani; Gianmarco Grimaldi; Andrea M Isidori; Carlo Catalano; Vito Cantisani Journal: Radiol Med Date: 2021-06-15 Impact factor: 3.469