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Automatic numeration and localization of I-125 seeds in the post-implant prostate images based on CT and radiography image fusion

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Abstract  

Purpose

Permanent prostate seed implant brachytherapy is widely adopted as a successful treatment method for prostate cancer. While radiographic planar fluoroscopy images are a well-established method to determine the location of seeds implanted in the prostate, many have investigated computed tomography (CT) to determine it. In this study, our purpose is to develop an automatic algorithm to accurately identify the seed positions, direction, and at the same time, to estimate the number of I-125 seeds implanted during the treatment procedure, as implanted seeds location is helpful information in intraoperative dosimetry in low-dose-rate (LDR) permanent prostate brachytherapy.

Methods

A prostate phantom with a total of 40 I-125 implanted dummy seeds and 22 patients with a total of 1091 implanted seeds were scanned using CT imaging device with 2.5 mm slice thickness and radiography imaging. Phase congruency (PC) was performed to enhance edge detection and seed visualization. Seed detection was performed using the histogram analysis of the processed image, and the calculation of the probability of the number of separate and overlapped seeds was performed using registration process between CT and Fluoroscopy images.

Results

This algorithm could successfully recognize 98.28% of the seeds without losing any image information, and therefore could correctly estimate the number of seeds, which is an essential step to maintain the high-quality treatment of prostate brachytherapy.

Conclusion

While the simulation results demonstrate the capability of the proposed algorithm, it is sensitive to the imaging process due to its dependency upon the CT and radiography image fusion procedure.

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Data Availability

The data of the article is available and will be sent upon the editor's request.

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Authors and Affiliations

  1. School of Mechanical Engineering, Department of Nuclear Engineering, Shiraz University, Shiraz, Iran

    Marsa Gholamian & Reza Faghihi

  2. School of Electrical and Computer Engineering, Department of Electronics and Telecommunication Engineering, Shiraz University, Shiraz, Iran

    Mehran Yazdi

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  1. Marsa Gholamian
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  2. Mehran Yazdi
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  3. Reza Faghihi
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Correspondence to Reza Faghihi.

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Gholamian, M., Yazdi, M. & Faghihi, R. Automatic numeration and localization of I-125 seeds in the post-implant prostate images based on CT and radiography image fusion. Res. Biomed. Eng. 39, 415–425 (2023). https://doi.org/10.1007/s42600-023-00276-w

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