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VECTOR: An algorithm for the detection of COVID-19 pneumonia from velcro-like lung sounds.
Pancaldi, Fabrizio; Pezzuto, Giuseppe Stefano; Cassone, Giulia; Morelli, Marianna; Manfredi, Andreina; D'Arienzo, Matteo; Vacchi, Caterina; Savorani, Fulvio; Vinci, Giovanni; Barsotti, Francesco; Mascia, Maria Teresa; Salvarani, Carlo; Sebastiani, Marco.
  • Pancaldi F; University of Modena and Reggio Emilia, Department of Sciences and Methods for Engineering, via Amendola 2, 42122, Reggio Emilia, Italy; University of Modena and Reggio Emilia, Artificial Intelligence Research and Innovation Center (AIRI), Via Pietro Vivarelli 10, 41125, Modena, Italy. Electronic ad
  • Pezzuto GS; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: pezzuto.giuseppe@aou.mo.it.
  • Cassone G; University of Modena and Reggio Emilia, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, via del Pozzo 71, 42124, Modena, Italy; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Mode
  • Morelli M; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: morelli.marianna@aou.mo.it.
  • Manfredi A; University of Modena and Reggio Emilia, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, via del Pozzo 71, 42124, Modena, Italy; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Mode
  • D'Arienzo M; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: darienzo.matteo@aou.mo.it.
  • Vacchi C; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: caterina.vacchi@unimore.i.
  • Savorani F; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: savorani.fulvio@aou.mo.it.
  • Vinci G; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: vinci.giovanni@aou.mo.it.
  • Barsotti F; Emergency Room and Emergency Medicine, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Modena, Italy. Electronic address: francesco.barsotti@aou.mo.it.
  • Mascia MT; University of Modena and Reggio Emilia, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, via del Pozzo 71, 42124, Modena, Italy; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Mode
  • Salvarani C; University of Modena and Reggio Emilia, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, via del Pozzo 71, 42124, Modena, Italy; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Mode
  • Sebastiani M; University of Modena and Reggio Emilia, Department of Surgery, Medicine, Dentistry and Morphological Sciences with Transplant Surgery, Oncology and Regenerative Medicine Relevance, via del Pozzo 71, 42124, Modena, Italy; Rheumatology Unit, Azienda Policlinico di Modena, via del Pozzo 71, 42124, Mode
Comput Biol Med ; 142: 105220, 2022 03.
Article in English | MEDLINE | ID: covidwho-1611676
ABSTRACT
The coronavirus disease 2019 (COVID-19) has severely stressed the sanitary systems of all countries in the world. One of the main issues that physicians are called to tackle is represented by the monitoring of pauci-symptomatic COVID-19 patients at home and, generally speaking, everyone the access to the hospital might or should be severely reduced. Indeed, the early detection of interstitial pneumonia is particularly relevant for the survival of these patients. Recent studies on rheumatoid arthritis and interstitial lung diseases have shown that pathological pulmonary sounds can be automatically detected by suitably developed algorithms. The scope of this preliminary work consists of proving that the pathological lung sounds evidenced in patients affected by COVID-19 pneumonia can be automatically detected as well by the same class of algorithms. In particular the software VECTOR, suitably devised for interstitial lung diseases, has been employed to process the lung sounds of 28 patient recorded in the emergency room at the university hospital of Modena (Italy) during December 2020. The performance of VECTOR has been compared with diagnostic techniques based on imaging, namely lung ultrasound, chest X-ray and high resolution computed tomography, which have been assumed as ground truth. The results have evidenced a surprising overall diagnostic accuracy of 75% even if the staff of the emergency room has not been suitably trained for lung auscultation and the parameters of the software have not been optimized to detect interstitial pneumonia. These results pave the way to a new approach for monitoring the pulmonary implication in pauci-symptomatic COVID-19 patients.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2022 Document Type: Article