Diagnostic value of a spiral breast computed tomography system equipped with photon counting detector technology in patients with implants

Ruby, Lisa; Shim, Sojin; Berger, Nicole; Marcon, Magda; Frauenfelder, Thomas; Boss, Andreas

doi:10.1097/md.0000000000020797

Cited by 11 publications

(13 citation statements)

References 40 publications

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“…Dedicated B-CT represents a new development in breast imaging with few recently published studies showing the first applications in a clinical setting. 5,6,9,22 Compared with the more established tomosynthesis, B-CT offers the possibility to obtain true 3-dimensional imaging without breast compression. Major drawbacks are still the limited availability and the lack of studies comparing its diagnostic performance with mammography and/or tomosynthesis.…”

Section: Discussionmentioning

confidence: 99%

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Breast Computed Tomography

et al. 2021

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ObjectivesThis study aimed to evaluate the diagnostic performance of the maximum intensity projection (MIP) reformations of breast computed tomography (B-CT) images as a stand-alone method for the detection and characterization of breast imaging findings.Materials and MethodsA total of 160 women undergoing B-CT between August 2018 and December 2020 were retrospectively included; 80 patients with known breast imaging findings were matched with 80 patients without imaging findings according to age and amount of fibroglandular tissue (FGT). A total of 71 benign and 9 malignant lesions were included. Images were evaluated using 15-mm MIP in 3 planes by 2 radiologists with experience in B-CT. The presence of lesions and FGT were evaluated, using the BI-RADS classification. Interreader agreement and descriptive statistics were calculated.ResultsThe interreader agreement of the 2 readers for finding a lesion (benign or malignant) was 0.86 and for rating according to BI-RADS classification was 0.82. One of 9 cancers (11.1%) was missed by both readers due to dense breast tissue. BI-RADS 1 was correctly applied to 73 of 80 patients (91.3%) by reader 1 and to 74 of 80 patients (92.5%) by reader 2 without recognizable lesions. BI-RADS 2 or higher with a lesion in at least one of the breasts was correctly applied in 69 of 80 patients (86.3%) by both readers. For finding a malignant lesion, sensitivity was 88.9% (95% confidence interval [CI], 51.75%–99.72%) for both readers, and specificity was 99.3% (95% CI, 96.4%–100%) for reader 1 and 100% (95% CI, 97.20%–100.00%) for reader 2.ConclusionsEvaluation of B-CT images using the MIP reformations may help to reduce the reading time with high diagnostic performance and confidence.

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Section: Discussionmentioning

confidence: 99%

“…Dedicated B-CT represents a new development in breast imaging with few recently published studies showing the first applications in a clinical setting 5,6,9,22 . Compared with the more established tomosynthesis, B-CT offers the possibility to obtain true 3-dimensional imaging without breast compression.…”

Section: Discussionmentioning

confidence: 99%

Breast Computed Tomography

et al. 2021

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“…Based on the results of previously conducted image quality studies, 10,13 the X‐ray tube current was set to 32 mA. The detailed examination acquisition parameters are presented in 12–15,17 . The BCT image datasets were reconstructed with a soft kernel (Shepp–Logan) at (300 μm) 3 voxel size using a Feldkamp‐type filtered back projection (FBP) algorithm 18 …”

Section: Methodsmentioning

confidence: 99%

“…Further information about the MC dose simulation program including the particle transport can be found in 23 . The MC technique was previously validated for the BCT scanner in the University Hospital Zurich by comparing the simulated dose to the measured dose based on the weighted CT dose index (CTDI w ) using an ionization chamber (DCT10, Iba Dosimetry GmbH, Schwarzenbruck, Germany) connected to a dosimetry tool (MagicMaX, Iba Dosimetry GmbH, Schwarzenbruck, Germany) on a standard CTDI head phantom composed of PMMA material (2‐part PMMA CT‐phantom, Iba Dosimetry GmbH, Schwarzenbruck, Germany) 12,13 . The absorbed dose was simulated by using 2.0 × 10 7 photons per projection with 2000 projections per rotation.…”

Section: Methodsmentioning

confidence: 99%

Radiation dose estimates based on Monte Carlo simulation for spiral breast computed tomography imaging in a large cohort of patients

Shim

Kolditz²,

Steiding³

et al. 2023

Medical Physics

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Background: Spiral breast computed tomography (BCT) equipped with a photon-counting detector (PCD) is a new radiological modality allowing for the compression-free acquisition of high-resolution 3-D datasets of the breast.Optimized dose exposu04170/re setups according to breast size were previously proposed but could not effectively be applied in a clinical environment due to ambiguity in measuring breast size.Purpose: This study aims to report the standard radiation dose values in a large cohort of patients examined with BCT, and to provide a mathematical model to estimate radiation dose based on morphological features of the breast. Methods: This retrospective study was conducted on 1657 BCT examinations acquired between 2018 and 2021 from 829 participants (57 ± 10 years, all female). Applying a dedicated breast tissue segmentation algorithm and Monte Carlo (MC) simulation, mean absorbed dose (MAD), mean glandular dose (MGD), mean skin dose (MSD), maximum glandular dose (maxGD), and maximum skin dose (maxSD) were calculated and related to morphological features such as breast volume, effective diameter, breast length, skin volume, and glandularity. Effective dose (ED) was calculated by applying the corresponding beam and tissue weighting factors, 1 Sv/Gy and 0.12 per breast. Relevant morphological features predicting dose values were identified based on the Spearman's rank correlation coefficient. Exponential or bi-exponential models predicting the dose values as a function of morphological features were fitted by using a nonlinear least squares (LS) method. The models were validated by assessing R 2 and residual standard error (RSE). Results: The most relevant morphological features for radiation dose estimation were the breast volume (correlation coefficient: −0.8), diameter (−0.7), and length (−0.6). The glandularity presented a weak-positive correlation (0.4) with MGD and maxGD due to the inhomogeneous distribution of the glandularity and absorbed dose in the 3-D breast volume. The standard MGDs were calculated to be 7.3 ± 0.7, 6.5 ± 0.3, and 5.9 ± 0.3 mGy, MADs to 7.6 ± 0.8, 6.8 ± 0.3, and 6.2 ± 0.3 mGy, maxSDs to 19.9 ± 1.6, 19.5 ± 0.5, and 18.9 ± 0.5 mGy, and EDs to 0.88 ± 0.08, 0.78 ± 0.04, and 0.72 ± 0.04 mSv for small, medium, and large breasts with average breast lengths of 5.9 ± 1.6, 8.7 ± 1.3, and 12.2 ± 2.0 cm, respectively. The estimated glandularity -23.1 ± 16.9, 12.5 ± 11.4, and 6.9 ± 7.3% from small to large breasts. The mathematical models were able to estimate the MAD, MGD, MSD, and maxSD as a function of each morphological feature with only upto 0.5 mGy RSE.

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“…The HU values were reliable across a variety of conditions such as breast size or implant presence except the area where artifacts appear. 12 , 13 , 14 …”

Section: Methodsmentioning

confidence: 99%

Fully automated breast segmentation on spiral breast computed tomography images

Shim

Cester

Ruby

et al. 2022

J Applied Clin Med Phys

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INTRODUCTION The quantification of the amount of the glandular tissue and breast density is important to assess breast cancer risk. Novel photon-counting breast computed tomography (CT) technology has the potential to quantify them. For accurate analysis, a dedicated method to segment the breast components-the adipose and glandular tissue, skin, pectoralis muscle, skinfold section, rib, and implant-is required. We propose a fully automated breast segmentation method for breast CT images. METHODS The framework consists of four parts: (1) investigate, (2) segment the components excluding adipose and glandular tissue, (3) assess the breast density, and (4) iteratively segment the glandular tissue according to the estimated density. For the method, adapted seeded watershed and region growing algorithm were dedicatedly developed for the breast CT images and optimized on 68 breast images. The segmentation performance was qualitatively (five-point Likert scale) and quantitatively (Dice similarity coefficient [DSC] and difference coefficient [DC]) demonstrated according to human reading by experienced radiologists. RESULTS The performance evaluation on each component and overall segmentation for 17 breast CT images resulted in DSCs ranging 0.90-0.97 and in DCs 0.01-0.08. The readers rated 4.5-4.8 (5 highest score) with an excellent inter-reader agreement. The breast density varied by 3.7%-7.1% when including mis-segmented muscle or skin. CONCLUSION The automatic segmentation results coincided with the human expert's reading. The accurate segmentation is important to avoid the significant bias in breast density analysis. Our method enables accurate quantification of the breast density and amount of the glandular tissue that is directly related to breast cancer risk.

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Diagnostic value of a spiral breast computed tomography system equipped with photon counting detector technology in patients with implants

Cited by 11 publications

References 40 publications

Breast Computed Tomography

Breast Computed Tomography

Radiation dose estimates based on Monte Carlo simulation for spiral breast computed tomography imaging in a large cohort of patients

Fully automated breast segmentation on spiral breast computed tomography images

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