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Detection support of lesions in patients with prostate cancer using \({}_{{}}^{18} {\text{F}}\)-PSMA 1007 PET/CT

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

This study proposes a detection support system for primary and metastatic lesions of prostate cancer using \({}_{{}}^{18} {\text{F}}\)-PSMA 1007 positron emission tomography/computed tomography (PET/CT) images with non-image information, including patient metadata and location information of an input slice image.

Methods

A convolutional neural network with condition generators and feature-wise linear modulation (FiLM) layers was employed to allow input of not only PET/CT images but also non-image information, namely, Gleason score, flag of pre- or post-prostatectomy, and normalized z-coordinate of an input slice. We explored the insertion position of the FiLM layers to optimize the conditioning of the network using non-image information.

Results

\({}_{{}}^{18} {\text{F}}\)-PSMA 1007 PET/CT images were collected from 163 patients with prostate cancer and applied to the proposed system in a threefold cross-validation manner to evaluate the performance. The proposed system achieved a Dice score of 0.5732 (per case) and sensitivity of 0.8200 (per lesion), which are 3.87 and 4.16 points higher than the network without non-image information.

Conclusion

This study demonstrated the effectiveness of the use of non-image information, including metadata of the patient and location information of the input slice image, in the detection of prostate cancer from \({}_{{}}^{18} {\text{F}}\)-PSMA 1007 PET/CT images. Improvement in the sensitivity of inactive and small lesions remains a future challenge.

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Acknowledgements

We would like to thank Sadahiro Naka for synthesizing the PET probes, Takashi Kamiya and Hidetaka Sasaki for acquiring PET images, and Frederik L. Giesel for supporting PET research. This study was supported by the Ministry of Health, Labour and Welfare Grants and Japan Agency for Medical Research and Development Grants No. 22ck0106577h0003, Development and application of \({}_{{}}^{18} {\text{F}}\)-PSMA PET/CT imaging system for prostate cancer enabled by newly developed synthesizing device (P.I., Ukihide Tateishi, MD). We have also been given helpful suggestions by the Timothy Hall, PhD, Chair and Steering Committee, Quantitative Imaging Biomarkers Alliance (QIBA), Radiological Society of North America (RSNA), Shigeki Aoki, MD, and Ukihide Tateishi, MD, Chair and Steering Committee, J-QIBA, JRS. This study was supported by the QiSS program of the OPERA (Grant Number: JPMJOP1721) from the Japan Science and Technology Agency (JST).

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Authors and Affiliations

  1. Institute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan

    Naoki Tsuchiya & Akinobu Shimizu

  2. Department of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo City, Tokyo, Japan

    Koichiro Kimura & Ukihide Tateishi

  3. Department of Nuclear Medicine and Tracer Kinetics, Graduate School of Medicine, Osaka University, Osaka, Japan

    Tadashi Watabe

  4. Department of Urology, Graduate School of Medicine, Osaka University, Osaka, Japan

    Koji Hatano, Motohide Uemura & Norio Nonomura

  5. Department of Urology, Fukushima Medical University School of Medicine, Fukushima, Japan

    Motohide Uemura

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  1. Naoki Tsuchiya
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Correspondence to Naoki Tsuchiya or Akinobu Shimizu.

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This manuscript has not been published elsewhere and is not under consideration for publication in any other journal. All authors have approved the manuscript and agree with its submission to IJCARS. All procedures in this study involving human participants were performed in accordance with the ethical standards of the institutional research committees and the 1975 Helsinki Declaration [as revised in 2008(5)].

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Tsuchiya, N., Kimura, K., Tateishi, U. et al. Detection support of lesions in patients with prostate cancer using \({}_{{}}^{18} {\text{F}}\)-PSMA 1007 PET/CT. Int J CARS 19, 613–623 (2024). https://doi.org/10.1007/s11548-024-03067-5

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