Evidence map›Paper›PMID 42552321›Full record

ArticleScientific data2026

OpenQPAIData: Measurements of test objects with reference labels for quantitative photoacoustic imaging research.

Janek Gröhl, Sandeep Kumar Kalva, Berkan Lafci, Francesca Di Cecio, Ran Tao, Thomas R Else, Lorna Wright, Daniel Razansky, Sarah E Bohndiek

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. 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. Article
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

9 authors.

Janek GröhlInstitute for Experimental Molecular Imaging, RWTH Aachen University Hospital, Aachen, Germany. jgroehl@ukaachen.de.
Sandeep Kumar KalvaInstitute of Pharmacology and Toxicology and Institute for Biomedical Engineering, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
Berkan LafciInstitute of Pharmacology and Toxicology and Institute for Biomedical Engineering, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
Francesca Di CecioDepartment of Physics, University of Cambridge, Cambridge, United Kingdom.
Ran TaoDepartment of Physics, University of Cambridge, Cambridge, United Kingdom.
Thomas R ElseDepartment of Physics, University of Cambridge, Cambridge, United Kingdom.
Lorna WrightDepartment of Physics, University of Cambridge, Cambridge, United Kingdom.
Daniel RazanskyInstitute of Pharmacology and Toxicology and Institute for Biomedical Engineering, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
Sarah E BohndiekDepartment of Physics, University of Cambridge, Cambridge, United Kingdom. seb53@cam.ac.uk.

Funding

High-Resolution Bidirectional Optical-Acoustic Mesoscopic Neural Interface for Image-Guided Neuromodulation in Behaving Animals - RF1 Admin SupplementRF1NS126102 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CAMPBELL, ROBERT E., RAZANSKY, DANIEL · 2022 to 2024
$3.1M
Anusandhan National Research Foundation (ANRF) Prime Minister Early Career Grant ANRF/ECRG/2025/002695/LSCancer Research UK A29580Cancer Research UK C9545/A29580Deutsche Forschungsgemeinschaft GR 5824/1Engineering and Physical Sciences Research Council EP/R003599/1, EP/V027069/1, and EP/X037770/1IIT Bombay Seed Grant RD/0524-IRCCSH0-004NINDS NIH HHS RF1 NS126102Personalized Health and Related Technologies of the ETH domain PHRT-582Swiss National Science Foundation 310030_192757US National Institutes of Health RF1-NS126102
6 · The paper itself

Abstract

The goal of quantitative photoacoustic imaging (qPAI) is to determine absolute chromophore concentrations from multispectral photoacoustic images. Achieving this goal would enable bias-free molecular photoacoustic imaging and the derivation of functional tissue biomarkers, such as local blood oxygenation, with numerous clinical implications. To deliver qPAI, two inverse problems must be solved: the acoustic inverse problem of reconstructing the initial pressure distribution from measured signals, and the optical inverse problem of reconstructing spatial images of optical absorption from the initial pressure. Unfortunately, these inverse problems are difficult to solve in practice. The validation of proposed qPAI algorithms is particularly challenging due to the lack of experimentally measured ground truth of the optical and acoustic tissue properties. With OpenQPAIData, we present a dataset of 30 tissue-mimicking phantoms imaged using three different photoacoustic systems: the Multispectral Optoacoustic Tomography (MSOT) InVision commercially produced system from iThera Medical GmbH, and the custom-built Transmission Reflection Optoacoustic and Ultrasound (TROPUS) and Spiral Volumetric Optoacoustic Tomography (SVOT) imaging systems developed by Prof. Daniel Razansky's group. The dataset includes raw measurements, reconstructed images, manually segmented reference annotations, and matched optical property maps derived from double-integrating-sphere (DIS) measurements. By providing these multi-device imaging data with reference optical properties, we believe that OpenQPAIData enables the benchmarking of both acoustic and optical inverse solvers and supports the development of image quality assessment metrics for photoacoustic imaging.

Indexed as

Photoacoustic TechniquesAlgorithmsPhantoms, Imaging

Identifiers

PMID42552321
PMCPMC13439077

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.