Evidence map›Paper›PMID 26019171›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2015

MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI.

Michael A Mastanduno, Junqing Xu, Fadi El-Ghussein, Shudong Jiang, Hong Yin, Yan Zhao, Ke Wang, Fang Ren, Jiang Gui, Brian W Pogue and 1 more

Abstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

11 authors.

Michael A MastandunoThayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
Junqing XuDepartment of Radiology, Xijing Hospital, Xi'an, China.
Fadi El-GhusseinThayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
Shudong JiangThayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
Hong YinDepartment of Radiology, Xijing Hospital, Xi'an, China. keith.paulsen@dartmouth.edu yinhong@fmmu.edu.cn.
Yan ZhaoThayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
Ke WangDepartment of Radiology, Xijing Hospital, Xi'an, China.
Fang RenDepartment of Radiology, Xijing Hospital, Xi'an, China.
Jiang GuiDepartment of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire.
Brian W PogueThayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
Keith D PaulsenThayer School of Engineering, Dartmouth College, Hanover, New Hampshire. Department of Diagnostic Radiology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire. keith.paulsen@dartmouth.edu yinhong@fmmu.edu.cn.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Steven D Leach · 1985 to 2026
$91.3M
Small Molecule Enhancers of Photodynamic Therapy for Skin CancerP01CA084203 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Bryan Quilty Spring · 2001 to 2026
$27.9M
FREQUENCY DOMAIN OPTICAL IMAGING OF BREAST CANCERR01CA069544 · NCI · DARTMOUTH COLLEGE · PI PAULSEN, KEITH D. · 1996 to 2012
$2.4M
Monitoring Neoadjuvant Chemotherapy Responses with NIR TomographyR01CA176086 · NCI · DARTMOUTH COLLEGE · PI JIANG, SHUDONG · 2014 to 2018
$2.0M
NIRFASTR01CA132750 · NCI · DARTMOUTH COLLEGE · PI POGUE, BRIAN WILLIAM · 2009 to 2012
$1.2M
NCI NIH HHS P01 CA084203NCI NIH HHS P30 CA023108NCI NIH HHS R01 CA069544NCI NIH HHS R01 CA132750NCI NIH HHS R01 CA176086
6 · The paper itself

Abstract

purposeThe purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI. EXPERIMENTAL

designThe study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20-81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance.

resultsIn the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively.

conclusionsMRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.

Indexed as

AdultAgedAged, 80 and overBiopsyBreast NeoplasmsFemaleHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMiddle AgedReproducibility of ResultsROC CurveSpectroscopy, Near-InfraredTomography, OpticalTumor BurdenYoung Adult

Identifiers

PMID26019171
PMCPMC4763338

What OpenQuestion holds

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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 OpenQuestion graph.