↓ Skip to main content

Approximation of head and neck cancer volumes in contrast enhanced CT

Overview of attention for article published in Cancer Imaging, September 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
31 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
Approximation of head and neck cancer volumes in contrast enhanced CT
Published in
Cancer Imaging, September 2015
DOI 10.1186/s40644-015-0051-3
Pubmed ID
Authors

D. Dejaco, C. Url, V. H. Schartinger, A. K. Haug, N. Fischer, D. Riedl, A. Posch, H. Riechelmann, G. Widmann

Abstract

Tumor volume may serve as a predictor of response to radiochemotherapy (RCT) in head and neck squamous cell carcinoma (HNSCC). Computer assisted tumor volumetry requires time-consuming slice-by-slice manual or semi-automated segmentation. We questioned how accurately primary tumor and suspect cervical lymph node (LN) volumes can be approximated by the maximum tumor diameters in three dimensions. In contrast-enhanced diagnostic CT scans of 74 patients with incident advanced HNSCC, manual slice-by-slice segmentation volumetry of primary tumor, total- and largest suspect cervical LN served as the reference method. In the same scans, maximum orthogonal diameters were measured using the distance measurement tool in standard visualization software in axial and coronal sections. From these diameters, approximate volumes were calculated using the cubic and ellipsoid formula. A second segmentation volumetry was performed in contrast enhanced radiotherapy-planning CT scans obtained prior to primary concurrent RCT 24 days (+/- 13 days) following the initial diagnostic CT scans. Intraclass correlation coefficients and Bland-Altman analyses were used to compare results. Slice-by-slice manual segmentation volumetry of primary and LN volumes revealed a lognormal distribution and ranged from 0 to 86 ml and 0 to 129 ml, respectively. Volume approximations in diagnostic CT scans with the ellipsoid formula resulted in an -8 % underestimation of tumor volumes (95 % CI -14 % to -1 %; p = 0.022) and an -18 % underestimation of suspect cervical LN volumes (95 % CI -25 % to -12 %; p = 0.001). Inter rater intraclass correlation for primaries was 0.95 (95 % CI +0.92 to +0.97; p = 0.001), and intra rater intraclass correlation was 0.99 (95 % CI +0.98 to +0.99; p = 0.001). The cubic formula resulted in pronounced overestimation of primary and LN volumes. Primary tumor volumes obtained by the second segmentation volumetry in radiotherapy-planning CT scans obtained on average 24 days following the initial volumetry resulted in larger primary tumor volumes (mean bias +28 %, 95 % CI +14 % to +41 %; p = 0.001). Tumor volume increase correlated with time between the diagnostic and planning CTs (r = 0.24, p = 0.05) and was approximately 1 % per day. Ellipsoid approximations of tumor and lymph node volumes in HNSCC using maximum orthogonal diameters underestimates volumes based on segmentation in multiple slices. Due to time difference and safety margins, segmented volumes in radiotherapy-planning CT scans tend to be larger than in diagnostic CT scans. Ellipsoid approximations of tumor and lymph node volumes in HNSCC are easily available from diagnostic CT scans. Volume estimates are applicable over a wide range of tumor and LN sizes and may be useful in clinical decision-making and oncologic research.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 16%
Student > Bachelor 5 16%
Student > Ph. D. Student 4 13%
Student > Doctoral Student 3 10%
Other 3 10%
Other 7 23%
Unknown 4 13%
Readers by discipline Count As %
Medicine and Dentistry 13 42%
Nursing and Health Professions 5 16%
Mathematics 2 6%
Biochemistry, Genetics and Molecular Biology 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 7 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 February 2016.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Cancer Imaging
#320
of 674 outputs
Outputs of similar age
#171,190
of 286,197 outputs
Outputs of similar age from Cancer Imaging
#2
of 12 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 674 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 286,197 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 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 66% of its contemporaries.