Emission textural features I-131 of differentiated thyroid cancer tissue

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BACKGROUND: The management of differentiated thyroid cancer includes single-photon emission tomography combined with X-ray computed tomography after radioiodine therapy. Despite a good response to surgery and radioiodine therapy, recurrence is noted in some cases, leading to an unfavorable prognosis in 8% of cases [1]. A preliminary analysis of the distribution of I-131 in residual thyroid tissues and foci of metastasis allows for the estimation of the probability of differentiated cancer recurrence. Currently, there is no method that is simultaneously effective and easy to perform for predicting the recurrence of differentiated thyroid cancer.

AIM: The aim of the study was to develop a technique for extracting and computing textural features of the I-131 accumulation region using a single-photon emission tomography system corresponding to differentiated thyroid cancer tissue.

MATERIALS AND METHODS: A retrospective analysis of single-photon emission tomography combined with X-ray computed tomography of the neck and thorax of 23 patients was conducted. Regions of interest, including foci of I-131 accumulation in the primary tumor bed, regional and distant metastases, were delineated in Xeleris 4DR software. The obtained mask with the original image was processed in a program written with the help of the Matlab package, which localizes the foci. The textural features of foci are calculated based on the obtained spatial adjacency matrix. This matrix shows how often pixels with certain gray scale brightness values occur in an image. Therefore, the features based on the spatial adjacency matrix reflect the frequency distribution of different pixel neighborhoods in a given context.

RESULTS: An algorithm for constructing three-dimensional matrices of a radiation source surrounded by tissue of differentiated thyroid cancer was developed. The textural features of three-dimensional matrices were investigated. It was demonstrated that there are tendencies for differences in texture features corresponding to the ordering of pixel values and image contrast. The values of the obtained features obey the lognormal distribution.

CONCLUSIONS: An algorithm for extracting textural features of I-131 accumulation foci allows post-therapy single-photon emission tomography images combined with X-ray computed tomography to be analyzed for the likelihood of recurrence of differentiated thyroid cancer.

Texto integral

BACKGROUND: The management of differentiated thyroid cancer includes single-photon emission tomography combined with X-ray computed tomography after radioiodine therapy. Despite a good response to surgery and radioiodine therapy, recurrence is noted in some cases, leading to an unfavorable prognosis in 8% of cases [1]. A preliminary analysis of the distribution of I-131 in residual thyroid tissues and foci of metastasis allows for the estimation of the probability of differentiated cancer recurrence. Currently, there is no method that is simultaneously effective and easy to perform for predicting the recurrence of differentiated thyroid cancer.

AIM: The aim of the study was to develop a technique for extracting and computing textural features of the I-131 accumulation region using a single-photon emission tomography system corresponding to differentiated thyroid cancer tissue.

MATERIALS AND METHODS: A retrospective analysis of single-photon emission tomography combined with X-ray computed tomography of the neck and thorax of 23 patients was conducted. Regions of interest, including foci of I-131 accumulation in the primary tumor bed, regional and distant metastases, were delineated in Xeleris 4DR software. The obtained mask with the original image was processed in a program written with the help of the Matlab package, which localizes the foci. The textural features of foci are calculated based on the obtained spatial adjacency matrix. This matrix shows how often pixels with certain gray scale brightness values occur in an image. Therefore, the features based on the spatial adjacency matrix reflect the frequency distribution of different pixel neighborhoods in a given context.

RESULTS: An algorithm for constructing three-dimensional matrices of a radiation source surrounded by tissue of differentiated thyroid cancer was developed. The textural features of three-dimensional matrices were investigated. It was demonstrated that there are tendencies for differences in texture features corresponding to the ordering of pixel values and image contrast. The values of the obtained features obey the lognormal distribution.

CONCLUSIONS: An algorithm for extracting textural features of I-131 accumulation foci allows post-therapy single-photon emission tomography images combined with X-ray computed tomography to be analyzed for the likelihood of recurrence of differentiated thyroid cancer.

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Sobre autores

Mikhail Maltsev

National Research Nuclear University MEPhI

Autor responsável pela correspondência
Email: misha.malcev.01@bk.ru
ORCID ID: 0009-0009-2420-4650
Rússia, Moscow

Alexey Trukhin

National Research Nuclear University MEPhI; Endocrinology research centre

Email: Alexey.trukhin12@gmail.com
ORCID ID: 0000-0001-5592-4727
Código SPIN: 4398-9536
Rússia, Moscow; Moscow

Almaz Manaev

National Research Nuclear University MEPhI; Endocrinology research centre

Email: a.manaew2016@yandex.ru
ORCID ID: 0009-0003-8035-676X
Código SPIN: 2902-9767
Rússia, Moscow; Moscow

Maria Reinberg

Endocrinology research centre

Email: mrezerford12@gmail.com
ORCID ID: 0009-0002-1632-2197
Rússia, Moscow

Bibliografia

  1. Reinberg MV, Slashchuk KY, Trukhin AA, Avramova KI, Sheremeta MS. Preparation for radioiodine therapy in patients with differentiated thyroid cancer: a modern perspective (a review). Digital Diagnostics. 2023;4(4):543–568. doi: 10.17816/DD532728

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