Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need?

Sarmento, S.; Mendes, Bruno; Gouvêa, Margarida

doi:10.1002/acm2.12240

Cited by 6 publications

(5 citation statements)

References 22 publications

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“…Unfortunately, unlike the observation that d w increases with age for the pediatric population [ 28 ], no significant correlation was observed between d w and age for chest and abdomen-pelvis CT, which is attributed to the lack of growth of d w with the increasing ages of adult patients. However, similar to previous results reported by Menke [ 20 , 25 ], we also found that both body weight and BMI strongly correlated with d w in chest and abdomen-pelvis, despite different populations in Asian-Pacific and European-American regions. Thus, age cannot be used to generate f for calculating SSDEs in adult patients.…”

Section: Discussionsupporting

confidence: 92%

“…Sarmento et al's study reported that d w is a function of patient weight, suggesting that the calculation of SSDEs could be simplified using weight [20,21]. To the best of our knowledge, there have been no previous studies on the calculation of SSDE from the chest and abdomen-pelvic CT examinations based on the correlations of body weight, BMI, and d w .…”

Section: Introductionmentioning

confidence: 99%

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Size-Specific Dose Estimates of Radiation Based on Body Weight and Body Mass Index for Chest and Abdomen-Pelvic CTs

Wang

Pei

et al. 2020

BioMed Research International

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Background. To correlate body weight, body mass index (BMI), and water-equivalent diameter (dw) and to assess size-specific dose estimates (SSDEs) based on body weight and BMI for chest and abdomen-pelvic CT examinations. Methods. An in-house program was used to calculate dw, size-dependent conversion factor (f), and SSDE for 1178 consecutive patients undergoing chest and abdomen-pelvic CT examinations. Associations among body weight, BMI, and dw were determined, and linear equations were generated using linear regression analysis of the first 50% of the patient population. SSDEs (SSDEweight and SSDEBMI) were calculated based on body weight and BMI as dw surrogates on the second 50% of the patient population. Mean root-mean-square errors of SSDEweight and SSDEBMI were computed with SSDE from the axial images as reference values. Results. Both body weight and BMI correlated strongly with dw for the chest (r=0.85, 0.87, all p<0.001) and abdomen-pelvis (r=0.85, 0.86, all p<0.001). Mean values of SSDEweight and SSDEBMI based on the linear equations for body weight, BMI, and dw were in close agreement with SSDE from the axial images, with overall mean root-mean-square errors of 0.62 mGy (6.10%) and 0.57 mGy (5.65%), for chest, and 0.76 mGy (5.61%) and 0.71 mGy (5.22%), for abdomen-pelvis, respectively. Conclusions. Both body weight and BMI, serving as dw surrogates, can be used to calculate SSDEs in the chest and abdomen-pelvis CT examinations, providing values comparable to SSDEs from the axial images, with an overall mean root-mean-square error of less than 0.76 mGy or 6.10%.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Size-Specific Dose Estimates of Radiation Based on Body Weight and Body Mass Index for Chest and Abdomen-Pelvic CTs

Wang

Pei

et al. 2020

BioMed Research International

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“…The accuracy achieved in the SSDE and D W computations and the very small time for processing an entire CT study allow us to compute the water-equivalent diameter averaged over the slice D w_ave ( 17 ), a quantity favorable for protocol optimization ( 17 ). Based on the authors’ knowledge, there are no previous studies showing such small computational times allowing for clinical real-time computation of size-specific dosimetric quantities.…”

Section: Discussionmentioning

confidence: 99%

Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study

Porzio

Anam

2022

Front. Oncol.

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BackgroundCurrently, the volume computed tomography dose index (CTDIvol), the most-used quantity to express the output dose of a computed tomography (CT) patient’s dose, is not related to the real size and attenuation properties of each patient. The size-specific dose estimates (SSDE), based on the water-equivalent diameter (DW) overcome those issues. The proposed methods found in the literature do not allow real-time computation of DW and SSDE.PurposeThis study aims to develop a software to compute DW and SSDE in a real-time clinical workflow.MethodIn total, 430 CT studies and scans of a water-filled funnel phantom were used to compute accuracy and evaluate the times required to compute the DW and SSDE. Two one-sided tests (TOST) equivalence test, Bland–Altman analysis, and bootstrap-based confidence interval estimations were used to evaluate the differences between actual diameter and DW computed automatically and between DW computed automatically and manually.ResultsThe mean difference between the DW computed automatically and the actual water diameter for each slice is −0.027% with a TOST confidence interval equal to [−0.087%, 0.033%]. Bland–Altman bias is −0.009% [−0.016%, −0.001%] with lower limits of agreement (LoA) equal to −0.0010 [−0.094%, −0.068%] and upper LoA equal to 0.064% [0.051%, 0.077%]. The mean difference between DW computed automatically and manually is −0.014% with a TOST confidence interval equal to [−0.056%, 0.028%] on phantom and 0.41% with a TOST confidence interval equal to [0.358%, 0.462%] on real patients. The mean time to process a single image is 13.99 ms [13.69 ms, 14.30 ms], and the mean time to process an entire study is 11.5 s [10.62 s, 12.63 s].ConclusionThe system shows that it is possible to have highly accurate DW and SSDE in almost real-time without affecting the clinical workflow of CT examinations.

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“…Automatic noise calculation performed directly from the patient image is an important factor to optimize the radiation dose received by the patient. Automated dose calculation received by patients using the concept of size-specific dose estimate (SSDE) has been widely reported [15,[26][27][28]. While automated noise calculations performed directly from patient images have been reported previously [20,24], they have been limited to certain body parts such as the abdomen or thorax.…”

Section: Discussionmentioning

confidence: 99%

An Improved Method of Automated Noise Measurement System in CT Images

et al. 2021

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Background: It is necessary to have an automated noise measurement system working accurately to optimize dose in computerized tomography (CT) examinations.Objective: This study aims to develop an algorithm to automate noise measurement that can be implemented in CT images of all body regions. Materials and Methods:In this retrospective study, our automated noise measurement method consists of three steps as follows: the first is segmenting the image of the patient. The second is developing a standard deviation (SD) map by calculating the SD value for each pixel with a sliding window operation. The third step is estimating the noise as the smallest SD from the SD map. The proposed method was applied to the images of a homogenous phantom and a full body adult anthropomorphic phantom, and retrospectively applied to 27 abdominal images of patients.Results: For a homogeneous phantom, the noises calculated using our proposed and previous algorithms have a linear correlation with R 2 = 0.997. It is found that the noise magnitude closely follows the magnitude of the water equivalent diameter (D w ) in all body regions. The proposed algorithm is able to distinguish the noise magnitude due to variations in tube currents and different noise suppression techniques such as strong, standard, mild, and weak ones in a reconstructed image using the AIDR 3D algorithm. Conclusion: An automated noise calculation has been proposed and successfullyimplemented in all body regions. It is not only accurate and easy to implement but also not influenced by the subjectivity of user.

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Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need?

Cited by 6 publications

References 22 publications

Size-Specific Dose Estimates of Radiation Based on Body Weight and Body Mass Index for Chest and Abdomen-Pelvic CTs

Size-Specific Dose Estimates of Radiation Based on Body Weight and Body Mass Index for Chest and Abdomen-Pelvic CTs

Real-time fully automated dosimetric computation for CT images in the clinical workflow: A feasibility study

An Improved Method of Automated Noise Measurement System in CT Images

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