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REVIEW 4 major objections 4 minor 51 references

First experimental test of a coded-mask gamma camera for proton therapy monitoring

T0 review · 4 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read A coded-mask gamma camera, tested for the first time under clinical proton-therapy conditions, can locate the distal falloff of the prompt-gamma depth profile — and hence the proton range — with a statistical precision of about 1.7 mm for…

desk verdict The first full-scale coded-mask gamma camera test at a clinical proton facility is a real step forward, but the headline 1.7 mm precision at 10^8 protons is not actually derived in the text. read the letter →

arxiv 2501.00666 v1 pith:7GJYZJNE submitted 2024-12-31 physics.med-ph

Magdalena Ko{l}odziej , Stephan Brons , Miko{l}aj Dubiel , George N. Farah , Alexander Fenger , Ronja Hetzel , Jonas Kasper , Monika Kercz
show 10 more authors
Barbara Ko{l}odziej Linn Mielke Gabriel Ostrzo{l}ek Magdalena Rafecas Jorge Roser Katarzyna Rusiecka Achim Stahl Vitalii Urbanevych Ming-Liang Wong Aleksandra Wrońska
This is my paper · ORCID
classification physics.med-ph
keywords codedmaskprompt-gammaimagingprotontherapyrangeverificationdistalfalloffpositionMLEMscintillatingfibers
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper reports the first experimental test of a coded-mask gamma camera for real-time proton therapy monitoring. The central claim is that the camera can determine the prompt-gamma distal falloff position, a proxy for the proton range, with a statistical precision of 1.7 mm for $10^{8}$ protons at a reference beam energy of 90.86 MeV, in a clinical beam environment. This precision matches the paper's Monte Carlo predictions, holds despite non-functional detector pixels, and is comparable to the precision of established knife-edge slit and multi-slit cameras. The authors also show the detector can sustain clinical beam intensities without measurable dead time, making real-time range verification a practical prospect.

What carries the argument

The central object is the coded-mask camera: a structured tungsten collimator with a modified uniformly redundant array (MURA) pattern that casts a position-dependent shadow of the prompt-gamma source onto a pixelated scintillating-fiber detector. The reconstruction machinery is maximum-likelihood expectation maximization (MLEM), iteratively inverting the recorded hit map against a simulated system matrix to recover the one-dimensional prompt-gamma depth profile, from which the distal falloff position is read at half maximum of the falling edge. The system matrix is the load-bearing link between detector hits and source depth: it encodes, for each depth bin, the probability that a prompt gamma is registered in each detector pixel, corrected per-pixel for measured detection efficiency.

What would settle it

Take the same camera into the same geometry but irradiate the PMMA phantom at an energy not used in building the system matrix (say 75 MeV), reconstruct the distal falloff position, and compare with the PSTAR range; if the residual grows beyond the claimed 1.7 mm or the slope departs from the tested energies' fit, the simulated system matrix is not transferable.

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Extended reading notes

Core claim

In this experiment, a prototype coded-mask camera — a 7-layer stack of LYSO:Ce,Ca scintillating fibers read out by silicon photomultipliers, shadowed by a 476-rank MURA tungsten mask — was placed beside a PMMA phantom irradiated by proton beams of seven energies from 70.51 to 108.15 MeV at the Heidelberg Ion Therapy Center. Prompt-gamma depth profiles were reconstructed with an MLEM algorithm whose system matrix came from Geant4 simulations of point-source responses. The distal falloff position extracted from each profile tracked the PSTAR-calculated proton range with a Pearson correlation of 0.996 and an RMSE of 1.7 mm; for the reference spot S4 at 90.86 MeV and $10^{8}$ protons, the statistical precision of the distal falloff determination was 1.7 mm (1σ). The agreement with simulations, which reproduce the experimental profiles including artifacts, supports the conclusion that the camera works as modeled. The paper interprets this as validating coded-mask imaging as a competitive alternative for online range verification.

Load-bearing premise

The reconstructed depth profile is only as trustworthy as the simulated system matrix: Monte Carlo point-source responses with an energy spectrum from one beam energy are assumed to hold for all seven beam energies, all lateral positions, and the real detector's efficiency pattern, so any depth- or energy-dependent simulation bias becomes a range-measurement bias.

Editorial extensions

If this is right

  • A coded-mask camera can determine proton range shifts in a phantom with about 2 mm precision per 10^8-proton spot, putting it on par with existing slit-based prompt-gamma cameras.
  • The detector's rate capability (up to 3.2×10^9 protons/s without dead time, with headroom for higher rates) is sufficient for synchrotron and cyclotron clinical beam intensities, so the approach is not limited by count-rate saturation.
  • Simulations of a fully operational detector with no dead pixels predict a fourfold improvement in the RMSE of distal falloff determination (1.7 mm to 0.4 mm), identifying hardware repair as the direct path to sub-millimetre precision.
  • The camera is insensitive to lateral beam position changes within ±1 cm at fixed depth, so small patient setup shifts do not corrupt range readings.
  • Once y-position resolution is restored, the same detector geometry can be extended to 2D prompt-gamma imaging, as shown in prior simulations.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The 1.7 mm precision is established in a homogeneous PMMA phantom; clinical tissue has density and composition variations that will add systematic errors, so the clinically achievable precision may be worse.
  • The system matrix is built from a single beam energy's gamma spectrum and assumed valid across energies; measuring the camera's response at untested energies or with a radioactive line source would directly test this transferability.
  • If the simulated factor-of-four improvement is realized after fixing dead pixels, coded-mask cameras could reach sub-millimetre range precision per spot, which would make margin reduction a quantitative trade-off rather than a safety risk.
  • The paper's comparison suggests coded masks offer a larger field of view and smaller material budget than slit cameras at similar precision; a head-to-head clinical study would be needed to see whether this translates into better patient outcomes.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The manuscript reports the first experimental test of a coded-mask (CM) gamma camera for proton therapy monitoring. The system uses a scintillating-fiber detector with a tungsten MURA mask, tested at the Heidelberg Ion Therapy Center with a PMMA phantom and proton beams of seven energies (70.51–108.15 MeV). Prompt-gamma depth profiles are reconstructed with MLEM, and the distal falloff position (DFP) is compared with PSTAR proton ranges. The authors report a statistical precision of DFP determination of 1.7 mm for 10^8 protons at 90.86 MeV, rate capability at clinical beam intensities, and benchmarking against Geant4 simulations. They conclude that the CM camera is a competitive alternative to slit-based systems.

Significance. If the quantitative claim is correct, this would be the first experimental demonstration that a coded-mask camera can track proton range shifts with precision comparable to knife-edge slit and multi-parallel slit systems in a clinically realistic setting. The paper has notable strengths: a seven-energy experimental dataset, rate tests up to 3.2×10^9 protons/s, transparent handling of dead pixels and background, and a detailed simulation chain with optical-photon tracking. However, the main precision claim is not consistently derived in the text: the only 1.7 mm value computed is an RMSE accuracy metric for full-statistics data, not a per-spot statistical precision from the bootstrap analysis. In addition, Table 3 includes a precision value for prior simulation work that the authors themselves retract in footnote 5. The qualitative feasibility result is credible, but the quantitative headline needs substantial revision or re-derivation.

major comments (4)
  1. [Abstract; Section 3.4; Section 3.5; Section 5] The paper claims a statistical precision of 1.7 mm for 10^8 protons at the reference energy of 90.86 MeV, but the only 1.7 mm value derived in the text is the RMSE computed in Section 3.4 (Eq. 2) from full 10^10-proton profiles across all seven beam energies. The bootstrap analysis in Section 2.5.5 and Figures 10 and 13 is never summarized as a standard deviation for spot S4 at 10^8 protons; Section 3.5 reports only interquartile ranges. The headline precision therefore appears to be a mislabeled accuracy metric rather than a statistically derived per-spot precision. Because this number is the basis of the abstract, the conclusions, and the comparison in Table 3, the authors must either provide the actual bootstrap standard deviation for S4 at 10^8 protons or reword the claims to refer to RMSE accuracy; footnote 5 shows that a similar conflation previously led to an incorrect published value.
  2. [Section 2.5.4; Section 3.4] The reconstruction parameters (MLEM iteration count, energy threshold, Gaussian smoothing kernel, excluded detector columns, and event classes) are optimized using the same experimental data set on which the RMSE, correlation, and slope are then reported. No held-out validation is described. Because the optimization explicitly targets low RMSE against PSTAR ranges, the quoted RMSE of 1.7 mm is an in-sample fit statistic and may be optimistic. I recommend a cross-validation scheme, such as leave-one-spot-out, or at least an explicit description of how the optimization was prevented from overfitting, to demonstrate that the reported performance is not an artifact of parameter tuning.
  3. [Table 3; Section 4.2, footnote 5] Table 3 lists a precision of 0.72 mm for CM simulation [25], but footnote 5 in Section 4.2 explicitly retracts the 0.7–1.3 mm range from that prior work as incorrect, stating that it corresponded to aggregated range-shift precision rather than single-spot statistical precision. Using the retracted value in the comparison table is misleading and undermines the claim that the current experimental result is consistent with prior simulation predictions. The entry should be removed, corrected, or annotated with the retraction.
  4. [Section 2.3.3; Section 3.6] The system matrix A used in the MLEM update (Eq. 1) is generated entirely from Monte Carlo simulations of point-like gamma sources, using the S4 energy spectrum, and the same simulation chain is then validated by its agreement with the experimental DFP data (Table 2). Consequently, the agreement between reconstructed and PSTAR ranges could reflect internal consistency of the simulation rather than the camera's physical response. I ask the authors to provide a sensitivity analysis with respect to the assumed gamma energy spectrum and the detector efficiency model, or to cross-validate using a system matrix computed from an independent simulation or analytical model, to establish that the DFP reconstruction is robust to simulation uncertainties.
minor comments (4)
  1. [Abstract] The abstract contains typographical and formatting issues, such as "to108.15 MeV" (missing space) and "10 8" instead of "10^8" in several places; please correct these throughout.
  2. [Section 3.5] The sentence "For all but the deepest beam spot (S1-S6), the IQR is below 3 mm" is confusing because S1-S6 is not a single spot; presumably it means all spots except S7, which is the deepest. Please reword for clarity.
  3. [Section 4.2, first paragraph; Figure 13] The text states that the statistical-precision studies are "translated to the usual metric of standard deviation (1σ)" and summarized in Fig. 13, but Figure 13 shows no numeric standard deviations. A table of the 1σ values, especially for spot S4 at 10^8 protons, would be necessary to support the claimed 1.7 mm precision.
  4. [Section 3.1; Section 4.3] The y-position resolution of 74 ± 10 mm FWHM is very poor and the authors note this precludes 2D imaging. The abstract and conclusions should perhaps qualify that the current prototype provides 1D imaging only, to avoid overstating the system's current capabilities.

Circularity Check

0 steps flagged · score 2.0 of 10

No definitional circularity: the central DFP result is an empirical measurement benchmarked against external PSTAR ranges; only minor self-consistency and metric-traceability caveats remain.

full rationale

The paper's core claim is an experimental measurement: DFP positions are extracted from measured hit maps via MLEM and compared with PSTAR proton ranges. PSTAR is an external benchmark, so the 1.7 mm accuracy/precision result does not reduce by construction to the simulation inputs. The MLEM system matrix A is generated by Geant4 simulations and includes an efficiency correction epsilon_i = (R_i - B_i)/SR_i that uses simulated reference data, creating a calibration loop, but the PSTAR comparison breaks any definitional circularity. The bootstrap analysis measures an internal spread of reconstructed DFPs rather than a fitted parameter renamed as a prediction. Two caveats keep the score at 2 rather than 0: the 1.7 mm value appears in Section 3.4 as the 10^10-proton RMSE and in the abstract/conclusions as the 10^8-proton single-spot precision, while Section 3.5 reports only IQRs and Fig. 13, so the text never states the S4/10^8 bootstrap standard deviation that would directly license the headline; and footnote 5 retracts a prior self-cited precision range that still appears in Table 3 as the CM-simulation comparator. These are reporting and self-citation inconsistencies, not equation-level reductions, so no circular step is identified.

Assumptions & free parameters 5 free parameters · 6 assumptions · 0 invented entities

The central claim rests on a Monte Carlo generated system matrix, tuned reconstruction hyperparameters, and the assumed equivalence between the extracted distal falloff position and the proton range. No new physical entities are postulated; the new content is an experimental measurement and its comparison with simulation.

free parameters (5)
  • MLEM iteration count = 23
    Chosen by optimizing correlation, RMSE, and slope on the experimental dataset (Section 2.5.4); affects all reconstructed DFP positions.
  • Lower hit-map energy threshold = 1 MeV
    Selected as the 'most robust' threshold in the optimization; higher thresholds reduce statistics, lower thresholds admit more background (Section 3.4).
  • Gaussian smoothing kernel standard deviation = 3 pixels
    Optimized smoothing of reconstructed PG depth profiles before DFP extraction (Section 2.5.4).
  • Excluded lateral fiber columns = columns 0-2 and 52-54 of 55
    Columns excluded because primary protons contaminated the front region and because of dead-pixel concentration and symmetry at the back; post hoc data selection (Section 3.4).
  • Included event classes = types 1-4 (unique and semi-unique), type 5 excluded
    Event classes used in reconstruction were part of the optimized chain; ambiguous events were excluded (Sections 2.4.2 and 2.5.4).
assumptions (6)
  • domain assumption Geant4 QGSP_BIC_HP_EMZ plus GODDeSS optical simulation accurately predicts prompt-gamma production and detector response for 70-108 MeV protons in PMMA.
    Used to generate phase-space files and the system matrix; the paper cites its own prior work [42] for PG production but does not independently re-validate the physics list here (Sections 2.3.1-2.3.3).
  • domain assumption The system matrix built from point sources using the S4 gamma energy spectrum is valid for all seven beam energies and all lateral beam positions.
    Section 2.3.3; if the PG energy spectrum or angular distribution changes with beam energy, the reconstruction may be biased in a depth-dependent way.
  • domain assumption The distal falloff position defined as the half-maximum point of a spline fit on the falling edge is a faithful proxy for proton range.
    Section 2.5.2, based on Min et al. [3] and Gueth et al. [49]; the exact choice of spline range and half-maximum is not derived from first principles.
  • domain assumption PSTAR-calculated proton ranges in PMMA are accurate ground truth for the tested energies.
    Used as the reference in the RMSE and linearity metrics; PSTAR is an external NIST standard (ref [39]), but any error in the range tables enters the reported precision.
  • domain assumption The efficiency correction using the 68Ge reference measurement and background subtraction removes all relevant detector nonuniformities and activation background.
    Sections 2.2.6 and 2.5.1; after correction the relative standard deviation of fiber efficiency is still 11.39%, so residual nonuniformities remain and could affect reconstructed profiles.
  • domain assumption Background measured at least 30 minutes after the last beam run represents the inter-spill background during irradiation.
    Section 2.4; short-lived activation products may differ between the reference background measurement and the actual spill intervals, which is not quantified.

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Cite this review

Pith. "Pith review of First experimental test of a coded-mask gamma camera for proton therapy monitoring." pith.science (2026). https://pith.science/paper/7GJYZJNE

@misc{pith2026250100666,
  author       = {Pith},
  title        = {Pith review of: First experimental test of a coded-mask gamma camera for proton therapy monitoring},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/7GJYZJNE}},
  note         = {Machine review of arXiv:2501.00666}
}
abstract

Objective. The objective of the presented study was to evaluate the feasibility of a coded-mask (CM) gamma camera for real-time range verification in proton therapy, addressing the need for a precise and efficient method of treatment monitoring. Approach. A CM gamma camera prototype was tested in clinical conditions. The setup incorporated a scintillator-based detection system and a structured tungsten collimator. The experiment consisted of the irradiation of PMMA phantom with proton beams of energies ranging from 70.51 to 108.15 MeV. Experimental data were benchmarked against Monte Carlo simulations. The distal falloff position was determined for both experimental data and simulations. Main results. The tested CM camera achieved a statistical precision of distal falloff position determination of 1.7 mm for $10^8$ protons, which is consistent with simulation predictions, despite hardware limitations such as non-functional detector pixels. Simulations indicated that a fully operational setup would further improve the performance of the detector. The system demonstrated rate capability sufficient for clinical proton beam intensities and maintained performance without significant dead time. Significance. This study validates the potential of the CM gamma camera for real-time proton therapy monitoring. The technology promises to enhance treatment accuracy and patient safety, offering a competitive alternative to existing approaches such as single-slit and multi-slit systems.

Figures

Figures reproduced from arXiv: 2501.00666 by the authors.

Figure 1
Figure 1. Top left: a schematic of the detector setup: a stack of scintillation fibers (green) [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Detection setup in imaging experiments: perspective view (left) and top view (right). [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Location of the irradiated spots in the phantom overlaid with the camera FOV - [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (10 more)
Figure 4
Figure 4. Figure 4: The processing scheme of the experimental and simulated data. [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: Time structure of the proton beam, with separation to the spill (blue) and the [PITH_FULL_IMAGE:figures/full_fig_p011_5.png]
Figure 6
Figure 6. Figure 6: Comparison of gamma energy spectra for spills and background for beam spot S4. [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Components of the image reconstruction, presented in the form of hit maps. On the [PITH_FULL_IMAGE:figures/full_fig_p013_7.png]
Figure 8
Figure 8. Figure 8: The system matrix - constructed from hits with energy deposits [PITH_FULL_IMAGE:figures/full_fig_p014_8.png]
Figure 9
Figure 9. Figure 9: PG depth profiles reconstructed from experimental data, smoothed with Gaussian [PITH_FULL_IMAGE:figures/full_fig_p018_9.png]
Figure 10
Figure 10. Figure 10: Analysis of statistical precision: median and IQRs of the reconstructed DFPs vs. [PITH_FULL_IMAGE:figures/full_fig_p019_10.png]
Figure 11
Figure 11. Figure 11: PG depth profiles reconstructed from simulated data, smoothed with Gaussian [PITH_FULL_IMAGE:figures/full_fig_p020_11.png]
Figure 12
Figure 12. Figure 12: PG depth profiles reconstructed from simulated data without acceptance gaps (non [PITH_FULL_IMAGE:figures/full_fig_p021_12.png]
Figure 13
Figure 13. Figure 13: Precision of DFP determination across the FOV for different numbers of protons [PITH_FULL_IMAGE:figures/full_fig_p022_13.png]

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Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.