Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Michael Ljungberg

Michael Ljungberg

Professor

Michael Ljungberg

Machine learning-based prediction of conversion coefficients for I-123 metaiodobenzylguanidine heart-to-mediastinum ratio

Författare

  • Koichi Okuda
  • Kenichi Nakajima
  • Chiemi Kitamura
  • Michael Ljungberg
  • Tetsuo Hosoya
  • Yumiko Kirihara
  • Mitsumasa Hashimoto

Summary, in English

Purpose: We developed a method of standardizing the heart-to-mediastinal ratio in 123I-labeled meta-iodobenzylguanidine (MIBG) images using a conversion coefficient derived from a dedicated phantom. This study aimed to create a machine-learning (ML) model to estimate conversion coefficients without using a phantom. Methods: 210 Monte Carlo (MC) simulations of 123I-MIBG images to obtain conversion coefficients using collimators that differed in terms of hole diameter, septal thickness, and length. Simulated conversion coefficients and collimator parameters were prepared as training datasets, then a gradient-boosting ML was trained to estimate conversion coefficients from collimator parameters. Conversion coefficients derived by ML were compared with those that were MC simulated and experimentally derived from 613 phantom images. Results: Conversion coefficients were superior when estimated by ML compared with the classical multiple linear regression model (root mean square deviations: 0.021 and 0.059, respectively). The experimental, MC simulated, and ML-estimated conversion coefficients agreed, being, respectively, 0.54, 0.55, and 0.55 for the low-; 0.74, 0.70, and 0.72 for the low-middle; and 0.88, 0.88, and 0.88 for the medium-energy collimators. Conclusions: The ML model estimated conversion coefficients without the need for phantom experiments. This means that conversion coefficients were comparable when estimated based on collimator parameters and on experiments.

Avdelning/ar

  • Medicinsk strålningsfysik, Lund
  • Nuclear Medicine Physics

Publiceringsår

2023

Språk

Engelska

Sidor

1630-1641

Publikation/Tidskrift/Serie

Journal of Nuclear Cardiology

Volym

30

Issue

4

Dokumenttyp

Artikel i tidskrift

Förlag

Springer

Ämne

  • Radiology, Nuclear Medicine and Medical Imaging

Nyckelord

  • I-MIBG
  • collimator
  • heart-to-mediastinum ratio
  • Monte Carlo simulation

Status

Published

Forskningsgrupp

  • Nuclear Medicine Physics

ISBN/ISSN/Övrigt

  • ISSN: 1071-3581