Evidence map›Paper›PMID 41777598›Full record

ArticleMolecular imaging

Absolute Quantitative Photoacoustic Imaging for Contrast Agents Concentration Estimation Using a Spectral Decomposition Approach.

Shang Gao, Liudmila Serebrennikova, Ryo Murakami, Srikanth Boinapally, Sangeeta Ray, Martin G Pomper, Haichong K Zhang

Abstract read
In one paragraph

Article in Molecular imaging. 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

7 authors.

Shang GaoDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0001-9921-7899
Liudmila SerebrennikovaDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Department of Biomedical Engineering, Worcester, MA, USA.
Ryo MurakamiDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0009-0005-5770-5866
Srikanth BoinapallyJohns Hopkins University, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, USA.ORCID 0000-0001-6394-4453
Sangeeta RayJohns Hopkins University, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, USA.
Martin G PomperJohns Hopkins University, Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD, USA.ORCID 0000-0001-6753-3010
Haichong K ZhangDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA, USA.ORCID 0000-0002-1314-8456

Funding

Training/Dissemination-Resource for Molecular Imaging Agents in Precision MedicineP41EB024495 · NIBIB · UT SOUTHWESTERN MEDICAL CENTER · PI Lilja Solnes · 2017 to 2026
$11.8M
PSMA-based Cancer Imaging AgentsR01CA134675 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI POMPER, MARTIN G · 2009 to 2025
$6.2M
Robotic Lung Ultrasound for Triage of COVID-19 Patients in a Resource-Limited EnvironmentDP5OD028162 · OD · WORCESTER POLYTECHNIC INSTITUTE · PI ZHANG, HAICHONG · 2019 to 2023
$2.3M
NCI NIH HHS R01 CA134675NIBIB NIH HHS P41 EB024495NIH HHS DP5 OD028162
6 · The paper itself

Abstract

Photoacoustic (PA) imaging is a promising modality for medical diagnostics and therapeutic monitoring, but accurate quantification of contrast agents (CAs) remains a challenge due to nonlinear signal responses and spectral shifts at varying concentrations. These limitations hinder its clinical utility in applications such as tumor detection and treatment monitoring. This study introduces a spectral decomposition method to improve absolute CA concentration estimation in PA imaging. By using a reference spectral library, the approach corrects for signal distortions and nonlinear behavior, overcoming key limitations of traditional intensity-based methods. Validation was performed through in vitro experiments using a prostate-specific membrane antigen (PSMA)-targeted CA in both saline and blood, as well as dynamic tracking of indocyanine green (ICG) in ex vivo tissue. The method achieved significantly lower concentration estimation errors, with average absolute errors of 1.80 µM in saline and 3.34 µM in blood. Compared to conventional techniques, the proposed method demonstrated enhanced reliability and robustness. These results underscore the potential of this spectral-based quantification technique to support more precise, clinically translatable PA imaging, enabling accurate CA measurement for early disease detection, surgical guidance, and real-time monitoring of therapeutic interventions.

Indexed as

Contrast MediaPhotoacoustic TechniquesAnimalsHumansIndocyanine GreenMaleReproducibility of ResultsContrast MediaIndocyanine Greencontrast agent quantificationmolecular imagingphotoacoustic imagingspectral decompositiontumor detection

Identifiers

PMID41777598
PMCPMC12950945

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.