Evidence map›Paper›PMID 40241205›Full record

ArticleRadiation oncology (London, England)2025

Dosiomic predictors of biochemical failure in patients with localized prostate cancer treated with Iodine-125 low-dose-rate brachytherapy.

Masahiro Nakano, Shizuo Kaji, Shogo Kawakami, Hideyasu Tsumura, Toshikazu Imae, Yuichi Tanaka, Kyohei Fujii, Takuro Kainuma, Ryosuke Yamazaki, Ayaka Uchida and 6 more

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Systematic review of artificial intelligence in brachytherapy.Journal of contemporary brachytherapy · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Masahiro NakanoDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan. mnakano@kitasato-u.ac.jp.
Shizuo KajiInstitute of Mathematics for Industry, Kyushu University, Fukuoka, Fukuoka, Japan.
Shogo KawakamiDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Hideyasu TsumuraDepartment of Urology, Kitasato University School of Medicine, Sagamihara, Kanagawa, Japan.
Toshikazu ImaeDepartment of Radiology, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan.
Yuichi TanakaDepartment of Radiology, Kitasato University Hospital, Sagamihara, Kanagawa, Japan.
Kyohei FujiiDepartment of Radiology, Kitasato University Hospital, Sagamihara, Kanagawa, Japan.
Takuro KainumaDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Ryosuke YamazakiDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Ayaka UchidaDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Hijiri KanekoDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Mako FujinoDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.
Chizu HataDepartment of Radiology, Kitasato University Hospital, Sagamihara, Kanagawa, Japan.
Yu MurakamiDepartment of Physics, Cancer Institute, Japanese Foundation for Cancer Research, Koto-ku, Tokyo, Japan.
Masatoshi HashimotoDepartment of Medical Engineering and Technology, Kitasato University School of Allied Health Sciences, Sagamihara, Japan.
Hiromichi IshiyamaDepartment of Radiation Oncology, Kitasato University School of Medicine, 1-15-1, Kitasato, Minami-ku, Sagamihara-shi, Kanagawa, 252-0374, Japan.

Funding

JSPS KAKENHI 18K15569Moonshot Research and Development Program JPMJMS2021
6 · The paper itself

Abstract

backgroundThis study aimed to identify dosiomic features that have a significant impact on biochemical failure (BCF) following low-dose rate (LDR) brachytherapy treatment using Iodine-125 seeds for prostate cancer and to provide insights into LDR brachytherapy treatment efficacy using a dosiomic approach.

methodsBetween January 2005 and February 2015, 1,205 patients with localized prostate cancer underwent Iodine-125 seed implantation without combined external irradiation. A total of 96 patients were selected for this study, including 48 with BCF and 48 without BCF. The patients were divided into two cohorts: derivation and validation. Dose distribution images (DDs) were calculated from computed tomography (CT) images taken one month after implantation. A total of 1,130 dosiomic features, including shape-and-size, histogram, and texture features, were extracted from these DDs, their wavelet-transformed images, and Laplacian-of-Gaussian (LoG)-filtered images. The features obtained were categorized into three groups: shape-and-size (S), histogram (H), and texture (T). The Boruta algorithm was used to eliminate less important features. Two analyses were performed: Analysis A performed a multivariate logistic regression analysis using data from the validation cohort to identify significant features. Analysis B generated logistic regression models using derivation cohort data. The accuracy of BCF prediction was assessed using the validation cohort, with performance measured using the area under the receiver operating characteristic curve (AUC).

resultsAfter the feature reduction process, two, two, and four features remained in the S, H, and T feature groups, respectively. In analysis A, the multivariate logistic regression identified four dominant features, two from each of the S and T groups. In analysis B, the AUC of the logistic regression prediction models using S, H, and all four features were 0.81, 0.77, and 0.86, respectively.

conclusionsFour significant dosiomic features were identified. Notably, three features-elongation, Maximum2DDiameterRow, and wavelet-HHL_Skewness-strongly distinguished patients with favorable prognoses from others. These findings suggest that dosiomic features from postimplant CT and dose distribution may serve as effective factors for evaluating LDR brachytherapy outcomes in patients with prostate cancer.

Indexed as

BrachytherapyIodine RadioisotopesProstatic NeoplasmsRadiotherapy Planning, Computer-AssistedAgedAged, 80 and overHumansMaleMiddle AgedPrognosisRadiotherapy DosageRetrospective StudiesROC CurveTomography, X-Ray ComputedIodine-125Iodine RadioisotopesBiochemical failureDosiomic featuresLow-dose-rate brachytherapyProstate cancer

Identifiers

PMID40241205
PMCPMC12004553

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.