Automatic Aberration Correction for Transcranial Functional and Super-Resolution Ultrasound Imaging in Rodents and Nonhuman Primates

Paul Xing , Antoine Malescot , Eric Martineau , Stephan Quessy , Ravi L. Rungta , Numa Dancause , Jean Provost

Authors on Pith no claims yet

Pith reviewed 2026-05-09 17:29 UTC · model grok-4.3

classification ⚛️ physics.med-ph eess.IVeess.SP

keywords transcranialaberrationcorrectionfunctionalimagingultrasoundaberrationsacross

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The pith

A differentiable beamforming framework optimizes aberration correction using angular coherence, improving transcranial ULM and fUS imaging resolution and sensitivity in mice and nonhuman primates.

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

Ultrasound waves passing through the skull get distorted, causing blurry or incorrect images of brain blood vessels and activity. The authors created a computer framework that automatically adjusts the timing of the ultrasound signals by optimizing a measure of how well the signals align from different angles. They tested this on living mice and monkeys, showing clearer images of brain structures and better detection of blood flow changes. The method works for both high-resolution vessel mapping and functional imaging, and even in 3D for larger animals.

Core claim

By providing a fully automated and generalizable solution for aberration correction, this work lowers a major technical barrier to transcranial ultrasound imaging, enabling broader adoption of non-invasive, super-resolution and functional neuroimaging across laboratories and across species.

Load-bearing premise

The assumption that angular coherence is an effective and sufficient objective function for optimizing the spatially distributed delay-based aberration parameterization in vivo, without requiring additional validation or ground truth.

read the original abstract

Skull-induced aberrations remain a major drawback of transcranial ultrasound localization microscopy (ULM), degrading sensitivity and spatial accuracy through microbubble mislocalization, false detections, and imaging artifacts, such as disconnected or duplicated vessels. Here, we present a differentiable beamforming framework for automatic aberration correction in transcranial Doppler and ULM. Our approach uses spatially distributed delay-based parameterization of the aberration that is optimized in a closed-loop manner using angular coherence as an objective function. We demonstrate robust improvements of transcranial ULM, in vivo, with enhanced resolution of both mouse and nonhuman primate (NHP) brains. We also extended differentiable beamforming to functional measurements, with improvements in the sensitivity of transcranial functional ultrasound (fUS) and ULM based hemodynamic quantification. Extending this approach to 3D transcranial ULM imaging in NHPs, we show efficient correction of skull induced aberrations and removal of artifacts, such as vessel duplications. By providing a fully automated and generalizable solution for aberration correction, this work lowers a major technical barrier to transcranial ultrasound imaging, enabling broader adoption of non-invasive, super-resolution and functional neuroimaging across laboratories and across species.

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.

Desk Editor's Note private letter to a colleague

The paper gives a practical differentiable optimization for automatic transcranial aberration correction using angular coherence on delay parameters, with in vivo demos in mice and NHPs, but the gains stay visual and lack ground-truth checks on the recovered delays.

read the letter

The core idea is a closed-loop differentiable beamformer that tunes spatially distributed delay parameters by maximizing angular coherence. They show this on transcranial ULM and fUS in rodents and nonhuman primates, with some 3D NHP results, and claim clearer vessels, fewer artifacts, and better sensitivity for hemodynamic measures. The automation and the extension beyond basic Doppler are the parts that stand out as new. The parameterization itself is straightforward and avoids needing a full skull model, which makes the method easier to apply across labs and species. The in vivo examples do look improved on the images they provide, and extending the same framework to functional imaging is a reasonable step. The main limitation is the evidence. Improvements are shown through selected images rather than with numbers on resolution, detection rates, or artifact counts, and there are no direct comparisons of the optimized delays against independent measurements such as hydrophone data or controlled phantoms. Without that, it is hard to know whether the objective is recovering the actual aberrations or simply suppressing sidelobes and false detections in another way. The angular coherence choice is reasonable on paper, but the lack of validation leaves the central claim partly open. This is the kind of work that labs doing animal ultrasound neuroimaging would want to read, especially those already running ULM or fUS through the skull and looking for less manual fixes. It has enough technical substance and cross-species application to go to referees rather than a desk reject. I would send it for review and expect the referees to ask for quantitative metrics and some form of ground-truth test on the delay estimates.

Referee Report

2 major / 2 minor

Summary. The manuscript presents a differentiable beamforming framework for automatic correction of skull-induced aberrations in transcranial Doppler, ultrasound localization microscopy (ULM), and functional ultrasound (fUS). Aberrations are parameterized as spatially distributed delays and optimized in closed loop by maximizing angular coherence. In vivo demonstrations in mice and nonhuman primates show qualitative gains in vessel continuity, sensitivity, and artifact reduction (including vessel duplications), with extension to 3D ULM.

Significance. If the recovered delays accurately represent true skull aberrations, the work addresses a major technical barrier to transcranial ultrasound and could enable broader adoption of non-invasive super-resolution and functional neuroimaging across laboratories and species. The physical parameterization combined with an external objective function (angular coherence) is a methodological strength that avoids circularity in the fitting process.

major comments (2)

[Results] Results section (in vivo ULM and fUS demonstrations): improvements in vessel continuity, sensitivity, and artifact removal are presented through example images without quantitative metrics, error bars, statistical tests, or controls (e.g., no reported changes in localization precision, contrast-to-noise ratio, or vessel density). This leaves the claim of 'robust improvements' without load-bearing numerical support.
[Methods] Methods (aberration parameterization and optimization): the framework optimizes spatially distributed delays via angular coherence, yet no ground-truth validation is described comparing the recovered delays to independent measurements (hydrophone, simulation, or phantom). Without this, it is unclear whether gains arise from accurate aberration correction or from a different mechanism such as sidelobe suppression.

minor comments (2)

[Abstract] Abstract: the phrase 'robust improvements' is used without any accompanying quantitative values or specific metrics; adding one or two key numbers would strengthen the summary.
[Methods] Notation: the spatially distributed delay parameterization is introduced without an explicit equation number or diagram showing how delays are distributed across the aperture; adding this would improve reproducibility.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central method relies on the domain assumption that optimizing delay parameters via angular coherence corrects skull aberrations effectively.

free parameters (1)

spatially distributed delay parameters
Optimized in closed-loop using angular coherence for each imaging case.

axioms (1)

domain assumption Angular coherence is a valid objective function for aberration correction
Used to optimize the beamforming parameters in the framework.

pith-pipeline@v0.9.0 · 5538 in / 1062 out tokens · 35497 ms · 2026-05-09T17:29:23.976286+00:00 · methodology

Automatic Aberration Correction for Transcranial Functional and Super-Resolution Ultrasound Imaging in Rodents and Nonhuman Primates

Core claim

Load-bearing premise

discussion (0)