Breast tumor movements analysis using MRI scans in prone and supine positions

Evaluation of the accuracy of an augmented reality-based tumor-targeting guide for breast-conserving surgery

BACKGROUND AND OBJECTIVES

Although magnetic resonance imaging (MRI) is commonly used for breast tumor detection, significant challenges remain in determining and presenting the three-dimensional (3D) morphology of tumors to guide breast-conserving surgery. To address this challenge, we have developed the augmented reality-breast surgery guide (AR-BSG) and compared its performance with that of a traditional 3D-printed breast surgical guide (3DP-BSG).

METHODS

Based on the MRI results of a breast cancer patient, a breast phantom made of skin, body, and tumor was fabricated through 3D printing and silicone-casting. AR-BSG and 3DP-BSG were executed using surgical plans based on the breast phantom's computed tomography scan images. Three operators independently inserted a catheter into the phantom using each guide. Their targeting accuracy was then evaluated using Bland-Altman analysis with limits of agreement (LoA). Differences between the users of each guide were evaluated using the intraclass correlation coefficient (ICC).

RESULTS

The entry and end point errors associated with AR-BSG were -0.34±0.68 mm (LoA: -1.71-1.01 mm) and 0.81±1.88 mm (LoA: -4.60-3.00 mm), respectively, whereas 3DP-BSG was associated with entry and end point errors of -0.28±0.70 mm (LoA: -1.69-1.11 mm) and -0.62±1.24 mm (LoA: -3.00-1.80 mm), respectively. The AR-BSG's entry and end point ICC values were 0.99 and 0.97, respectively, whereas 3DP-BSG was associated with entry and end point ICC values of 0.99 and 0.99, respectively.

CONCLUSIONS

AR-BSG can consistently and accurately localize tumor margins for surgeons without inferior guiding accuracy AR-BSG can consistently and accurately localize tumor margins for surgeons without inferior guiding accuracy compared to 3DP-BSG. Additionally, when compared with 3DP-BSG, AR-BSG can offer better spatial perception and visualization, lower costs, and a shorter setup time.

Evaluation of Image Quality of Motion-Corrected Supine Breast MRI

Breast MRI is the most performant modality for breast cancer diagnosis and could be widespread in the future. The gold standard breast MRI is performed in the prone position, but comfort and correlation with surgery or biopsy positioning can be problematic, while supine MRI could be an interesting alternative. In this work, we evaluated the image quality of T2-weighted supine breast MRI in healthy volunteers after online correction of respiratory motion artifacts compared to standard vendor's reconstruction and to standard prone MRI. T2-weighted images were acquired in the prone and free-breathing supine position in 10 volunteers. Two types of reconstructions were evaluated for supine acquisitions: the standard vendor's reconstruction and an online version of a nonrigid motion correction technique (generalized reconstruction by inversion of coupled system). Image quality criteria, including overall quality, sharpness, uniformity, and different types of artifacts, were assessed and scored by 2 radiologists in a randomized fashion. Interobserver agreement was verified by Weighted Cohen's Kappa calculation and a comparison between the different acquisitions was made by Wilcoxon signed-rank test. Generalized Reconstruction by Inversion of Coupled Systems (GRICS) reconstruction method significantly increased image quality in comparison to the standard reconstruction of supine acquisition. It allows a comparable quality, slightly lower than the gold standard prone MRI in T2-weighted images but it needs to be assessed with more patients and with target lesions before it can be used in clinical practice.

Improvement of semantic segmentation through transfer learning of multi-class regions with convolutional neural networks on supine and prone breast MRI images

Semantic segmentation of breast and surrounding tissues in supine and prone breast magnetic resonance imaging (MRI) is required for various kinds of computer-assisted diagnoses for surgical applications. Variability of breast shape in supine and prone poses along with various MRI artifacts makes it difficult to determine robust breast and surrounding tissue segmentation. Therefore, we evaluated semantic segmentation with transfer learning of convolutional neural networks to create robust breast segmentation in supine breast MRI without considering supine or prone positions. Total 29 patients with T1-weighted contrast-enhanced images were collected at Asan Medical Center and two types of breast MRI were performed in the prone position and the supine position. The four classes, including lungs and heart, muscles and bones, parenchyma with cancer, and skin and fat, were manually drawn by an expert. Semantic segmentation on breast MRI scans with supine, prone, transferred from prone to supine, and pooled supine and prone MRI were trained and compared using 2D U-Net, 3D U-Net, 2D nnU-Net and 3D nnU-Net. The best performance was 2D models with transfer learning. Our results showed excellent performance and could be used for clinical purposes such as breast registration and computer-aided diagnosis.

Can Supine Breast Magnetic Resonance Imaging After a Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging Provide Information for Supine Procedures?

METHODS

A retrospective analysis was conducted on 75 lesions in 50 patients with pathologically proven breast cancer who underwent MRI in prone and supine positions between December 2019 and December 2020. The transverse, anteroposterior, and craniocaudal dimensions (in millimeters) of the tumor in the x-, y-, and z-axes were measured. Distances from the center of the tumor to the chest wall and the adjacent skin were measured on transverse and reformatted sagittal images. In cases where multifocal lesions were present, the transverse, anteroposterior, and craniocaudal distances between the tumor centers in the x-, y-, and z-axes were measured. Differences between measurements in supine and prone MRI were evaluated with the Mann-Whitney U and the Wilcoxon tests. P values of less than 0.05 were considered to indicate a statistically significant difference.

RESULTS

The analysis revealed 31 MRIs with 1 and 20 with multifocal lesions. The x-axis dimension of the lesions in prone and supine positions did not significantly differ (P = 0.198) between the 2 positions. A significant difference in the y- and z-axes dimensions was observed between the prone and supine position (P = 0.00 for both). The distance from the tumor to the chest wall and the adjacent skin showed significant difference (P = 0.00 for both). For multifocal lesions, the distance between the lesions showed a significant difference on the y-axis (P = 0.00).

CONCLUSIONS

This study showed a significant difference in the tumor size, location, and tumor-to-tumor distances due to change of patient position, from the standard prone MRI to the supine position in the operating room, resulting in distortion, spatial repositioning, and convergence of the lesions. Supine MRI may be considered in providing a less extensive surgery.

Development of a patient-specific chest computed tomography imaging phantom with realistic lung lesions using silicone casting and three-dimensional printing

The validation of the accuracy of the quantification software in computed tomography (CT) images is very challenging. Therefore, we proposed a CT imaging phantom that accurately represents patient-specific anatomical structures and randomly integrates various lesions including disease-like patterns and lesions of various shapes and sizes using silicone casting and three-dimensional (3D) printing. Six nodules of various shapes and sizes were randomly added to the patient's modeled lungs to evaluate the accuracy of the quantification software. By using silicone materials, CT intensities suitable for the lesions and lung parenchyma were realized, and their Hounsfield unit (HU) values were evaluated on a CT scan of the phantom. As a result, based on the CT scan of the imaging phantom model, the measured HU values for the normal lung parenchyma, each nodule, fibrosis, and emphysematous lesions were within the target value. The measurement error between the stereolithography model and 3D-printing phantoms was 0.2 ± 0.18 mm. In conclusion, the use of 3D printing and silicone casting allowed the application and evaluation of the proposed CT imaging phantom for the validation of the accuracy of the quantification software in CT images, which could be applied to CT-based quantification and development of imaging biomarkers.

The modified shrinkage classification modes could help to guide breast conserving surgery after neoadjuvant therapy in breast cancer

Purpose

The traditional shrinkage classification modes might not suitable for guiding breast conserving surgery (BCS) after neoadjuvant therapy (NAT). Aim was to explore the modified shrinkage classification modes to guide BCS after NAT.

Methods

From April 2010 to 2018, 104 patients were included. All patients underwent MRI examinations before and after NAT. Residual tumors were removed and divided into more than 30 tissue blocks at 5-mm intervals. After performing routine procedures for paraffin-embedded histology, we made semiserial sections (6-μm thick). The MRI and pathology 3D models were reconstructed with 3D-DOCTOR software. Combined with traditional shrinkage modes and efficacy of NAT, we derived modified shrinkage classification modes which oriented by BCS purpose: modified concentric shrinkage modes (MCSM) and modified non concentric shrinkage modes (MNCSM). The MCSM means the longest diameter of residual tumor was less than 50% and ≤2cm in comparison with the primary tumor before NAT. Other shrinkage modes were classified as MNCSM.

Results

According to traditional shrinkage modes, 50 (48.1%) cases were suitable for BCS;while 70 (67.3%) cases were suitable for BCS according to the modified shrinkage modes (p=0.007). The consistency of MRI 3D reconstruction in assessing modified shrinkage classification modes was 93.2%, while it was 61.5% when assessing traditional shrinkage modes. Multivariate analysis showed that primary tumor stage, mammographic malignant calcification, molecular subtypes and nodal down-staging after NAT were independent predictors of modified shrinkage modes (all p<0.05). A nomogram was created based on these four predictors. With a median follow-up time of 77 months, the recurrence/metastasis rate in the MCSM and MNCSM group was 7.1% and 29.4%, respectively.

Conclusion

Modified shrinkage classification modes could help to guide the individualized selection of BCS candidates and scope of resection after NAT. MRI 3D reconstruction after NAT could accurately predict modified shrinkage modes and extent of residual tumor.

Rehearsal simulation to determine the size of device for left atrial appendage occlusion using patient-specific 3D-printed phantoms

Left atrial appendage (LAA) occlusion (LAAO) is used to close the finger-like extension from the left atrium with occlusion devices to block the source of thrombosis. However, selection of the devices size is not easy due to various anatomical changes. The purpose of this study is patient-specific, computed tomography angiography (CTA)-based, three-dimensionally (3D) printed LAAO phantoms were applied pre-procedure to determine the size. Ten patients were enrolled prospectively in March 2019 and December 2020. The cardiac structure appearing in CTA was first segmented, and the left atrium and related structures in the LAAO procedure were modeled. The phantoms were fabricated using two methods of fused deposition modeling (FDM) and stereolithography (SLA) 3D printers with thermoplastic polyurethane (TPU) and flexible resin materials and evaluated by comparing their physical and material properties. The 3D-printed phantoms were directly used to confirm the shape of LAA, and to predict the device size for LAAO. In summary, the shore A hardness of TPU of FDM was about 80–85 shore A, and that of flexible resin of SLA was about 50–70 shore A. The measurement error between the STL model and 3D printing phantoms were 0.45 ± 0.37 mm (Bland–Altman, limits of agreement from − 1.8 to 1.6 mm). At the rehearsal, the estimations of device sizes were the exact same with those in the actual procedures of all 10 patients. In conclusion, simulation with a 3D-printed left atrium phantom could be used to predict the LAAO insertion device size accurately before the procedure.

Accuracy evaluation of a 3D printing surgical guide for breast-conserving surgery using a realistic breast phantom

To prevent recurrence after breast-conserving surgery (BCS), it is imperative to secure a clear resection margin, and magnetic resonance imaging (MRI) is useful for predicting this. Although MRI is highly accurate in predicting the extent of a tumor, it is difficult to quantitatively mark the tumor area directly on the patient's breast skin using MRI. Therefore, we developed a 3D-printed breast surgical guide (3DP-BSG). The 3DP-BGS is positioned on the breast using the guideline pointing to the opposite nipple and clavicle notch, centering on the nipple of the breast with the tumor. Then, the tumor was visualized by injecting blue-dye into the breast along the guide's columns using a syringe. For the quantitative evaluation of 3DP-BSG, the experiment must be done in the simulated environment. However, since it is difficult to construct the environment in the clinical field, we have fabricated a realistic breast phantom using an MRI. For modeling the 3DP-BSG, the phantom was scanned using computed tomography (CT), and. Based on these images, the 3DP-BSG was modeled to mark a 5-mm safety margin on a patient's breast skin by inserting a 16-gauge intravenous catheter. Then, the breast phantom was scanned by CT for quantitative evaluation. The insertion point measurement error (mean ± standard deviation) was 2.513 ± 0.914 mm, and the cosine similarity of the trajectories was 0.997 ± 0.005. This 3DP-BSG exhibits high accuracy in tumor targeting and is expected to facilitate precise BCS by providing a quantitative measure of the tumor area to surgeons.

Breast-conserving surgery with 3D-printed surgical guide: a single-center, prospective clinical study

To facilitate precise tumor resection at the time of breast-conserving surgery (BCS), we developed and implemented a magnetic resonance imaging (MRI)-based three-dimensional-printed (3DP) breast surgical guide (BSG). This prospective cohort study was conducted at a single institution from July 2017 to February 2019 on women with breast cancer who underwent partial breast resection using patient-specific 3DP BSGs. Eighty-eight patients with invasive cancer were enrolled, of whom 1 patient had bilateral breast cancer. The mean size of the tumor long-axis on MRI before surgery was 2.8 ± 0.9 cm, and multiple tumors were observed in 34 patients. In 16 cases (18.0%), the resection margin was tumor-positive according to intraoperative frozen biopsy; all of these tumors were ductal carcinoma in situ and were re-excised intraoperatively. In 93.3% of the cases, the resection margin was tumor-free in the permanent pathology. The mean pathological tumor size was 1.7 ± 1.0 cm, and the mean distance from the tumor to the border was 1.5 ± 1.0 cm. This exploratory study showed that the tumor area on the MRI could be directly displayed on the breast when using a 3DP BSG for BCS, thereby allowing precise surgery and safe tumor removal.

Trial Registration Clinical Research Information Service (CRIS) Identifier (No. KCT0002375, KCT0003043).

Clinical Assessment of Breast Volume: Can 3D Imaging Be the Gold Standard?

Background:

Three-dimensional (3D) camera systems are increasingly used for computerized volume calculations. In this study we investigate whether the Vectra XT 3D imaging system is a reliable tool for determination of breast volume in clinical practice. It is compared with the current gold standard in literature, magnetic resonance imaging (MRI), and current clinical practice (plastic surgeon’s clinical estimation).

Methods:

Breast volumes of 29 patients (53 breasts) were evaluated. 3D images were acquired by Vectra XT 3D imaging system. Pre-existing breast MRI images were collected. Both imaging techniques were used for volume analyses, calculated by two independent investigators. Breast volume estimations were done by plastic surgeons during outpatient consultations. All volume measurements were compared using paired samples t-test, intra-class correlation coefficient, Pearson’s correlation, and Bland–Altman analysis.

Results:

Two 3D breast volume measurements showed an excellent reliability (intra-class correlation coefficient: 0.991), which was comparable to the reliability of MRI measurements (intra-class correlation coefficient: 0.990). Mean (SD) breast volume measured with 3D breast volume was 454 cm³ (157) and with MRI was 687 cm³ (312). These volumes were significantly different, but a linear association could be found: y(MRI) = 1.58 × (3D) – 40. Three-dimensional breast volume was not significantly different from volume estimation made by plastic surgeons (472 cm³ (69), P = 0.323).

Conclusions:

The 3D imaging system measures lower volumes for breasts than MRI. However, 3D measurements show a linear association with MRI and have excellent reliability, making them an objective and reproducible measuring method suitable for clinical practice.