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Purpose <p>The study explored the quantitative analysis of portable ultrasound devices using target images from Multipurpose Phantom N-365. It focused on identifying inter-device variability and time-dependent degradation of the devices and their probes to support standardization and quality control of ultrasound devices.</p> Methods <p>Three ultrasound device models were assessed, with two different setup conditions for each model. Three types of phantom targets, i.e., cyst-like, colloid cyst-like, and nodule-like, were collected from circular grayscale targets. The mean and standard deviation (SD) of brightness were calculated for each target type.</p> Results <p>Quantification of the mean and SD values of target brightness effectively distinguished between ultrasound devices due to the aging of the ultrasound equipment. Multivariate analysis further revealed that both the probes and the main unit independently contributed to time-related changes.</p> Conclusion <p>This article presents a novel method for ensuring rigorous quality control and promoting standardization in ultrasound examinations by quantifying phantom image characteristics.</p>

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Explorative research on image quantification methods for setup conditions and quality control of ultrasound devices in thyroid ultrasonography

  • 期刊论文

  • 发表日期：

    2026年2月19日

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  • Chisato Takahashi,
  • Yukio Kimura,
  • Shoko Nishiyama,
  • Yumiko Kurosu,
  • Haruka Ejiri,
  • Mahiro Asano,
  • Satoshi Suzuki,
  • Shinichi Suzuki,
  • Hiroki Shimura

摘要

Purpose

The study explored the quantitative analysis of portable ultrasound devices using target images from Multipurpose Phantom N-365. It focused on identifying inter-device variability and time-dependent degradation of the devices and their probes to support standardization and quality control of ultrasound devices.

Methods

Three ultrasound device models were assessed, with two different setup conditions for each model. Three types of phantom targets, i.e., cyst-like, colloid cyst-like, and nodule-like, were collected from circular grayscale targets. The mean and standard deviation (SD) of brightness were calculated for each target type.

Results

Quantification of the mean and SD values of target brightness effectively distinguished between ultrasound devices due to the aging of the ultrasound equipment. Multivariate analysis further revealed that both the probes and the main unit independently contributed to time-related changes.

Conclusion

This article presents a novel method for ensuring rigorous quality control and promoting standardization in ultrasound examinations by quantifying phantom image characteristics.