↓ Skip to main content

Study protocol: multi-parametric magnetic resonance imaging for therapeutic response prediction in rectal cancer

Overview of attention for article published in BMC Cancer, July 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
44 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Study protocol: multi-parametric magnetic resonance imaging for therapeutic response prediction in rectal cancer
Published in
BMC Cancer, July 2017
DOI 10.1186/s12885-017-3449-4
Pubmed ID
Authors

Trang Thanh Pham, Gary Liney, Karen Wong, Robba Rai, Mark Lee, Daniel Moses, Christopher Henderson, Michael Lin, Joo-Shik Shin, Michael Bernard Barton

Abstract

Response to neoadjuvant chemoradiotherapy (CRT) of rectal cancer is variable. Accurate imaging for prediction and early assessment of response would enable appropriate stratification of management to reduce treatment morbidity and improve therapeutic outcomes. Use of either diffusion weighted imaging (DWI) or dynamic contrast enhanced (DCE) imaging alone currently lacks sufficient sensitivity and specificity for clinical use to guide individualized treatment in rectal cancer. Multi-parametric MRI and analysis combining DWI and DCE may have potential to improve the accuracy of therapeutic response prediction and assessment. This protocol describes a prospective non-interventional single-arm clinical study. Patients with locally advanced rectal cancer undergoing preoperative CRT will prospectively undergo multi-parametric MRI pre-CRT, week 3 CRT, and post-CRT. The protocol consists of DWI using a read-out segmented sequence (RESOLVE), and DCE with pre-contrast T1-weighted (VIBE) scans for T1 calculation, followed by 60 phases at high temporal resolution (TWIST) after gadoversetamide injection. A 3-dimensional voxel-by-voxel technique will be used to produce colour-coded ADC and K(trans) histograms, and data evaluated in combination using scatter plots. MRI parameters will be correlated with surgical histopathology. Histopathology analysis will be standardized, with chemoradiotherapy response defined according to AJCC 7th Edition Tumour Regression Grade (TRG) criteria. Good response will be defined as TRG 0-1, and poor response will be defined as TRG 2-3. The combination of DWI and DCE can provide information on physiological tumour factors such as cellularity and perfusion that may affect radiotherapy response. If validated, multi-parametric MRI combining DWI and DCE can be used to stratify management in rectal cancer patients. Accurate imaging prediction of patients with a complete response to CRT would enable a 'watch and wait' approach, avoiding surgical morbidity in these patients. Consistent and reliable quantitation from standardised protocols is essential in order to establish optimal thresholds of ADC and K(trans) and permit the role of multi-parametric MRI for early treatment prediction to be properly evaluated. Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12616001690448 (retrospectively registered 8/12/2016).

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 18%
Researcher 6 14%
Student > Master 6 14%
Student > Doctoral Student 3 7%
Student > Postgraduate 3 7%
Other 9 20%
Unknown 9 20%
Readers by discipline Count As %
Medicine and Dentistry 19 43%
Engineering 4 9%
Nursing and Health Professions 3 7%
Computer Science 2 5%
Economics, Econometrics and Finance 1 2%
Other 3 7%
Unknown 12 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 August 2017.
All research outputs
#14,638,545
of 23,881,329 outputs
Outputs from BMC Cancer
#3,329
of 8,483 outputs
Outputs of similar age
#171,486
of 315,435 outputs
Outputs of similar age from BMC Cancer
#43
of 119 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,483 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,435 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.