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Pulmonary nodule visualization and evaluation of AI-based detection at various ultra-low-dose levels using photon-counting detector CT.
Jungblut, Lisa; Euler, André; Landsmann, Anna; Englmaier, Vanessa; Mergen, Victor; Sefirovic, Medina; Frauenfelder, Thomas.
Afiliação
  • Jungblut L; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Euler A; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Landsmann A; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Englmaier V; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Mergen V; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Sefirovic M; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
  • Frauenfelder T; Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Acta Radiol ; : 2841851241275289, 2024 Sep 15.
Article em En | MEDLINE | ID: mdl-39279297
ABSTRACT

BACKGROUND:

Radiation dose should be as low as reasonably achievable. With the invention of photon-counting detector computed tomography (PCD-CT), the radiation dose may be considerably reduced.

PURPOSE:

To evaluate the potential of PCD-CT for dose reduction in pulmonary nodule visualization for human readers as well as for computer-aided detection (CAD) studies. MATERIAL AND

METHODS:

A chest phantom containing pulmonary nodules of different sizes/densities (range 3-12 mm and -800-100 HU) was scanned on a PCD-CT with standard low-dose protocol as well as with half, quarter, and 1/40 dose (CTDIvol 0.4-0.03 mGy). Dose-matched scans were performed on a third-generation energy-integrating detector CT (EID-CT). Evaluation of nodule visualization and detectability was performed by two blinded radiologists. Subjective image quality was rated on a 5-point Likert scale. Artificial intelligence (AI)-based nodule detection was performed using commercially available software.

RESULTS:

Highest image noise was found at the lowest dose setting of 1/40 radiation dose (eff. dose = 0.01mSv) with 166.1 ± 18.5 HU for PCD-CT and 351.8 ± 53.0 HU for EID-CT. Overall sensitivity was 100% versus 93% at standard low-dose protocol (eff. dose = 0.2 mSv) for PCD-CT and EID-CT, respectively. At the half radiation dose, sensitivity remained 100% for human reader and CAD studies in PCD-CT. At the quarter radiation dose, PCD-CT achieved the same results as EID-CT at the standard radiation dose setting (93%, P = 1.00) in human reading studies. The AI-CAD system delivered a sensitivity of 93% at the lowest radiation dose level in PCD-CT.

CONCLUSION:

At half dose, PCD CT showed pulmonary nodules similar to full-dose PCD, and at quarter dose, PCD CT performed comparably to standard low-dose EID CT. The CAD algorithm is effective even at ultra-low doses.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article