A Randomized Prospective Trial of Supine MRI-Guided Versus Wire-Localized Lumpectomy for Breast Cancer

Comparing regularized Kelvinlet functions and the finite element method for registration of medical images to sparse organ data

Image-guided surgery collocates patient-specific data with the physical environment to facilitate surgical decision making. Unfortunately, these guidance systems commonly become compromised by intraoperative soft-tissue deformations. Nonrigid image-to-physical registration methods have been proposed to compensate for deformations, but clinical utility requires compatibility of these techniques with data sparsity and temporal constraints in the operating room. While finite element models can be effective in sparse data scenarios, computation time remains a limitation to widespread deployment. This paper proposes a registration algorithm that uses regularized Kelvinlets, which are analytical solutions to linear elasticity in an infinite domain, to overcome these barriers. This algorithm is demonstrated and compared to finite element-based registration on two datasets: a phantom liver deformation dataset and an in vivo breast deformation dataset. The regularized Kelvinlets algorithm resulted in a significant reduction in computation time compared to the finite element method. Accuracy as evaluated by target registration error was comparable between methods. Average target registration errors were 4.6 ± 1.0 and 3.2 ± 0.8 mm on the liver dataset and 5.4 ± 1.4 and 6.4 ± 1.5 mm on the breast dataset for the regularized Kelvinlets and finite element method, respectively. Limitations of regularized Kelvinlets include the lack of organ-specific geometry and the assumptions of linear elasticity and infinitesimal strain. Despite limitations, this work demonstrates the generalizability of regularized Kelvinlets registration on two soft-tissue elastic organs. This method may improve and accelerate registration for image-guided surgery, and it shows the potential of using regularized Kelvinlets on medical imaging data.

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.

Breast simulation pipeline: From medical imaging to patient-specific simulations

BACKGROUND

Breast-conserving surgery is the most acceptable operation for breast cancer removal from an invasive and psychological point of view. Before the surgical procedure, a preoperative MRI is performed in the prone configuration, while the surgery is achieved in the supine position. This leads to a considerable movement of the breast, including the tumor, between the two poses, complicating the surgeon's task.

METHODS

In this work, a simulation pipeline allowing the computation of patient-specific geometry and the prediction of personalized breast material properties was put forward. Through image segmentation, a finite element model including the subject-specific geometry is established. By first computing an undeformed state of the breast, the geometrico-material model is calibrated by surface acquisition in the intra-operative stance.

FINDINGS

Using an elastic corotational formulation, the patient-specific mechanical properties of the breast and skin were identified to obtain the best estimates of the supine configuration. The final results are a shape-fitting closest point residual of 4.00 mm for the mechanical parameters Ebreast=0.32 kPa and Eskin=22.72 kPa, congruent with the current state-of-the-art. The Covariance Matrix Adaptation Evolution Strategy optimizer converges on average between 5 to 30 min depending on the initial parameters, reaching a simulation speed of 20 s. To our knowledge, our model offers one of the best compromises between accuracy and speed.

INTERPRETATION

Satisfactory results were obtained for the estimation of breast deformation from preoperative to intra-operative configuration. Furthermore, we have demonstrated the clinical feasibility of such applications using a simulation framework that aims at the smallest disturbance of the actual surgical pipeline.

Evaluating Receptor-Specific Fresh Specimen Staining for Tumor Margin Detection in Clinical Breast Specimens

PURPOSE

Reliable and rapid identification of tumor in the margins of breast specimens during breast-conserving surgery to reduce repeat surgery rates is an active area of investigation. Dual-stain difference imaging (DDSI) is one of many approaches under evaluation for this application. This technique aims to topically apply fluorescent stain pairs (one targeted to a receptor-of-interest and the other a spectrally distinct isotype), image both stains, and compute a normalized difference image between the two channels. Prior evaluation and optimization in a variety of preclinical models produced encouraging diagnostic performance. Herein, we report on a pilot clinical study which evaluated HER2-targeted DDSI on 11 human breast specimens.

PROCEDURES

Gross sections from 11 freshly excised mastectomy specimens were processed using a HER2-receptor-targeted DDSI protocol shortly after resection. After staining with the dual-probe protocol, specimens were imaged on a fluorescence scanner, followed by tissue fixation for hematoxylin and eosin and anti-HER2 immunohistochemical staining. Receiver operator characteristic curves and area under the curve (AUC) analysis were used to assess diagnostic performance of the resulting images. Performance values were also compared to expression level determined from IHC staining.

RESULTS

Eight of the 11 specimens presented with distinguishable invasive ductal carcinoma and/or were not affected by an imaging artifact. In these specimens, the DDSI technique provided an AUC = 0.90 ± 0.07 for tumor-to-adipose tissue and 0.81 ± 0.15 for tumor-to-glandular tissue, which was significantly higher than AUC values recovered from images of the targeted probe alone. DDSI values and diagnostic performance did not correlate with HER2 expression level, and tumors with low HER2 expression often produced high AUC, suggesting that even the low expression levels were enough to help distinguish tumor.

CONCLUSIONS

The results from this preliminary study of rapid receptor-specific staining in human specimens were consistent with prior preclinical results and demonstrated promising diagnostic potential.

Multishot Diffusion-Weighted MRI of the Breasts in the Supine vs. Prone Position

BACKGROUND

Diffusion-weighted imaging (DWI) may allow for breast cancer screening MRI without a contrast injection. Multishot methods improve prone DWI of the breasts but face different challenges in the supine position.

PURPOSE

To establish a multishot DWI (msDWI) protocol for supine breast MRI and to evaluate the performance of supine vs. prone msDWI.

STUDY TYPE

Prospective.

POPULATION

Protocol optimization: 10 healthy women (ages 22-56), supine vs. prone: 24 healthy women (ages 22-62) and five women (ages 29-61) with breast tumors.

FIELD STRENGTH/SEQUENCE

3-T, protocol optimization msDWI: free-breathing (FB) 2-shots, FB 4-shots, respiratory-triggered (RT) 2-shots, RT 4-shots, supine vs. prone: RT 4-shot msDWI, T2-weighted fast-spin echo.

ASSESSMENT

Protocol optimization and supine vs. prone: three observers performed an image quality assessment of sharpness, aliasing, distortion (vs. T2), perceived SNR, and overall image quality (scale of 1-5). Apparent diffusion coefficients (ADCs) in fibroglandular tissue (FGT) and breast tumors were measured.

STATISTICAL TESTS

Effect of study variables on dichotomized ratings (4/5 vs. 1/2/3) and FGT ADCs were assessed with mixed-effects logistic regression. Interobserver agreement utilized Gwet's agreement coefficient (AC). Lesion ADCs were assessed by Bland-Altman analysis and concordance correlation (ρc ). P value <0.05 was considered statistically significant.

RESULTS

Protocol optimization: 4-shots significantly improved sharpness and distortion; RT significantly improved sharpness, aliasing, perceived SNR, and overall image quality. FGT ADCs were not significantly different between shots (P = 0.812), FB vs. RT (P = 0.591), or side (P = 0.574). Supine vs. prone: supine images were rated significantly higher for sharpness, aliasing, and overall image quality. FGT ADCs were significantly higher supine; lesion ADCs were highly correlated (ρc  = 0.92).

DATA CONCLUSION

Based on image quality, supine msDWI outperformed prone msDWI. Lesion ADCs were highly correlated between the two positions, while FGT ADCs were higher in the supine position.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 1.

Incorporating heterogeneity and anisotropy for surgical applications in breast deformation modeling

BACKGROUND

Simulating soft-tissue breast deformations is of interest for many applications including image fusion, longitudinal registration, and image-guided surgery. For the surgical use case, positional changes cause breast deformations that compromise the use of preoperative imaging to inform tumor excision. Even when acquiring imaging in the supine position, which better reflects surgical presentation, deformations still occur due to arm motion and orientation changes. A biomechanical modeling approach to simulate supine breast deformations for surgical applications must be both accurate and compatible with the clinical workflow.

METHODS

A supine MR breast imaging dataset from n = 11 healthy volunteers was used to simulate surgical deformations by acquiring images in arm-down and arm-up positions. Three linear-elastic modeling approaches with varying levels of complexity were used to predict deformations caused by this arm motion: a homogeneous isotropic model, a heterogeneous isotropic model, and a heterogeneous anisotropic model using a transverse-isotropic constitutive model.

FINDINGS

The average target registration errors for subsurface anatomical features were 5.4 ± 1.5 mm for the homogeneous isotropic model, 5.3 ± 1.5 mm for the heterogeneous isotropic model, and 4.7 ± 1.4 mm for the heterogeneous anisotropic model. A statistically significant improvement in target registration error was observed between the heterogeneous anisotropic model and both the homogeneous and the heterogeneous isotropic models (P < 0.01).

INTERPRETATION

While a model that fully incorporates all constitutive complexities of anatomical structure likely achieves the best accuracy, a computationally tractable heterogeneous anisotropic model provided significant improvement and may be applicable for image-guided breast surgeries.

Computational Imaging to Compensate for Soft-Tissue Deformations in Image-Guided Breast Conserving Surgery

OBJECTIVE

During breast conserving surgery (BCS), magnetic resonance (MR) images aligned to accurately display intraoperative lesion locations can offer improved understanding of tumor extent and position relative to breast anatomy. Unfortunately, even under consistent supine conditions, soft tissue deformation compromises image-to-physical alignment and results in positional errors.

METHODS

A finite element inverse modeling technique has been developed to nonrigidly register preoperative supine MR imaging data to the surgical scene for improved localization accuracy during surgery. Registration is driven using sparse data compatible with acquisition during BCS, including corresponding surface fiducials, sparse chest wall contours, and the intra-fiducial skin surface. Deformation predictions were evaluated at surface fiducial locations and subsurface tissue features that were expertly identified and tracked. Among n = 7 different human subjects, an average of 22 ± 3 distributed subsurface targets were analyzed in each breast volume.

RESULTS

The average target registration error (TRE) decreased significantly when comparing rigid registration to this nonrigid approach (10.4 ± 2.3 mm vs 6.3 ± 1.4 mm TRE, respectively). When including a single subsurface feature as additional input data, the TRE significantly improved further (4.2 ± 1.0 mm TRE), and in a region of interest within 15 mm of a mock biopsy clip TRE was 3.9 ± 0.9 mm.

CONCLUSION

These results demonstrate accurate breast deformation estimates based on sparse-data-driven model predictions.

SIGNIFICANCE

The data suggest that a computational imaging approach can account for image-to-surgery shape changes to enhance surgical guidance during BCS.

Optimal localization strategies for non-palpable breast cancers –A network meta-analysis of randomized controlled trials

Purpose

Mammographic screening programmes have increased detection rates of non-palpable breast cancers. In these cases, wire-guided localization (WGL) is the most common approach used to guide breast conserving surgery (BCS). Several RCTs have compared WGL to a range of novel localization techniques. We aimed to perform a network meta-analysis (NMA) of randomized controlled trials (RCTs) comparing methods of non-palpable breast cancer localization.

Methods

A NMA was performed according to PRISMA-NMA guidelines. Analysis was performed using R packages and Shiny.

Results

24 RCTs assessing 9 tumour localization methods in 4236 breasts were included. Margin positivity and reoperation rates were 16.9% (714/4236) and 14.3% (409/2870) respectively. Cryo-assisted localization had the highest margin positivity (28.2%, 58/206) and reoperation (18.9%, 39/206) rates. Compared to WGL (n = 2045 from 24 RCTs) only ultrasound guided localization (USGL) (n = 316 from 3 RCTs) significantly lowered margin positivity (odds ratio (OR): 0.192, 95% confidence interval (CI): 0.079–0.450) and reoperation rates (OR: 0.182, 95%CI: 0.069–0.434). Anchor-guided localization (n = 52, 1 RCT) significantly lowered margin positivity (OR: 0.229, 95%CI: 0.050–0.938) and magnetic-marker localization improved patient satisfaction (OR: 0.021, 95%CI: 0.001–0.548). There was no difference in operation duration, overall complications, haematoma, seroma, surgical site infection rates, or specimen size/vol/wt between methods.

Conclusion

USGL and AGL are non-inferior to WGL for the localization of non-palpable breast cancers. The reported data suggests that these techniques confer reduced margin positivity rates and requirement for re-operation. However, caution when interpreting results relating to RCTs with small sample sizes and further validation is required in larger prospective, randomized studies.

•

Ultrasound-guided (USGL) and anchor-guided (AGL) localization had optimal outcomes.

•

These methods significantly lowered margin positivity (odds ratio: 0.192 & 0.229).

•

However, small sample sizes in trials evaluating USGL and AGL limit these results.

•

Operation duration, complications, or specimen data were comparable for all methods.

Comparative effectiveness of different localization techniques for non-palpable breast cancer. A systematic review and network meta-analysis

BACKGROUND

Several localization techniques are in use for localization of non palpable breast cancer but data on comparative effectiveness of these techniques are sparse. Our aim was to provide the first comparative effectiveness data on the topic.

METHODS

PubMed, Ovid, Scopus and Cochrane library were searched for randomized controlled trials. Pairwise meta-analysis was performed when more than 2 studies reported on the same head-to-head comparison. Network meta-analysis was performed in Stata.

RESULTS

Eighteen studies with 3112 patients were identified. A star shaped network was formed for every outcome as all studies had as common comparator the wire localization technique (WGL). Ultrasound guided surgery (UGS) had decreased positive margin both in the pairwise [OR = 0.19(0.11, 0.35); P < 0.01] and network meta-analysis OR = 0.19 (0.11,0.60). There was also a statistically significant reduction in re-operation rate [OR = 0.19 (0.11, 0.36); P < 0.01] and operative time [MD = -4.24(-7.85,-0.63); P = 0.02] as compared to WGL in pairwise meta-analysis. Re-operation rate and operative time did not hold there statistical significance in network meta-analysis. On network meta-analysis UGS had a statistically significant reduction in positive margin as compared to radio-guided occult lesion localization (ROLL) OR = 0.19 (0.11,0.6) and radioactive seed localization (RSL) OR = 0.26(0.13, 0.52). UGS had a 54.6% of being the best technique for positive margin. All techniques were equivalent for successful excision, localization complications, operative time and overall complications.

CONCLUSIONS

UGS has potential benefits in reduction of positive surgical margin, the rest of the techniques seem to have equivalent efficacy. Further randomized trials are required to verify these results.

A method for validating depth-resolved biodistributions in topically-stained specimen with multi-channel fluorescence cryo-imaging

Fluorescent contrast agents targeted to cancer biomarkers are increasingly being explored for cancer detection, surgical guidance, and response monitoring. Efforts have been underway to topically apply such biomarker-targeted agents to freshly excised specimen for detecting cancer cell receptors on the surface as a method for intraoperative surgical margin assessment, including dual-probe staining methods introduce a second 'non-specific' optical agent as a control to help compensate for heterogeneous uptake and normalize the imaging field. Still, such specimen staining protocols introduce multifaceted complexity with unknown variables, such as tissue-specific diffusion, cell-specific binding and disassociation rates, and other factors, affecting the interpreted cancer-biomarker distribution across the specimen surface. The ability to recover three-dimensional dual-probe biodistributions throughout whole-specimens could offer a ground-truth validation method for examining topical staining uptake behaviors. Herein, we report on a novel method for characterizing dual-probe accumulation with 3D depth-profiles observed from a dual-probe fresh-specimen staining experiment.

Impact of deformation on a supine-positioned image-guided breast surgery approach

PURPOSE

To reduce reoperation rates for image-guided breast-conserving surgery, the enhanced sensitivity of magnetic resonance (MR) supine imaging may be leveraged. However, accurate tissue correspondence between images and their physical counterpart in the surgical presentation is challenging due to breast deformations (e.g., from patient/arm position changes, and operating room table rotation differences). In this study, standard rigid registration methods are employed and tissue deformation is characterized.

METHODS

On n = 10 healthy breasts, surface displacements were measured by comparing intraoperative fiducial locations as the arm was moved from conventional MR scanning positions (arm-down and arm-up) to the laterally extended surgical configuration. Supine MR images in the arm-down and arm-up positions were registered to mock intraoperative presentations.

RESULTS

Breast displacements from a supine MR imaging configuration to a mock surgical presentation were 28.9 ± 9.2 mm with shifts occurring primarily in the inferior/superior direction. With respect to supine MR to surgical alignment, the average fiducial, target, and maximum target registration errors were 9.0 ± 1.7 mm, 9.3 ± 1.7 mm, and 20.0 ± 7.6 mm, respectively. Even when maintaining similar arm positions in the MR image and mock surgery, the respective averages were 6.0 ± 1.0 mm, 6.5 ± 1.1 mm, and 12.5 ± 2.8 mm.

CONCLUSION

From supine MR positioning to surgical presentation, the breast undergoes large displacements (9.9-70.1 mm). The data also suggest that significant nonrigid deformations (9.3 ± 1.7 mm with 20.0 mm average maximum) exist that need to be considered in image guidance and modeling applications.

The shape of breast cancer

PURPOSE

Little is known about the three-dimensional shape of breast cancer. Implicit to approaches that localize the center of the tumor for breast-conserving surgery (BCS) of non-palpable cancers is the assumption that breast cancers are spherical about a central point, which may not be accurate.

METHODS

Pre-operative supine breast MRI images were obtained of 83 breast cancer patients undergoing partial mastectomy using supine MRI-guided resection techniques. Three-dimensional (3D) tumor models were derived after radiologists outlined tumor edges on successive MRI slices. Ideal resection volumes were determined by adding 1 cm in every dimension to the actual tumor volume. Geometrically defined parameters were used to define tumor shapes and associations between clinical variables and shapes were examined.

RESULTS

Seventy-five patients had invasive cancer. Breast cancers were categorized into four tumor shapes: 34% of tumors were discoidal, 29% segmental, 19% spherical, and 18% irregular. If hypothetical spherical excisions were performed, non-spherical cases would excise 143% more tissue than the ideal resection volume. When the 3D shape of each tumor was provided to the surgeon during MR-guided BCS, the percentage of tissue overexcised in non-spherical cases was significantly less (143% vs. 66%, p < 0.001).

CONCLUSIONS

Information obtained from a supine MRI can be used to generate 3D tumor models and rapidly classify breast tumor shapes. The vast majority of invasive cancers and DCIS are not spherical. Knowledge of tumor shape may allow surgeons to excise breast cancer more precisely.