Fully automated breast segmentation on spiral breast computed tomography images.

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.

Spiral breast computed tomography (CT): signal-to-noise and dose optimization using 3D-printed phantoms.

OBJECTIVES: To investigate the dependence of signal-to-noise ratio (SNR) and calculated average dose per volume of spiral breast-CT (B-CT) on breast size and breast density and to provide a guideline for choosing the optimal tube current for each B-CT examination. MATERIALS AND METHODS: Three representative B-CT datasets (small, medium, large breast size) were chosen to create 3D-printed breast phantoms. The phantoms were filled with four different agarose-oil-emulsions mimicking differences in breast densities. Phantoms were scanned in a B-CT system with systematic variation of the tube current (6, 12.5, 25, 32, 40, 50, 64, 80, 100, 125 mA). Evaluation of SNR and the average dose per volume using Monte Carlo simulations were performed for high (HR) and standard (STD) spatial resolution. RESULTS: SNR and average dose per volume increased with increasing tube current. Artifacts had negligible influence on image evaluation. SNR values ≥ 35 (HR) and ≥ 100 (STD) offer sufficient image quality for clinical evaluation with SNR being more dependent on breast density than on breast size. For an average absorbed dose limit of 6.5 mGy for the medium and large phantoms and 7 mGy for the small phantom, optimal tube currents were either 25 or 32 mA. CONCLUSIONS: B-CT offers the possibility to vary the X-ray tube current, allowing image quality optimization based on individual patient's characteristics such as breast size and density. This study describes the optimal B-CT acquisition parameters, which provide diagnostic image quality for various breast sizes and densities, while keeping the average dose at a level similar to digital mammography. KEY POINTS: • Image quality optimization based on breast size and density varying the tube current using spiral B-CT.

Quantitative Study on the Breast Density and the Volume of the Mammary Gland According to the Patient's Age and Breast Quadrant.

OBJECTIVES: Breast density is considered an independent risk factor for the development of breast cancer. This study aimed to quantitatively assess the percent breast density (PBD) and the mammary glands volume (MGV) according to the patient's age and breast quadrant. We propose a regression model to estimate PBD and MGV as a function of the patient's age. METHODS: The breast composition in 1027 spiral breast CT (BCT) datasets without soft tissue masses, calcifications, or implants from 517 women (57 ± 8 years) were segmented. The breast tissue volume (BTV), MGV, and PBD of the breasts were measured in the entire breast and each of the four quadrants. The three breast composition features were analyzed in the seven age groups, from 40 to 74 years in 5-year intervals. A logarithmic model was fitted to the BTV, and a multiplicative inverse model to the MGV and PBD as a function of age was established using a least-squares method. RESULTS: The BTV increased from 545 ± 345 to 676 ± 412 cm3, and the MGV and PBD decreased from 111 ± 164 to 57 ± 43 cm3 and from 21 ± 21 to 11 ± 9%, respectively, from the youngest to the oldest group (p < 0.05). The average PBD over all ages were 14 ± 13%. The regression models could predict the BTV, MGV, and PBD based on the patient's age with residual standard errors of 386 cm3, 67 cm3, and 13%, respectively. The reduction in MGV and PBD in each quadrant followed the ones in the entire breast. CONCLUSIONS: The PBD and MGV computed from BCT examinations provide important information for breast cancer risk assessment in women. The study quantified the breast mammary gland reduction and density decrease over the entire breast. It established mathematical models to estimate the breast composition features-BTV, MGV, and PBD, as a function of the patient's age.

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

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 non-linear least squares (LS) method. The models were validated by assessing R2 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. CONCLUSION: We presented the typical morphological features and standard dose values according to the breast size acquired from a large patient cohort. We established radiation dose estimation models allowing accurate estimation of dose values including MGD with an acceptable RSE based on each of the easily measured morphological features of the breast. Clinicians could use the breast length to operate as a dosimetric alert of the scanner prior to a BCT scan. Radiation exposure for BCT was lower than diagnostic mammography (MG) and cone-beam breast CT (BCT).

Diagnostic value of a spiral breast computed tomography system equipped with photon counting detector technology in patients with implants: An observational study of our initial experiences.

To evaluate the value of a breast computed tomography (CT) (B-CT) in assessing breast density, pathologies and implant integrity in women with breast implants.This retrospective study was approved by the local ethics committee. B-CT images of 21 women with implants (silicone/saline; 20 bilateral, 1 unilateral) who underwent opportunistic screening or diagnostic bilateral B-CT were included. Breast density, implant integrity, extensive capsular fibrosis, soft tissue lesions and micro-/macrocalcifications were rated. In 18 of the 21 women, an additional ultrasound and in two patients breast magnetic resonance imaging was available for comparison. The average dose was calculated for each breast using verified Monte Carlo simulations on 3D image data sets.Breast density was nearly completely fatty (ACR a) in two patients, scattered fibroglandular (ACR b) in five, heterogeneously dense (ACR c) in ten and very dense (ACR d) in four women. In three women showed a unilateral positive Linguine sign indicative of an inner capsule rupture. Extensive capsular fibrosis was found in three women. In three women, soft tissue lesions were depicted, which revealed to be cysts (n = 2) and lymph nodes (n = 1) on subsequent sonography. Diffuse, non-clustered microcalcifications were found in nine women. Eleven women showed cutaneous or intramammary macrocalcifications. Average dose was 6.45 mGy (range 5.81-7.28 mGy).In women with implants, B-CT presents a promising modality for evaluating breast density, implant integrity, extensive capsular fibrosis, soft tissue lesions and micro-/macrocalcifications without the need of breast compression utilizing a lower dose compared to doses reported for conventional four-view mammography.

Lesion Detectability and Radiation Dose in Spiral Breast CT With Photon-Counting Detector Technology: A Phantom Study.

OBJECTIVES: The aim of the article was to evaluate the lesion detectability, image quality, and radiation dose of a dedicated clinical spiral breast computed tomography (CT) system equipped with a photon-counting detector, and to propose optimal scan parameter settings to achieve low patient dose levels and optimal image quality. METHODS: A breast phantom containing inserts mimicking microcalcifications (diameters 196, 290, and 400 µm) and masses (diameters 1.8, 3.18, 4.76, and 6.32 mm) was examined in a spiral breast CT system with systematic variations of x-ray tube currents between 5 and 125 mA, using 2 slabs of 100 and 160 mm. Signal-to-noise ratio and contrast-to-noise ratio measurements were performed by region of interest analysis. Two experienced radiologists assessed the detectability of the inserts. The average absorbed dose was calculated in Monte Carlo simulations. RESULTS: Microcalcifications in diameters of 290 and 400 µm and masses in diameters of 3.18, 4.76, and 6.32 mm were visible for all tube currents between 5 and 125 mA. Soft tissue masses in a diameter of 1.8 mm were visible at tube currents of 25 mA and higher. Microcalcifications with a diameter of 196 µm were detectable at a tube current of 25 mA and higher in the small, and at a tube current of 40 mA and higher in the large slab. For the small and large breast, at a tube current of 25 and 40 mA, an average dose value of 4.30 ± 0.01 and 5.70 ± 0.02 mGy was calculated, respectively. CONCLUSIONS: Optimizing tube current of spiral breast CT according to the breast size enables the visualization of microcalcifications as small as 196 µm while keeping dose values in the range of conventional mammography.

Evaluation of the ray-casting analytical algorithm for pencil beam scanning proton therapy.

For pencil beam scanned (PBS) proton therapy, analytical dose calculation engines are still typically used for the optimisation process, and often for the final evaluation of the plan. Recently however, the suitability of analytical calculations for planning PBS treatments has been questioned. Conceptually, the two main approaches for these analytical dose calculations are the ray-casting (RC) and the pencil-beam (PB) method. In this study, we compare dose distributions and dosimetric indices, calculated on both the clinical dose calculation grid and as a function of dose grid resolution, to Monte Carlo (MC) calculations. The analysis is done using a comprehensive set of clinical plans which represent a wide choice of treatment sites. When analysing dose difference histograms for relative treatment plans, pencil beam calculations with double grid resolution perform best, with on average 97.7%/91.9% (RC), 97.9%/92.7% (RC, double grid resolution), 97.6%/91.0% (PB) and 98.6%/94.0% (PB, double grid resolution) of voxels agreeing within ±5%/± 3% between the analytical and the MC calculations. Even though these point-to-point dose comparison shows differences between analytical and MC calculations, for all algorithms, clinically relevant dosimetric indices agree within ±4% for the PTV and within ±5% for critical organs. While the clinical agreement depends on the treatment site, there is no substantial difference of indices between the different algorithms. The pencil-beam approach however comes at a higher computational cost than the ray-casting calculation. In conclusion, we would recommend using the ray-casting algorithm for fast dose optimization and subsequently combine it with one MC calculation to scale the absolute dose and assure the quality of the treatment plan.