Evidence map›Paper›PMID 23255739›Full record

ArticleAJR. American journal of roentgenology2013

Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck.

Sanjeev Chawla, Sungheon Kim, Lawrence Dougherty, Sumei Wang, Laurie A Loevner, Harry Quon, Harish Poptani

Open access · greenAbstract read
In one paragraph

Article in AJR. American journal of roentgenology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 3 pooled it
9.2field-weighted citation impact, top 2% of its field
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

78 citing papers in PubMed, 3 syntheses or guidelines pooled it, 149 citations in OpenAlex.

  1. Pooled it
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  4. Trial
  5. Review
  6. Surrogating tumour cell density in head and neck cancer: [Radiation oncology (London, England) · 2025
    Article
  7. Review
  8. Role of Diffusion Weighted Magnetic Resonance Imaging in Oral Cancer in Predicting Response to Neoadjuvant Chemotherapy.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2025
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18 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 1 country.

Sanjeev ChawlaDepartment of Radiology, University of Pennsylvania, 423 Guardian Dr, B6 Blockley Hall, Philadelphia, PA 19104, USA.
Sungheon Kim
Lawrence Dougherty
Sumei Wang
Laurie A Loevner
Harry Quon
Harish Poptani
California University of Pennsylvania · USUniversity of Pennsylvania · US

Funding

MR Spectroscropy and Imaging in Head and Neck TumorsR01CA102756 · NCI · UNIVERSITY OF PENNSYLVANIA · PI POPTANI, HARISH · 2004 to 2007
$1.1M
NCI NIH HHS R01 CA102756NCI NIH HHS R01-CA102756
6 · The paper itself

Abstract

objectiveThe objective of our study was to predict response to chemoradiation therapy in patients with head and neck squamous cell carcinoma (HNSCC) by combined use of diffusion-weighted imaging (DWI) and high-spatial-resolution, high-temporal-resolution dynamic contrast-enhanced MRI (DCE-MRI) parameters from primary tumors and metastatic nodes. SUBJECTS AND

methodsThirty-two patients underwent pretreatment DWI and DCE-MRI using a modified radial imaging sequence. Postprocessing of data included motion-correction algorithms to reduce motion artifacts. The median apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), extracellular extravascular volume fraction (v(e)), and plasma volume fraction (v(p)) were computed from primary tumors and nodal masses. The quality of the DCE-MRI maps was estimated using a threshold median chi-square value of 0.10 or less. Multivariate logistic regression and receiver operating characteristic curve analyses were used to determine the best model to discriminate responders from nonresponders.

resultsAcceptable χ(2) values were observed from 84% of primary tumors and 100% of nodal masses. Five patients with unsatisfactory DCE-MRI data were excluded and DCE-MRI data for three patients who died of unrelated causes were censored from analysis. The median follow-up for the remaining patients (n = 24) was 23.72 months. When ADC and DCE-MRI parameters (K(trans), v(e), v(p)) from both primary tumors and nodal masses were incorporated into multivariate logistic regression analyses, a considerably higher discriminative accuracy (area under the curve [AUC] = 0.85) with a sensitivity of 81.3% and specificity of 75% was observed in differentiating responders (n = 16) from nonresponders (n = 8).

conclusionThe combined use of DWI and DCE-MRI parameters from both primary tumors and nodal masses may aid in prediction of response to chemoradiation therapy in patients with HNSCC.

Indexed as

ChemoradiotherapyContrast MediaDiffusion Magnetic Resonance ImagingMagnetic Resonance AngiographyCarcinoma, Squamous CellFemaleHead and Neck NeoplasmsHumansImage Processing, Computer-AssistedLymphatic MetastasisMaleMiddle AgedROC CurveSensitivity and SpecificityContrast Media

Identifiers

PMID23255739
PMCPMC3549615
OpenAlexW2091880592

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.