pith. sign in

arxiv: 2606.11465 · v1 · pith:O4P54XUKnew · submitted 2026-06-09 · ⚛️ physics.med-ph

Planned, delivered and variable RBE dose difference analysis for a patient cohort with base-of-tongue cancer treated with IMPT

Qianxia Wang , Edgar Gelover Reyes , Alex Stanforth , William Andrew LePain , Haijian Chen , Mingyao Zhu , Katja M. Langen , William Stokes
show 4 more authors
Soumon Rudra Mark McDonald James Edward Bates Stella Flampouri
This is my paper

Pith reviewed 2026-06-27 10:22 UTC · model grok-4.3

classification ⚛️ physics.med-ph
keywords proton therapyIMPTbase-of-tongue cancerRBEdose differenceanatomy changesplan evaluationhead and neck
0
0 comments X

The pith

Planned and delivered proton doses differ substantially for base-of-tongue cancer due to anatomy changes, and variable RBE influences plan evaluation.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper sets out to quantify how much the radiation dose actually received by base-of-tongue cancer patients during intensity-modulated proton therapy deviates from the original plan. These deviations stem from shifts in patient anatomy across lengthy treatment courses, a problem noted as especially severe in head and neck cases. The work also examines the effect of replacing the standard fixed relative biological effectiveness value of 1.1 with models that assign higher values near the end of the proton range. A reader would care because the study states that clinics currently have no installed tools to perform such delivered-versus-planned comparisons, leaving open the possibility that plans are evaluated on incomplete information.

Core claim

The authors analyze a patient cohort with base-of-tongue cancer treated by IMPT to measure differences between planned and delivered doses while incorporating variable RBE. They observe that anatomy changes can produce large discrepancies and that variable RBE exceeds 1.1 particularly at beam ends, thereby altering plan evaluation, in the absence of clinical tools for routine assessment of these quantities.

What carries the argument

Comparison of planned versus delivered dose distributions using variable RBE models across a base-of-tongue cancer cohort.

If this is right

  • Clinics lack installed tools for evaluating delivered versus planned dose differences in proton therapy.
  • Head and neck patients suffer the most anatomy changes over long treatment courses and difficulty eating.
  • Variable RBE values larger than 1.1 at beam ends change how treatment plans are evaluated.
  • The constant RBE of 1.1 may not capture the full biological effect in these cases.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar dose-difference tracking could be applied to other treatment sites to identify where adaptive replanning is most needed.
  • Incorporating variable RBE into routine evaluation might shift estimates of normal-tissue complication probabilities in head and neck cases.
  • The absence of clinical tools noted in the study points to a practical barrier that future software development could address.

Load-bearing premise

The selected base-of-tongue cancer cohort experiences the most anatomy changes compared with other treatment sites and the analysis methods accurately capture delivered dose without unstated modeling errors.

What would settle it

Direct comparison of repeated imaging and dose recalculation for the same patients showing delivered doses match planned doses within a small margin regardless of anatomy shifts, or outcome data showing identical clinical results under constant and variable RBE.

Figures

Figures reproduced from arXiv: 2606.11465 by Alex Stanforth, Edgar Gelover Reyes, Haijian Chen, James Edward Bates, Katja M. Langen, Mark McDonald, Mingyao Zhu, Qianxia Wang, Soumon Rudra, Stella Flampouri, William Andrew LePain, William Stokes.

Figure 2
Figure 2. Figure 2: (a) The planned dose (Dplanned) VS the delivered dose (Ddelivered): difference in the mean dose (D̅), three DVH indices (D95, D50 and D05) (the planned dose – the delivered dose); (b) The constant RBE dose (Ddelivered) VS the variable RBE dose (DRBE): difference in the mean dose (D̅), three DVH indices (D95, D50 and D05) (the variable RBE dose – the constant RBE dose). Markers without a bar were the values… view at source ↗
read the original abstract

Background: To our knowledge, no tools have been installed in clinic for delivered and planned dose differences evaluation. This difference could be large for head and neck patients who suffer the most anatomy changes compared with other treatment sites due to long treatment courses and difficulty in eating. At the same time, variable RBE dose is an increasing concern for proton therapy. The constant RBE 1.1 is widely applied in clinics, however, the real RBE is larger than 1.1 especially at the end of beam range. How they are different and what the influence on plan evaluation are an interesting topic to investigate.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript analyzes differences between planned and delivered doses as well as the effects of variable RBE (versus constant RBE=1.1) for a cohort of base-of-tongue cancer patients treated with IMPT. It motivates the work by noting that anatomy changes during long treatment courses can produce large dose discrepancies in head-and-neck cases and that variable RBE, which exceeds 1.1 at the distal beam edge, may alter plan evaluation.

Significance. If the delivered-dose and variable-RBE comparisons prove robust, the study could highlight the need for adaptive planning or site-specific RBE models in proton therapy for head-and-neck patients. The absence of comparative data across treatment sites, however, prevents the cohort from being positioned as representative of the largest possible effects.

major comments (1)
  1. [Background] Background: The claim that head-and-neck patients 'suffer the most anatomy changes compared with other treatment sites' is unsupported; no quantitative metrics (weight loss, CTV volume change, setup error) or citations comparing base-of-tongue cases to prostate, lung, or other sites are provided. This directly weakens the motivation for selecting this cohort as the site of largest effect.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their review and constructive comment on our manuscript. We respond to the major comment below.

read point-by-point responses

  1. Referee: The claim that head-and-neck patients 'suffer the most anatomy changes compared with other treatment sites' is unsupported; no quantitative metrics (weight loss, CTV volume change, setup error) or citations comparing base-of-tongue cases to prostate, lung, or other sites are provided. This directly weakens the motivation for selecting this cohort as the site of largest effect.

    Authors: We agree that the statement is unsupported by quantitative metrics or comparative citations. The intent was to note known challenges in head-and-neck cases (long courses, eating difficulties), but the comparative phrasing ('most' relative to other sites) lacks evidence and should not have been included. We will revise the Background section to remove this claim, focusing instead on the clinical relevance of anatomy changes for base-of-tongue IMPT patients without asserting superiority of effect size over other sites. This change will be incorporated in the revised manuscript. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical cohort analysis with no derivations or self-referential fits

full rationale

The paper is a retrospective clinical dosimetry study comparing planned vs. delivered doses (with constant vs. variable RBE) in a base-of-tongue IMPT cohort. No equations, parameter fits, predictions, or derivation chains are described in the provided text or abstract. The background statement that head/neck patients 'suffer the most anatomy changes' is an unsupported claim (no comparative metrics or citations), but this is an evidentiary gap rather than circularity. No self-citations, ansatzes, or renamings reduce any result to its own inputs by construction. The analysis is self-contained against external patient data and does not invoke uniqueness theorems or fitted inputs called predictions.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review; no mathematical models, free parameters, axioms, or invented entities are described.

pith-pipeline@v0.9.1-grok · 5680 in / 945 out tokens · 24719 ms · 2026-06-27T10:22:27.032792+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

20 extracted references · 20 canonical work pages

  1. [1]

    Monte Carlo simulations in radiotherapy dosimetry

    Andreo P. Monte Carlo simulations in radiotherapy dosimetry. Radiat Oncol. 2018;13(1):121. doi:10.1186/s13014-018-1065-3

    work page doi:10.1186/s13014-018-1065-3 2018

  2. [2]

    Quantification of Proton Dose Calculation Accuracy in the Lung

    Grassberger C, Daartz J, Dowdell S, Ruggieri T, Sharp G, Paganetti H. Quantification of Proton Dose Calculation Accuracy in the Lung. Int J Radiat Oncol Biol Phys. 2014;89(2):424. doi:10.1016/j.ijrobp.2014.02.023

    work page doi:10.1016/j.ijrobp.2014.02.023 2014

  3. [3]

    Pencil beam algorithms are unsuitable for proton dose calculations in lung

    Taylor PA, Kry S, Followill D. Pencil beam algorithms are unsuitable for proton dose calculations in lung. Int J Radiat Oncol Biol Phys. 2017;99(3):750-756. doi:10.1016/j.ijrobp.2017.06.003

    work page doi:10.1016/j.ijrobp.2017.06.003 2017

  4. [4]

    Mechanisms and Review of Clinical Evidence of Variations in Relative Biological Effectiveness in Proton Therapy

    Paganetti H. Mechanisms and Review of Clinical Evidence of Variations in Relative Biological Effectiveness in Proton Therapy. Int J Radiat Oncol. 2022;112(1):222-236. doi:10.1016/j.ijrobp.2021.08.015

    work page doi:10.1016/j.ijrobp.2021.08.015 2022

  5. [5]

    Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios

    Giovannini G, Böhlen T, Cabal G, et al. Variable RBE in proton therapy: comparison of different model predictions and their influence on clinical-like scenarios. Radiat Oncol. 2016;11(1):68. doi:10.1186/s13014-016-0642-6

    work page doi:10.1186/s13014-016-0642-6 2016

  6. [6]

    Spatial correlation of linear energy transfer and relative biological effectiveness with suspected treatment-related toxicities following proton therapy for intracranial tumors

    Ödén J, Toma-Dasu I, Witt Nyström P, Traneus E, Dasu A. Spatial correlation of linear energy transfer and relative biological effectiveness with suspected treatment-related toxicities following proton therapy for intracranial tumors. Med Phys. 2020;47(2):342-351. doi:10.1002/mp.13911

    work page doi:10.1002/mp.13911 2020

  7. [7]

    Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy

    Paganetti H, Blakely E, Carabe-Fernandez A, et al. Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy. Med Phys. 2019;46(3):e53-e78. doi:10.1002/mp.13390

    work page doi:10.1002/mp.13390 2019

  8. [8]

    The linear-quadratic formula and progress in fractionated radiotherapy

    Fowler JF. The linear-quadratic formula and progress in fractionated radiotherapy. Br J Radiol. 1989;62(740):679-694. doi:10.1259/0007-1285-62-740-679 16

    work page doi:10.1259/0007-1285-62-740-679 1989

  9. [9]

    Range uncertainty in proton therapy due to variable biological effectiveness

    Carabe A, Moteabbed M, Depauw N, Schuemann J, Paganetti H. Range uncertainty in proton therapy due to variable biological effectiveness. Phys Med Biol. 2012;57(5):1159-1172. doi:10.1088/0031-9155/57/5/1159

    work page doi:10.1088/0031-9155/57/5/1159 2012

  10. [10]

    A model for the relative biological effectiveness of protons: the tissue specific parameter α/β of photons is a predictor for the sensitivity to LET changes

    Wedenberg M, Lind BK, Hårdemark B. A model for the relative biological effectiveness of protons: the tissue specific parameter α/β of photons is a predictor for the sensitivity to LET changes. Acta Oncol Stockh Swed. 2013;52(3):580-588. doi:10.3109/0284186X.2012.705892

    work page doi:10.3109/0284186x.2012.705892 2013

  11. [11]

    A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data

    McNamara AL, Schuemann J, Paganetti H. A phenomenological relative biological effectiveness (RBE) model for proton therapy based on all published in vitro cell survival data. Phys Med Biol. 2015;60(21):8399-8416. doi:10.1088/0031-9155/60/21/8399

    work page doi:10.1088/0031-9155/60/21/8399 2015

  12. [12]

    A microdosimetric-kinetic model of cell death from exposure to ionizing radiation of any LET, with experimental and clinical applications

    Hawkins RB. A microdosimetric-kinetic model of cell death from exposure to ionizing radiation of any LET, with experimental and clinical applications. Int J Radiat Biol. 1996;69(6):739-755. doi:10.1080/095530096145481

    work page doi:10.1080/095530096145481 1996

  13. [13]

    Elsässer T, Weyrather WK, Friedrich T, et al. Quantification of the relative biological effectiveness for ion beam radiotherapy: direct experimental comparison of proton and carbon ion beams and a novel approach for treatment planning. Int J Radiat Oncol Biol Phys. 2010;78(4):1177-1183. doi:10.1016/j.ijrobp.2010.05.014

    work page doi:10.1016/j.ijrobp.2010.05.014 2010

  14. [14]

    Combined Use of Monte Carlo DNA Damage Simulations and Deterministic Repair Models to Examine Putative Mechanisms of Cell Killing

    Carlson DJ, Stewart RD, Semenenko VA, Sandison GA. Combined Use of Monte Carlo DNA Damage Simulations and Deterministic Repair Models to Examine Putative Mechanisms of Cell Killing. Radiat Res. 2008;169(4):447-459. doi:10.1667/RR1046.1

    work page doi:10.1667/rr1046.1 2008

  15. [15]

    A technique for the quantitative evaluation of dose distributions

    Low DA, Harms WB, Mutic S, Purdy JA. A technique for the quantitative evaluation of dose distributions. Med Phys. 1998;25(5):656-661. doi:10.1118/1.598248

    work page doi:10.1118/1.598248 1998

  16. [16]

    Tolerance limits and methodologies for IMRT measurement- based verification QA: Recommendations of AAPM Task Group No

    Miften M, Olch A, Mihailidis D, et al. Tolerance limits and methodologies for IMRT measurement- based verification QA: Recommendations of AAPM Task Group No. 218. Med Phys. 2018;45(4):e53-e83. doi:10.1002/mp.12810

    work page doi:10.1002/mp.12810 2018

  17. [17]

    Dose-volume histograms

    Drzymala RE, Mohan R, Brewster L, et al. Dose-volume histograms. Int J Radiat Oncol. 1991;21(1):71-78. doi:10.1016/0360-3016(91)90168-4

    work page doi:10.1016/0360-3016(91)90168-4 1991

  18. [18]

    National Protocol for Model-Based Selection for Proton Therapy in Head and Neck Cancer

    Langendijk JA, Hoebers FJP, de Jong MA, et al. National Protocol for Model-Based Selection for Proton Therapy in Head and Neck Cancer. Int J Part Ther. 2021;8(1):354-365. doi:10.14338/IJPT- 20-00089.1

    work page doi:10.14338/ijpt- 2021

  19. [19]

    An Estimation of Radiobiological Parameters for Head- and-Neck Cancer Cells and the Clinical Implications

    Qi XS, Yang Q, Lee SP, Li XA, Wang D. An Estimation of Radiobiological Parameters for Head- and-Neck Cancer Cells and the Clinical Implications. Cancers. 2012;4(2):566-580. doi:10.3390/cancers4020566

    work page doi:10.3390/cancers4020566 2012

  20. [20]

    Calculation of cranial nerve complication probability for acoustic neuroma radiosurgery

    Meeks SL, Buatti JM, Foote KD, Friedman WA, Bova FJ. Calculation of cranial nerve complication probability for acoustic neuroma radiosurgery. Int J Radiat Oncol Biol Phys. 2000;47(3):597-602. doi:10.1016/s0360-3016(00)00493-4

    work page doi:10.1016/s0360-3016(00)00493-4 2000