Potential of spiral breast computed tomography to increase patient comfort compared to DM

Wetzl, Matthias; Wenkel, Evelyn; Dietzel, Matthias; Siegler, Lisa; Emons, Julius; Dethlefsen, Ebba; Heindl, Felix; Kühl, Christiane; Uder, Michael; Ohlmeyer, Sabine

doi:10.1016/j.ejrad.2021.110038

Cited by 11 publications

(6 citation statements)

References 26 publications

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“…This retrospective study was approved by the local ethics committee and all patients signed informed consent for the scientific evaluation of the imaging and clinical data. All patients receiving PC-BCT examination at our institution signed informed consent about the “off-label” use of PC-BCT, including all its benefits (no compression, improved lesion detectability compared to mammography) and disadvantages (higher radiation dose, long evaluation time, not implemented in any guidelines yet) [ 21 – 23 ]. A retrospective search of patient data in the local database resulted in 520 patients receiving PC-BCT between January and August 2021.…”

Section: Methodsmentioning

confidence: 99%

“…Spiral breast CT using photon-counting detector technology (photon-counting breast CT, PC-BCT) offers a truly three-dimensional breast imaging modality. Although not implemented in any guidelines yet, it might provide an alternative to mammography or breast-MRI for BC screening, combining improved patient comfort, fast image acquisition, and good visibility of microcalcifications [ 21 , 22 ]. Regarding lesion detection, the sensitivity of PC-BCT in dense tissue was reported to be higher compared to digital mammography at comparable radiation dose [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

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Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

et al. 2022

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Background We investigated whether features derived from texture analysis (TA) can distinguish breast density (BD) in spiral photon-counting breast computed tomography (PC-BCT). Methods In this retrospective single-centre study, we analysed 10,000 images from 400 PC-BCT examinations of 200 patients. Images were categorised into four-level density scale (a–d) using Breast Imaging Reporting and Data System (BI-RADS)-like criteria. After manual definition of representative regions of interest, 19 texture features (TFs) were calculated to analyse the voxel grey-level distribution in the included image area. ANOVA, cluster analysis, and multinomial logistic regression statistics were used. A human readout then was performed on a subset of 60 images to evaluate the reliability of the proposed feature set. Results Of the 19 TFs, 4 first-order features and 7 second-order features showed significant correlation with BD and were selected for further analysis. Multinomial logistic regression revealed an overall accuracy of 80% for BD assessment. The majority of TFs systematically increased or decreased with BD. Skewness (rho -0.81), as a first-order feature, and grey-level nonuniformity (GLN, -0.59), as a second-order feature, showed the strongest correlation with BD, independently of other TFs. Mean skewness and GLN decreased linearly from density a to d. Run-length nonuniformity (RLN), as a second-order feature, showed moderate correlation with BD, but resulted in redundant being correlated with GLN. All other TFs showed only weak correlation with BD (range -0.49 to 0.49, p < 0.001) and were neglected. Conclusion TA of PC-BCT images might be a useful approach to assess BD and may serve as an observer-independent tool.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

et al. 2022

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“…Wetzl et al reported a significant reduction of pain in women receiving BCT compared to digital mammography in their patient cohort. 3,4,28 Moreover, BCT reduces the effect of tissue overlay, as observed in superimposed mammograms. As a result, the sensitivity of BCT is reported to be higher compared to mammography at a similar radiation dose, especially in dense breast tissue.…”

Section: Introductionmentioning

confidence: 97%

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle

Landsmann

Ruppert²,

Borkowski

et al. 2023

Clinical Imaging

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“…In SBCT, the breast does not need to be compressed during examination. Thus, SBCT offers a higher patient comfort than mammography or DBT, especially for women with sensitive breasts [17]. It can be used for monitoring during neoadjuvant chemotherapy or after BCS if a recurrence of breast cancer is suspected [18].…”

Section: Introductionmentioning

confidence: 99%

Feasibility of In Vivo Metal Artifact Reduction in Contrast-Enhanced Dedicated Spiral Breast Computed Tomography

Wetzl,

Wenkel,

Steiding

et al. 2023

Diagnostics

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Background: Radiopaque breast markers cause artifacts in dedicated spiral breast-computed tomography (SBCT). This study investigates the extent of artifacts in different marker types and the feasibility of reducing artifacts through a metal artifact reduction (MAR) algorithm. Methods: The pilot study included 18 women who underwent contrast-enhanced SBCT. In total, 20 markers of 4 different types were analyzed for artifacts. The extent of artifacts with and without MAR was measured via the consensus of two readers. Image noise was quantitatively evaluated, and the effect of MAR on the detectability of breast lesions was evaluated on a 3-point Likert scale. Results: Breast markers caused significant artifacts that impaired image quality and the detectability of lesions. MAR decreased artifact size in all analyzed cases, even in cases with multiple markers in a single slice. The median length of in-plain artifacts significantly decreased from 31 mm (range 11–51 mm) in uncorrected to 2 mm (range 1–5 mm) in corrected images (p ≤ 0.05). Artifact size was dependent on marker size. Image noise in slices affected by artifacts was significantly lower in corrected (13.6 ± 2.2 HU) than in uncorrected images (19.2 ± 6.8 HU, p ≤ 0.05). MAR improved the detectability of lesions affected by artifacts in 5 out of 11 cases. Conclusion: MAR is feasible in SBCT and improves the image quality and detectability of lesions.

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Potential of spiral breast computed tomography to increase patient comfort compared to DM

Cited by 11 publications

References 26 publications

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle

Feasibility of In Vivo Metal Artifact Reduction in Contrast-Enhanced Dedicated Spiral Breast Computed Tomography

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