Evidence map›Paper›PMID 41395594›Full record

ArticleFrontiers in oncology2025

Evaluation of superficial tumor treatment using radixact with the kilovoltage computed tomography system: dosimetric and clinical feasibility of super stuff bolus.

Ryuichi Yada, Yuta Omi, Tatsuya Hasegawa, Katsumasa Nakamura

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Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ryuichi YadaDepartment of Regional Medical Management Studies, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
Yuta OmiDepartment of Radiation Oncology, Anjo Kosei Hospital, Anjo, Aichi, Japan.
Tatsuya HasegawaDepartment of Radiation Oncology, Anjo Kosei Hospital, Anjo, Aichi, Japan.
Katsumasa NakamuraDepartment of Radiation Oncology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Flat commercial boluses for superficial tumor radiation therapy often fail to conform to irregular body surfaces, resulting in air gaps that reduce dose coverage and uniformity. Although three-dimensional printed custom boluses have been developed to address this issue, the plastic material rigidity and time-consuming fabrication process limit their application. This study aimed to evaluate a flexible and easily moldable Super Stuff bolus as a practical alternative. Methods: We conducted a three-part study using Radixact with the kilovoltage computed tomography (kVCT) system. First, surface dose measurements were performed using radiochromic film on a solid water phantom. Super Stuff boluses of varying thicknesses (up to 20 mm) were compared with commercial boluses. Second, long-term stability was assessed over 65 days for dose delivery, thickness (via CT-based measurements), and CT number. Finally, in a clinical case of Ewing's sarcoma, setup reproducibility and conformity were assessed using Radixact's kVCT imaging. Delivered dose distributions were compared with the planned distribution using dose-volume histogram parameters and gamma analysis. Results: Surface dose measurements demonstrated that the maximum variation in surface dose among Super Stuff boluses with thicknesses ranging from 10.7 to 19.8 mm was within 4%. Over 65 days, the Super Stuff bolus showed good long-term stability. Changes in thickness were limited to a maximum of 1.6 mm, and fluctuations in CT number remained stable at 17.9 ± 1.2 Hounsfield units. In the clinical setting, kVCT imaging provided clear visualization of the Super Stuff bolus, and setup reproducibility was maintained throughout the treatment course. Air gaps were also minimized. Furthermore, gamma analysis (3%/2 mm) confirmed high dosimetric reproducibility throughout the treatment course, with passing rates exceeding 96% between the first and subsequent treatment fractions. Conclusions: The Super Stuff bolus provides notable clinical advantages for treating superficial tumors using Radixact with the kVCT system: consistent surface dose buildup, easy fabrication, and robust long-term physical and dosimetric stability. The seamless integration with the kVCT system enhances setup reproducibility, contributing to reliable and accurate dose delivery throughout the treatment course.

Indexed as

air gapclinical practicekilovoltage computed tomography systemlong-term stabilitymetastatic inguinal lymphnode lesions of Ewing’s sarcomaradixactsuper stuff bolussurface dose measurement

Identifiers

PMID41395594
PMCPMC12695533

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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.