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Liver detection algorithm improves abdomen image quality

Abstract
Philips CT Clinical Science Philips Healthcare • USA

Purpose of the study

The purpose of the study was to evaluate the efficacy of the liver detection algorithm on an abdomen CT scan to improve the image quality (IQ) of abdominal organs.

 

The following is a summary of the study presented at ECR 2019 by Dr. Lau and colleagues from Monash Medical Center in Australia.

Overview

CT is routinely used for evaluation of abdominal organs. Optimizing radiation dose to get good image quality on an abdomen CT scan is of utmost importance, especially for organs such as the liver. Hypo- and hyper-vascular lesions in the liver may have very subtle presentation compared to liver parenchyma, making it very difficult to identify them. The detection of these lesions is highly related to the image noise within the liver parenchyma, which is related to the radiation dose and patient size. The noise may increase with an increase in the size of the patient. A new liver detection algorithm was developed that allows the increase in target radiation dose to the liver region while maintaining the overall dose to the abdomen in the scanning range. The purpose of this study was to evaluate the efficacy of the liver identification algorithm on the image quality of the liver and other abdominal organs.

Methods

The study was undertaken using a Philips Ingenuity CT scanner (128 slice) and included a total of 80 consecutive patients divided into two groups, with 40 randomly selected patients evaluated using the liver detection algorithm and 40 patients evaluated using conventional CT. Both groups had identical baseline scanning protocols except for dose modulation parameters. The dose modulation profile in the liver detection group did not reach the same peak mAs in Z direction as the conventional scanning group. The liver was automatically identified in the liver detection group and received more dose; however, overall radiation dose in both the groups was the same, but the distribution of dose over the entire scanning range was different.

 

CT studies were reviewed by two radiologists to evaluate and compare the image quality of the abdominal organs using a 3-point scale (1- poor, 2- good, 3- excellent) between the two groups. Image noise was recorded by placing an ROI in the liver, pancreas, kidney, psoas muscle and bladder. Radiation doses were recorded and compared between the two groups.

Results

A higher percentage of patients received a ranking of “excellent” in the liver detection group as compared to the conventional group. The image quality rankings improved in 26% of the patients for liver, 9% for spleen, 7.5% for pancreas and 12.2% for kidney. Noise decreased in the liver detection group by 13% for liver, 15.8% for spleen, 13.3% for pancreas and 14.2% for kidney.

 

Mean radiation dose was 6% lower in the liver detection group as compared to the conventional scanning group.

Conclusion

Organ-based dose modulation using the liver detection algorithm can improve the image quality of abdominal organs while reducing noise without a significant change in radiation dose.

Clinical relevance

Image quality of abdominal organs can be improved using the liver detection algorithm.

Reference

Ardley N, Buchan K, Mak L, Lau K. Efficacy of a liver detection algorithm for image quality improvement in CT abdomen. Poster presented at European Society of Radiology; March 6-10, 2014; Vienna.


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Jun 18, 2019

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Abstract
Ingenuity CT
abdomen, bladder, Body, dose, image quality, kidney/renal, lesion, liver, pancreas, spleen
 

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