Incidental findings on total-body CT scans in trauma patients

Injury ◽  
2014 ◽  
Vol 45 (5) ◽  
pp. 840-844 ◽  
Author(s):  
J.C. Sierink ◽  
T.P. Saltzherr ◽  
M.J.A.M. Russchen ◽  
S.M.M. de Castro ◽  
L.F.M. Beenen ◽  
...  
2016 ◽  
Vol 27 (6) ◽  
pp. 2451-2462 ◽  
Author(s):  
K. Treskes ◽  
◽  
S. A. Bos ◽  
L. F. M. Beenen ◽  
J. C. Sierink ◽  
...  

2016 ◽  
Vol 27 (6) ◽  
pp. 2463-2463 ◽  
Author(s):  
K. Treskes ◽  
◽  
S. A. Bos ◽  
L. F. M. Beenen ◽  
J. C. Sierink ◽  
...  

2018 ◽  
Vol 43 (2) ◽  
pp. 490-496 ◽  
Author(s):  
Kaij Treskes ◽  
◽  
Teun P. Saltzherr ◽  
Michael J. R. Edwards ◽  
Benn J. A. Beuker ◽  
...  

2013 ◽  
Vol 38 (4) ◽  
pp. 795-802 ◽  
Author(s):  
Joanne C. Sierink ◽  
Teun Peter Saltzherr ◽  
Ludo F. M. Beenen ◽  
Marjolein J. A. M. Russchen ◽  
Jan S. K. Luitse ◽  
...  

2014 ◽  
Vol 80 (9) ◽  
pp. 855-859 ◽  
Author(s):  
Katherine A. Baugh ◽  
Leonard J. Weireter ◽  
Jay N. Collins

The objective of this study was to investigate the prevalence of incidental findings in pan-computed tomography (CT) scans of trauma patients and the communication of significant findings requiring follow-up to the patient. A retrospective chart review of adult trauma patients was performed during the period of January 1, 2011, to August 31, 2011. During that period, 990 patient charts were examined and 555 charts were selected based on the inclusion criteria of a pan-CT scan including the head, neck, abdomen/pelvis, and chest. Patient demographics such as age, gender, mechanism of injury, and Injury Severity Score were collected. Nontraumatic incidental findings were analyzed to establish the prevalence of incidental findings among trauma patients. Discharge summaries were also examined for follow-up instructions to determine the effectiveness of communication of the significant findings. Between the 555 pan-CT scans (1759 total scans), 1706 incidental findings were identified with an incidence of 3.1 incidental findings per patient and with the highest concentration of findings occurring in the abdomen/pelvis. The majority of findings were benign including simple renal cysts with a prevalence of 7.7 per cent. However, 282 significant findings were identified that were concerning for possible malignancy or those requiring further evaluation, the most common of which were lung nodules, which accounted for 21.6 per cent of significant findings. However, only 32.6 per cent of significant findings were documented as reported to the patient. With the use of pan scans on trauma patients, many incidental findings have been identified to the benefit of the patient. The majority of these are clinically insignificant; however, only 32.6 per cent of potentially significant findings were communicated to the patient. The advantage of early detection comes from proper communication and this study demonstrates that there could be improvement in conveying findings to the patient.


2014 ◽  
Vol 219 (3) ◽  
pp. S78
Author(s):  
Maria Michailidou ◽  
Bellal Joseph ◽  
Viraj Pandit ◽  
Narong Kulvatunyou ◽  
Andrew L. Tang ◽  
...  

2021 ◽  
Vol 24 ◽  
pp. 101104
Author(s):  
Bruce Grattan ◽  
David Ledrick ◽  
John Doan ◽  
Zach Wise ◽  
John Leskovan

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3302 ◽  
Author(s):  
Alizé Lacoste Jeanson ◽  
Ján Dupej ◽  
Chiara Villa ◽  
Jaroslav Brůžek

BackgroundEstimating volumes and masses of total body components is important for the study and treatment monitoring of nutrition and nutrition-related disorders, cancer, joint replacement, energy-expenditure and exercise physiology. While several equations have been offered for estimating total body components from MRI slices, no reliable and tested method exists for CT scans. For the first time, body composition data was derived from 41 high-resolution whole-body CT scans. From these data, we defined equations for estimating volumes and masses of total body AT and LT from corresponding tissue areas measured in selected CT scan slices.MethodsWe present a new semi-automatic approach to defining the density cutoff between adipose tissue (AT) and lean tissue (LT) in such material. An intra-class correlation coefficient (ICC) was used to validate the method. The equations for estimating the whole-body composition volume and mass from areas measured in selected slices were modeled with ordinary least squares (OLS) linear regressions and support vector machine regression (SVMR).Results and DiscussionThe best predictive equation for total body AT volume was based on the AT area of a single slice located between the 4th and 5th lumbar vertebrae (L4-L5) and produced lower prediction errors (|PE| = 1.86 liters, %PE = 8.77) than previous equations also based on CT scans. The LT area of the mid-thigh provided the lowest prediction errors (|PE| = 2.52 liters, %PE = 7.08) for estimating whole-body LT volume. We also present equations to predict total body AT and LT masses from a slice located at L4-L5 that resulted in reduced error compared with the previously published equations based on CT scans. The multislice SVMR predictor gave the theoretical upper limit for prediction precision of volumes and cross-validated the results.


2018 ◽  
Vol 42 (2) ◽  
pp. 129-131
Author(s):  
S. Dios-Barbeito ◽  
V. Durán-Muñoz-Cruzado ◽  
C. Martín-García ◽  
M. Rubio-Manzanares-Dorado ◽  
F.J. Padillo-Ruiz ◽  
...  
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