Impact of radiation dose and iterative reconstruction on pulmonary nodule measurements at chest CT: a phantom study

Kim, Hyungjin; Park, Chang Min; Chae, Hee Dong; Lee, Sang Min; Goo, Jin Mo

doi:10.5152/dir.2015.14541

Cited by 20 publications

(21 citation statements)

References 23 publications

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“…SNR was calculated using the following equation: SNR = mean attenuation of nodule (Mn) / SD of nodule. CNR was calculated using the following equation: CNR = ([Mn − Mb] / SDb) ( 10 19 20 ).…”

Section: Methodsmentioning

confidence: 99%

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

Lee

Goo

2018

Korean J Radiol

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ObjectiveTo describe the quantitative image quality and histogram-based evaluation of an iterative reconstruction (IR) algorithm in chest computed tomography (CT) scans at low-to-ultralow CT radiation dose levels.Materials and MethodsIn an adult anthropomorphic phantom, chest CT scans were performed with 128-section dual-source CT at 70, 80, 100, 120, and 140 kVp, and the reference (3.4 mGy in volume CT Dose Index [CTDIvol]), 30%-, 60%-, and 90%-reduced radiation dose levels (2.4, 1.4, and 0.3 mGy). The CT images were reconstructed by using filtered back projection (FBP) algorithms and IR algorithm with strengths 1, 3, and 5. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were statistically compared between different dose levels, tube voltages, and reconstruction algorithms. Moreover, histograms of subtraction images before and after standardization in x- and y-axes were visually compared.ResultsCompared with FBP images, IR images with strengths 1, 3, and 5 demonstrated image noise reduction up to 49.1%, SNR increase up to 100.7%, and CNR increase up to 67.3%. Noteworthy image quality degradations on IR images including a 184.9% increase in image noise, 63.0% decrease in SNR, and 51.3% decrease in CNR, and were shown between 60% and 90% reduced levels of radiation dose (p < 0.0001). Subtraction histograms between FBP and IR images showed progressively increased dispersion with increased IR strength and increased dose reduction. After standardization, the histograms appeared deviated and ragged between FBP images and IR images with strength 3 or 5, but almost normally-distributed between FBP images and IR images with strength 1.ConclusionThe IR algorithm may be used to save radiation doses without substantial image quality degradation in chest CT scanning of the adult anthropomorphic phantom, down to approximately 1.4 mGy in CTDIvol (60% reduced dose).

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Section: Methodsmentioning

confidence: 99%

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

Lee

Goo

2018

Korean J Radiol

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“…Volume has been examined for its potential for earlier determination of change in nodule size compared to a measurement of maximum diameter from a single slice (1) typically used in clinical practice. Numerous studies have been conducted to examine and quantify the interrelated effects of imaging protocols, nodule characteristics, and estimation methods on the measurement error of lung nodule volume, as summarized in two reviews on the subject published in 2009 (2) and 2014 (3) and presented in subsequent publications (4)(5)(6)(7)(8)(9)(10)(11). However, most of the aforementioned studies have focused on the measurement of solid pulmonary nodules, defined as those that completely obscure the lung parenchyma (12).…”

Section: Introductionmentioning

confidence: 99%

Quantitative assessment of nonsolid pulmonary nodule volume with computed tomography in a phantom study

Gavrielides

Berman

Supanich

et al. 2017

Quant. Imaging Med. Surg.

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Background: To assess the volumetric measurement of small (≤1 cm) nonsolid nodules with computed tomography (CT), focusing on the interaction of state of the art iterative reconstruction (IR) methods and dose with nodule densities, sizes, and shapes. Results: Density had the most important effect on measurement error followed by the interaction of density with nodule size. The nonsolid −630 HU nodules had high accuracy and precision at levels comparable to solid (−10 HU) nonsolid, regardless of reconstruction method and with CTDI vol as low as 0.6 mGy. PB was <5% and <11% for the 10-and 5-mm in nominal diameter −630 HU nodules respectively, and RC was <5% and <12% for the same nodules. For nonsolid −800 HU nodules, PB increased to <11% and <30% for the 10-and 5-mm nodules respectively, whereas RC increased slightly overall but varied widely across dose and reconstruction algorithms for the 5-mm nodules. Model-based IR improved measurement accuracy for the 5-mm, low-density (−800, −630 HU) nodules. For other nodules the effect of reconstruction method was small. Dose did not affect volumetric accuracy and only affected slightly the precision of 5-mm nonsolid nodules.Conclusions: Reasonable values of both accuracy and precision were achieved for volumetric measurements of all 10-mm nonsolid nodules, and for the 5-mm nodules with −630 HU or higher density, when derived from scans acquired with below screening dose levels as low as 0.6 mGy and regardless of reconstruction algorithm.

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“…However, measuring the solid component within a SSN is more challenging than measuring solid nodules, because there is a smaller difference in the attenuation coefficient with its boundary, and it could be more susceptible to increased image noise. Although previous studies have revealed that SSNs could be reliably measured with low-dose unenhanced CT using a chest phantom ( 16 29 ), there has been no study that has investigated accuracy of low-dose unenhanced CT in measuring the size of the solid component of SSNs in vivo . Therefore, we compared measurement accuracy in diagnosing invasive adenocarcinomas between low-dose unenhanced CT and standard-dose enhanced CT, and revealed that there was no clinically significant difference between these protocols.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, the role of low-dose chest CT in managing patients with SSNs has become increasingly crucial, with implementation of lung cancer CT screening ( 13 14 15 ). The Lung CT Screening Reporting and Data System (Lung-RADS) suggests a different patient management guideline based on classification and size measurement of SSNs on low-dose chest CT ( 16 ). Low-dose chest CT is used for determination of initial patient management as well as for follow-up of incidentally detected SSNs to evaluate their persistence and size according to the Fleischner Society guidelines ( 12 ).…”

Section: Introductionmentioning

confidence: 99%

Diameter of the Solid Component in Subsolid Nodules on Low-Dose Unenhanced Chest Computed Tomography: Measurement Accuracy for the Prediction of Invasive Component in Lung Adenocarcinoma

et al. 2018

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ObjectiveTo determine if measurement of the diameter of the solid component in subsolid nodules (SSNs) on low-dose unenhanced chest computed tomography (CT) is as accurate as on standard-dose enhanced CT in prediction of pathological size of invasive component of lung adenocarcinoma.Materials and MethodsFrom February 2012 to October 2015, 114 SSNs were identified in 105 patients that underwent low-dose unenhanced and standard-dose enhanced CT pre-operatively. Three radiologists independently measured the largest diameter of the solid component. Intraclass correlation coefficients (ICCs) were used to assess inter-reader agreement. We estimated measurement differences between the size of solid component and that of invasive component. We measured diagnostic accuracy of the prediction of invasive adenocarcinoma using a size criterion of a solid component ≥ 6 mm, and compared them using a generalized linear mixed model.ResultsInter-reader agreement was excellent (ICC, 0.84.0.89). The mean ± standard deviation of absolute measurement differences between the solid component and invasive component was 4 ± 4 mm in low-dose unenhanced CT and 5 ± 4 mm in standard-dose enhanced CT. Diagnostic accuracy was 81.3% (95% confidence interval, 76.7.85.3%) in low-dose unenhanced CT and 76.6% (71.8.81.0%) in standard-dose enhanced CT, with no statistically significant difference (p = 0.130).ConclusionMeasurement of the diameter of the solid component of SSNs on low-dose unenhanced chest CT was as accurate as on standard-dose enhanced CT for predicting the invasive component. Thus, low-dose unenhanced CT may be used safely in the evaluation of patients with SSNs.

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Impact of radiation dose and iterative reconstruction on pulmonary nodule measurements at chest CT: a phantom study

Cited by 20 publications

References 23 publications

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

Quantitative Image Quality and Histogram-Based Evaluations of an Iterative Reconstruction Algorithm at Low-to-Ultralow Radiation Dose Levels: A Phantom Study in Chest CT

Quantitative assessment of nonsolid pulmonary nodule volume with computed tomography in a phantom study

Diameter of the Solid Component in Subsolid Nodules on Low-Dose Unenhanced Chest Computed Tomography: Measurement Accuracy for the Prediction of Invasive Component in Lung Adenocarcinoma

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