Optical Coherence Tomography: A Novel Imaging Method for Post-lumpectomy Breast Margin Assessment-A Multi-reader Study

Toward real-time margin assessment in breast-conserving surgery with hyperspectral imaging

Margin assessment in breast-conserving surgery (BSC) remains a critical challenge, with 20-25% of cases resulting in inadequate tumor resection, increasing the risk of local recurrence and the need for additional treatment. In this study, we evaluate the diagnostic performance of hyperspectral imaging (HSI) as a non-invasive technique for assessing resection margins in ex vivo lumpectomy specimens. A dataset of over 200 lumpectomy specimens was collected using two hyperspectral cameras, and a classification algorithm was developed to distinguish between healthy and tumor tissue within margins of 0 and 2 mm. The proposed approach achieved its highest diagnostic performance at a 0 mm margin, with a sensitivity of 92%, specificity of 78%, accuracy of 83%, Matthews correlation coefficient of 68%, and an area under the curve of 89%. The entire resection surface could be imaged and evaluated within 10 minutes, providing a rapid and non-invasive alternative to conventional margin assessment techniques. These findings represent a significant advancement toward real-time intraoperative margin assessment, highlighting the potential of HSI to enhance surgical precision and reduce re-excision rates in BCS.

Clinical evaluation of breast cancer tissue with optical coherence tomography: key findings from a large-scale study

PURPOSE

Breast cancer patients undergoing breast-conserving surgery may require a second operation if positive margins persist but current intraoperative methodologies often lack real-time and comprehensive assessments of tissue margins. This study addresses this critical gap by introducing a novel approach to enhance margin assessment in breast surgery.

METHODS

A total of 252 fresh tissue blocks from 199 patients with different types of breast lesions were scanned with a customized swept-source optical coherence tomography (SS-OCT) system, and the OCT features of normal, benign, and malignant breast tissues, were systematically analyzed.

RESULTS

The qualitative analysis results revealed that adipose tissue has high penetration depth and a typical honeycomb pattern, whereas fibrous tissue has the brightest grayscale values and a bundle-like structure. The lobular area appears as a dark region, and dilated ducts present a distinct tubular structure on B-scan images. Adenosis results in bright areas, fibroadenoma results in typical contour structures, phyllodes tumors present lobular structures, invasive carcinomas present a stellate pattern and low penetration depth, and mucinous carcinoma cancer cells are clearly visible within the low-scattering mucin.

CONCLUSIONS

Importantly, we provide comparative OCT and hematoxylin and eosin (H&E) histology images for less common conditions, such as phyllodes tumors, intraductal papillomas, and mucinous carcinoma. For the first time, we established an 3D OCT-histopathology library with a large field of view and systematically analyzed the multidimensional features. This work strongly supports the feasibility of using OCT technology intraoperatively in surgery. Additionally, the OCT-histopathology library can help pathologists better understand and identify tissue features, thereby enhancing diagnostic efficiency.

Intraoperative evaluation of surgical margins in breast cancer

Achieving clear resection margins at the time of lumpectomy is essential for optimal patient outcomes. Margin status is traditionally determined by pathologic evaluation of the specimen and often is difficult or impossible for the surgeon to definitively know at the time of surgery, resulting in the need for re-operation to obtain clear surgical margins. Numerous techniques have been investigated to enhance the accuracy of intraoperative margin and are reviewed in this manuscript.

Hyperspectral dark-field microscopy of human breast lumpectomy samples for tumor margin detection in breast-conserving surgery

Significance

Hyperspectral dark-field microscopy (HSDFM) and data cube analysis algorithms demonstrate successful detection and classification of various tissue types, including carcinoma regions in human post-lumpectomy breast tissues excised during breast-conserving surgeries.

Aim

We expand the application of HSDFM to the classification of tissue types and tumor subtypes in pre-histopathology human breast lumpectomy samples.

Approach

Breast tissues excised during breast-conserving surgeries were imaged by the HSDFM and analyzed. The performance of the HSDFM is evaluated by comparing the backscattering intensity spectra of polystyrene microbead solutions with the Monte Carlo simulation of the experimental data. For classification algorithms, two analysis approaches, a supervised technique based on the spectral angle mapper (SAM) algorithm and an unsupervised technique based on the K -means algorithm are applied to classify various tissue types including carcinoma subtypes. In the supervised technique, the SAM algorithm with manually extracted endmembers guided by H&E annotations is used as reference spectra, allowing for segmentation maps with classified tissue types including carcinoma subtypes.

Results

The manually extracted endmembers of known tissue types and their corresponding threshold spectral correlation angles for classification make a good reference library that validates endmembers computed by the unsupervised K -means algorithm. The unsupervised K -means algorithm, with no a priori information, produces abundance maps with dominant endmembers of various tissue types, including carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma. The two carcinomas' unique endmembers produced by the two methods agree with each other within < 2 % residual error margin.

Conclusions

Our report demonstrates a robust procedure for the validation of an unsupervised algorithm with the essential set of parameters based on the ground truth, histopathological information. We have demonstrated that a trained library of the histopathology-guided endmembers and associated threshold spectral correlation angles computed against well-defined reference data cubes serve such parameters. Two classification algorithms, supervised and unsupervised algorithms, are employed to identify regions with carcinoma subtypes of invasive ductal carcinoma and invasive mucinous carcinoma present in the tissues. The two carcinomas' unique endmembers used by the two methods agree to < 2 % residual error margin. This library of high quality and collected under an environment with no ambient background may be instrumental to develop or validate more advanced unsupervised data cube analysis algorithms, such as effective neural networks for efficient subtype classification.

Comparing the diagnostic efficacy of optical coherence tomography and frozen section for margin assessment in breast-conserving surgery: a meta-analysis

AIMS

This meta-analysis assessed the relative diagnostic accuracy of optical coherence tomography (OCT) versus frozen section (FS) in evaluating surgical margins during breast-conserving procedures.

METHODS

PubMed and Embase were searched for relevant studies published up to October 2023. The inclusion criteria encompassed studies evaluating the diagnostic accuracy of OCT or FS in patients undergoing breast-conserving surgery. Sensitivity and specificity were analysed using the DerSimonian and Laird method and subsequently transformed through the Freeman-Tukey double inverse sine method.

RESULTS

The meta-analysis encompassed 36 articles, comprising 16 studies on OCT and 20 on FS, involving 10 289 specimens from 8058 patients. The overall sensitivity of OCT was 0.93 (95% CI: 0.90 to 0.96), surpassing that of FS, which was 0.82 (95% CI: 0.71 to 0.92), indicating a significantly higher sensitivity for OCT (p=0.04). Conversely, the overall specificity of OCT was 0.89 (95% CI: 0.83 to 0.94), while FS exhibited a higher specificity at 0.97 (95% CI: 0.95 to 0.99), suggesting a superior specificity for FS (p＜0.01).

CONCLUSIONS

Our meta-analysis reveals that OCT offers superior sensitivity but inferior specificity compared with FS in assessing surgical margins in breast-conserving surgery patients. Further larger well-designed prospective studies are needed, especially those employing a head-to-head comparison design.

PROSPERO REGISTRATION NUMBER

CRD42023483751.

Optical Emission Spectroscopy for the Real-Time Identification of Malignant Breast Tissue

Breast conserving resection with free margins is the gold standard treatment for early breast cancer recommended by guidelines worldwide. Therefore, reliable discrimination between normal and malignant tissue at the resection margins is essential. In this study, normal and abnormal tissue samples from breast cancer patients were characterized ex vivo by optical emission spectroscopy (OES) based on ionized atoms and molecules generated during electrosurgical treatment. The aim of the study was to determine spectroscopic features which are typical for healthy and neoplastic breast tissue allowing for future real-time tissue differentiation and margin assessment during breast cancer surgery. A total of 972 spectra generated by electrosurgical sparking on normal and abnormal tissue were used for support vector classifier (SVC) training. Specific spectroscopic features were selected for the classification of tissues in the included breast cancer patients. The average classification accuracy for all patients was 96.9%. Normal and abnormal breast tissue could be differentiated with a mean sensitivity of 94.8%, a specificity of 99.0%, a positive predictive value (PPV) of 99.1% and a negative predictive value (NPV) of 96.1%. For 66.6% patients all classifications reached 100%. Based on this convincing data, a future clinical application of OES-based tissue differentiation in breast cancer surgery seems to be feasible.

The Fusion of Wide Field Optical Coherence Tomography and AI: Advancing Breast Cancer Surgical Margin Visualization

This study explores the integration of Wide Field Optical Coherence Tomography (WF-OCT) with an AI-driven clinical decision support system, with the goal of enhancing productivity and decision making in breast cancer surgery margin assessment. A computationally efficient convolutional neural network (CNN)-based binary classifier is developed using 585 WF-OCT margin scans from 151 subjects. The CNN model swiftly identifies suspicious areas within margins with an on-device inference time of approximately 10 ms for a 420 × 2400 image. In independent testing on 155 pathology-confirmed margins, including 31 positive margins from 29 patients, the classifier achieved an AUROC of 0.976, a sensitivity of 0.93, and a specificity of 0.98. At the margin level, the deep learning model accurately identified 96.8% of pathology-positive margins. These results highlight the clinical viability of AI-enhanced margin visualization using WF-OCT in breast cancer surgery and its potential to decrease reoperation rates due to residual tumors.

Diagnostic accuracy of optical coherence tomography for margin assessment in breast-conserving surgery: A systematic review and meta-analysis

BACKGROUND

Breast cancer is the most common malignant tumor among women, and its incidence is increasing annually. At present, the results of the study on whether optical coherence tomography (OCT) can be used as an intraoperative margin assessment method for breast-conserving surgery (BCS) are inconsistent. We herein conducted this systematic review and meta-analysis to assess the diagnostic value of OCT in BCS.

METHODS

PubMed, Web of Science, Cochrane Library, and Embase were used to search relevant studies published up to September 15, 2022. We used Review Manager 5.4, Meta-Disc 1.4, and STATA 16.0 for statistical analysis.

RESULTS

The results displayed 18 studies with 782 patients included according to the inclusion and exclusion criteria. Meta-analysis showed the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and the area under the curve (AUC) of OCT in the margin assessment of BCS were 0.91 (95% CI 0.88-0.93), 0.88 (95% CI 0.83-0.92), 7.53 (95% CI 5.19-10.93), 0.11(95% CI 0.08-0.14), 70.37 (95% CI 39.78-124.47), and 0.94 (95% CI 0.92-0.96), respectively.

CONCLUSIONS

OCT is a promising technique in intraoperative margin assessment of breast cancer patients.

Diffuse reflectance spectroscopy for accurate margin assessment in breast-conserving surgeries: importance of an optimal number of fibers

During breast-conserving surgeries, it remains challenging to accomplish adequate surgical margins. We investigated different numbers of fibers for fiber-optic diffuse reflectance spectroscopy to differentiate tumorous breast tissue from healthy tissue ex vivo up to 2 mm from the margin. Using a machine-learning classification model, the optimal performance was obtained using at least three emitting fibers (Matthew's correlation coefficient (MCC) of 0.73), which was significantly higher compared to the performance of using a single-emitting fiber (MCC of 0.48). The percentage of correctly classified tumor locations varied from 75% to 100% depending on the tumor percentage, the tumor-margin distance and the number of fibers.

Wide-field optical coherence tomography for microstructural analysis of key tissue types: a proof-of-concept evaluation

Introduction: The presence of positive margins following tumor resection is a frequent cause of re-excision surgery. Nondestructive, real-time intraoperative histopathological imaging methods may improve margin status assessment at the time of surgery; optical coherence tomography (OCT) has been identified as a potential solution but has not been tested with the most common tissue types in surgical oncology using a single, standardized platform. Methods: This was a proof-of-concept evaluation of a novel device that employs wide-field OCT (WF-OCT; OTIS 2.0 System) to image tissue specimens. Various cadaveric tissues were obtained from a single autopsy and were imaged with WF-OCT then processed for permanent histology. The quality and resolution of the WF-OCT images were evaluated and compared to histology and with images in previous literature. Results: A total of 30 specimens were collected and tissue-specific microarchitecture consistent with previous literature were identified on both WF-OCT images and histology slides for all specimens, and corresponding sections were correlated. Application of vacuum pressure during scanning did not affect specimen integrity. On average, specimens were scanned at a speed of 10.3 s/cm² with approximately three features observed per tissue type. Conclusion: The WF-OCT images captured in this study displayed the key features of the most common human tissue types encountered in surgical oncology with utility comparable to histology, confirming the utility of an FDA-cleared imaging platform. With further study, WF-OCT may have the potential to bridge the gap between the immediate information needs of the operating room and the longer timeline inherent to histology workflow.

Intraoperative Assessment of Breast Cancer Tissues after Breast-Conserving Surgery Based on Mapping the Attenuation Coefficients in 3D Cross-Polarization Optical Coherence Tomography

Intraoperative differentiation of tumorous from non-tumorous tissue can help in the assessment of resection margins in breast cancer and its response to therapy and, potentially, reduce the incidence of tumor recurrence. In this study, the calculation of the attenuation coefficient and its color-coded 2D distribution was performed for different breast cancer subtypes using spectral-domain CP OCT. A total of 68 freshly excised human breast specimens containing tumorous and surrounding non-tumorous tissues after BCS was studied. Immediately after obtaining structural 3D CP OCT images, en face color-coded attenuation coefficient maps were built in co-(Att(co)) and cross-(Att(cross)) polarization channels using a depth-resolved approach to calculating the values in each A-scan. We determined spatially localized signal attenuation in both channels and reported ranges of attenuation coefficients to five selected breast tissue regions (adipose tissue, non-tumorous fibrous connective tissue, hyalinized tumor stroma, low-density tumor cells in the fibrotic tumor stroma and high-density clusters of tumor cells). The Att(cross) coefficient exhibited a stronger gain contrast of studied tissues compared to the Att(co) coefficient (i.e., conventional attenuation coefficient) and, therefore, allowed improved differentiation of all breast tissue types. It has been shown that color-coded attenuation coefficient maps may be used to detect inter- and intra-tumor heterogeneity of various breast cancer subtypes as well as to assess the effectiveness of therapy. For the first time, the optimal threshold values of the attenuation coefficients to differentiate tumorous from non-tumorous breast tissues were determined. Diagnostic testing values for Att(cross) coefficient were higher for differentiation of tumor cell areas and tumor stroma from non-tumorous fibrous connective tissue: diagnostic accuracy was 91-99%, sensitivity-96-98%, and specificity-87-99%. Att(co) coefficient is more suitable for the differentiation of tumor cell areas from adipose tissue: diagnostic accuracy was 83%, sensitivity-84%, and specificity-84%. Therefore, the present study provides a new diagnostic approach to the differentiation of breast cancer tissue types based on the assessment of the attenuation coefficient from real-time CP OCT data and has the potential to be used for further rapid and accurate intraoperative assessment of the resection margins during BCS.

Toward Intraoperative Margin Assessment Using a Deep Learning-Based Approach for Automatic Tumor Segmentation in Breast Lumpectomy Ultrasound Images

There is an unmet clinical need for an accurate, rapid and reliable tool for margin assessment during breast-conserving surgeries. Ultrasound offers the potential for a rapid, reproducible, and non-invasive method to assess margins. However, it is challenged by certain drawbacks, including a low signal-to-noise ratio, artifacts, and the need for experience with the acquirement and interpretation of images. A possible solution might be computer-aided ultrasound evaluation. In this study, we have developed new ensemble approaches for automated breast tumor segmentation. The ensemble approaches to predict positive and close margins (distance from tumor to margin ≤ 2.0 mm) in the ultrasound images were based on 8 pre-trained deep neural networks. The best optimum ensemble approach for segmentation attained a median Dice score of 0.88 on our data set. Furthermore, utilizing the segmentation results we were able to achieve a sensitivity of 96% and a specificity of 76% for predicting a close margin when compared to histology results. The promising results demonstrate the capability of AI-based ultrasound imaging as an intraoperative surgical margin assessment tool during breast-conserving surgery.

New Technology for the Breast Surgeon

New innovations aid the breast surgeon with better ability to localize tumors using wireless techniques, reduce re-excision rates by intraoperative margin evaluation and perform aesthetically; pleasing, and safe surgeries. In addition to improving oncological outcomes, we can continue to improve the quality of life for our patients through evolving surgeries including nerve-sparing mastectomies, robotic mastectomies, and lymphovascular surgeries (LYMPHA). Our article reviews current and evolving techniques and technology that all breast surgeons should add to his or her armamentarium to provide optimal surgical care.

Intraoperative Use of Wide-Field Optical Coherence Tomography to Evaluate Tissue Microstructure in the Oral Cavity and Oropharynx

Importance

Involvement of deep margins represents a significant challenge in the treatment of oropharyngeal cancer, and given practical limitations of frozen-section analysis, a need exists for real-time, nondestructive intraoperative margin analysis. Wide-field optical coherence tomography (WF-OCT) has been evaluated as a tool for high-resolution adjunct specimen imaging in breast surgery, but its clinical application in head and neck surgery has not been explored.

Objective

To evaluate the utility of WF-OCT for visualizing microstructures at margins of excised oral and oropharyngeal tissue.

Design, Setting, and Participants

This nonrandomized, investigator-initiated qualitative study evaluated the feasibility of the Perimeter Medical Imaging AI Otis WF-OCT device at a single academic center. Included participants were adults undergoing primary ablative surgery of the oral cavity or oropharynx for squamous cell carcinoma in 2018 and 2019. Data were analyzed in October 2019.

Exposures

Patients were treated according to standard surgical care. Freshly resected specimens were imaged with high-resolution WF-OCT prior to routine pathology. Interdisciplinary interpretation was performed to interpret WF-OCT images and compare them with corresponding digitized pathology slides. No clinical decisions were made based on WF-OCT image data.

Main Outcomes and Measures

Visual comparisons were performed between WF-OCT images and hematoxylin and eosin slides.

Results

A total of 69 specimens were collected and scanned from 53 patients (mean [SD] age, 59.4 [15.2] years; 35 [72.9%] men among 48 patients with demographic data) undergoing oral cavity or oropharynx surgery for squamous cell carcinoma, including 42 tonsillar tissue, 17 base of the tongue, 4 buccal tissue, 3 mandibular, and 3 other specimens. There were 41 malignant specimens (59.4%) and 28 benign specimens (40.6%). In visual comparisons of WF-OCT images and hematoxylin and eosin slides, visual differentiation among mucosa, submucosa, muscle, dysplastic, and benign tissue was possible in real time using WF-OCT images. Microarchitectural features observed in WF-OCT images could be matched with corresponding features within the permanent histology with fidelity.

Conclusions and Relevance

This qualitative study found that WF-OCT imaging was feasible for visualizing tissue microarchitecture at the surface of resected tissues and was not associated with changes in specimen integrity or surgical and pathology workflow. These findings suggest that formal clinical studies investigating use of WF-OCT for intraoperative analysis of deep margins in head and neck surgery may be warranted.

Virtual histological staining of label-free total absorption photoacoustic remote sensing (TA-PARS)

Histopathological visualizations are a pillar of modern medicine and biological research. Surgical oncology relies exclusively on post-operative histology to determine definitive surgical success and guide adjuvant treatments. The current histology workflow is based on bright-field microscopic assessment of histochemical stained tissues and has some major limitations. For example, the preparation of stained specimens for brightfield assessment requires lengthy sample processing, delaying interventions for days or even weeks. Therefore, there is a pressing need for improved histopathology methods. In this paper, we present a deep-learning-based approach for virtual label-free histochemical staining of total-absorption photoacoustic remote sensing (TA-PARS) images of unstained tissue. TA-PARS provides an array of directly measured label-free contrasts such as scattering and total absorption (radiative and non-radiative), ideal for developing H&E colorizations without the need to infer arbitrary tissue structures. We use a Pix2Pix generative adversarial network to develop visualizations analogous to H&E staining from label-free TA-PARS images. Thin sections of human skin tissue were first virtually stained with the TA-PARS, then were chemically stained with H&E producing a one-to-one comparison between the virtual and chemical staining. The one-to-one matched virtually- and chemically- stained images exhibit high concordance validating the digital colorization of the TA-PARS images against the gold standard H&E. TA-PARS images were reviewed by four dermatologic pathologists who confirmed they are of diagnostic quality, and that resolution, contrast, and color permitted interpretation as if they were H&E. The presented approach paves the way for the development of TA-PARS slide-free histological imaging, which promises to dramatically reduce the time from specimen resection to histological imaging.

Intraoperative Margin Trials in Breast Cancer

Purpose of Review

Obtaining negative margins in breast conservation surgery continues to be a challenge. Re-excisions are difficult for patients and expensive for the health systems. This paper reviews the literature on current strategies and intraoperative clinical trials to reduce positive margin rates.

Recent Findings

The best available data demonstrate that intraoperative imaging with ultrasound, intraoperative pathologic assessment such as frozen section, and cavity margins have been the most successful intraoperative strategies to reduce positive margins. Emerging technologies such as optical coherence tomography and fluorescent imaging need further study but may be important adjuncts.

Summary

There are several proven strategies to reduce positive margin rates to < 10%. Surgeons should utilize best available resources within their institutions to produce the best outcomes for their patients.

Classifying breast cancer in ultrahigh-resolution optical coherence tomography images using convolutional neural networks

Optical coherence tomography (OCT) is being investigated in breast cancer diagnostics as a real-time histology evaluation tool. We present a customized deep convolutional neural network (CNN) for classification of breast tissues in OCT B-scans. Images of human breast samples from mastectomies and breast reductions were acquired using a custom ultrahigh-resolution OCT system with 2.72 µm axial resolution and 5.52 µm lateral resolution. The network achieved 96.7% accuracy, 92% sensitivity, and 99.7% specificity on a dataset of 23 patients. The usage of deep learning will be important for the practical integration of OCT into clinical practice.

Magnetic resonance imaging system for intraoperative margin assessment for DCIS and invasive breast cancer using the ClearSight™ system in breast-conserving surgery-Results from a postmarketing study

BACKGROUND AND OBJECTIVES

Breast-conserving surgery (BCS) is followed by reoperations in approximately 25%. Reoperations lead to an increased risk of infection and wound healing problems as well as a worse cosmetic outcome. Several technical approaches for an intraoperative margin assessment to decrease the reoperation rate are under evaluation, some of them are still experimental.

METHODS

A prospective single-arm post-marketing study with 60 patients undergoing BCS for ductal carcinoma in situ (DCIS) and invasive breast cancer was conducted. The specimen was intraoperatively examined by the ClearSight™ system, a mobile magnetic resonance imaging system that is based on a diffusion-weighted imaging protocol. However, the results were blinded to the surgeon.

RESULTS

The ClearSight™ system was performed for both ductal and lobular breast cancer and DCIS, with a sensitivity of 0.80 (95% confidence interval [CI]: 0.44-0.96) and a specificity of 0.84 (95% CI 0.72-0.92), with an overall diagnostic accuracy of 80%.

CONCLUSION

Had the ClearSight™ been known to the surgeon intraoperatively, the reoperation rate would have been reduced by 83% for invasive carcinoma, from 10% to 2%, and 50% for DCIS, from 30% to 15% reoperations. A trial designed to examine the impact on reoperation rates is currently ongoing.

Assessment of photoacoustic tomography contrast for breast tissue imaging using 3D correlative virtual histology

Current breast tumor margin detection methods are destructive, time-consuming, and result in significant reoperative rates. Dual-modality photoacoustic tomography (PAT) and ultrasound has the potential to enhance breast margin characterization by providing clinically relevant compositional information with high sensitivity and tissue penetration. However, quantitative methods that rigorously compare volumetric PAT and ultrasound images with gold-standard histology are lacking, thus limiting clinical validation and translation. Here, we present a quantitative multimodality workflow that uses inverted Selective Plane Illumination Microscopy (iSPIM) to facilitate image co-registration between volumetric PAT-ultrasound datasets with histology in human invasive ductal carcinoma breast tissue samples. Our ultrasound-PAT system consisted of a tunable Nd:YAG laser coupled with a 40 MHz central frequency ultrasound transducer. A linear stepper motor was used to acquire volumetric PAT and ultrasound breast biopsy datasets using 1100 nm light to identify hemoglobin-rich regions and 1210 nm light to identify lipid-rich regions. Our iSPIM system used 488 nm and 647 nm laser excitation combined with Eosin and DRAQ5, a cell-permeant nucleic acid binding dye, to produce high-resolution volumetric datasets comparable to histology. Image thresholding was applied to PAT and iSPIM images to extract, quantify, and topologically visualize breast biopsy lipid, stroma, hemoglobin, and nuclei distribution. Our lipid-weighted PAT and iSPIM images suggest that low lipid regions strongly correlate with malignant breast tissue. Hemoglobin-weighted PAT images, however, correlated poorly with cancerous regions determined by histology and interpreted by a board-certified pathologist. Nuclei-weighted iSPIM images revealed similar cellular content in cancerous and non-cancerous tissues, suggesting malignant cell migration from the breast ducts to the surrounding tissues. We demonstrate the utility of our nondestructive, volumetric, region-based quantitative method for comprehensive validation of 3D tomographic imaging methods suitable for bedside tumor margin detection.

Development of intraoperative assessment of margins in breast conserving surgery: a narrative review

OBJECTIVE

We intend to provide an informative and up-to-date summary on the topic of intraoperative assessment of margins in breast conserving surgery (BCS). Conventional methods as well as cutting-edge technologies are analyzed for their advantages and limitations in the hope that clinicians can turn to this for reference. This review can also offer guidance for technicians in the future design of intraoperative margin assessment tools.

BACKGROUND

Achieving negative margins during BCS is one of the vital factors for preventing local recurrence. Conducting intraoperative margin assessment can ensure negative margins to a large extent and possibly relieve patients of the anguish of re-interventions. In recent years, innovative methods for margin assessment during BCS are advancing rapidly. And there is a lack of summary regarding the development of intraoperative margin assessment in BCS.

METHODS

A PubMed search with keywords "intraoperative margin assessment" and "breast conserving surgery" was conducted. Relevant publications were screened manually for its title, abstract and even full text to determine its true relevance. Publications on neo-adjuvant therapy and intraoperative radiotherapy were excluded. References from the searched articles and other supplementary articles were also looked into.

CONCLUSIONS

Conventional methods for margin assessment yields stable outcome but its use is limited because of the demand on pathology staff and the trade-off between time and precision. Conventional imaging techniques pass the workload to radiologists at the cost of a significantly low duration of time. Involving artificial intelligence for image-based assessment is a further improvement. However, conventional imaging is inherently flawed in that occult lesions can't show on the image and the showing ones are ambiguous and open to interpretation. Unconventional techniques which base their judgment on cellular composition are more reassuring. Nonetheless, unconventional techniques should be subjected to clinical trials before putting into practice. And studies regarding comparison between conventional methods and unconventional methods are also needed to evaluate their relative efficacy.

Potential Utility of Adjunct Imaging with Wide-Field Optical Coherence Tomography for Gross and Microscopic Evaluation of Breast Specimens in Real-Time in the Operating Suite

One challenge in the surgical management of breast cancer is maximizing the preservation of healthy tissue while achieving acceptable negative margins. Tools capable of assessing disease-margin involvement intraoperatively and in real-time could provide clinically useful guidance regarding the adequacy of margin resection before the surgery is over. Here we report the intraoperative use of optical coherence tomography (OCT) in 3 patients with DCIS. In all 3 cases, additional lesions identified by OCT during surgery were also noted in histopathology reports 3 to 5 days post-surgery, suggesting that intraoperative use of OCT is a valuable  tool for margin determination in real-time.

Diagnostic accuracy of optical coherence tomography for surgical margin assessment of feline injection-site sarcoma

The invasive, locally aggressive nature of feline injection-site sarcomas (FISSs) poses a unique challenge for surgeons to obtain complete margins with surgical excision. Optical coherence tomography (OCT), an imaging technology that uses light waves to generate real-time views of tissue architecture, provides an emerging solution to this dilemma by allowing fast, high-resolution scanning of surgical margins. The purpose of this study was to use OCT to assess surgical margins of FISS and to evaluate the diagnostic accuracy of OCT for detecting residual cancer using six evaluators of varying experience. Five FISSs were imaged with OCT to create a training set of OCT images that were compared with histopathology. Next, 25 FISSs were imaged with OCT prior to histopathology. Six evaluators of varying experience participated in a training session on OCT imaging after which each of the evaluators was given a dataset that included OCT images and videos to score on a scale from cancerous to non-cancerous. Diagnostic accuracy statistics were calculated. The overall sensitivity and specificity for classification of OCT images by evaluators were 78.9% and 77.6%, respectively. Correct classification rate of OCT images was associated with experience, while individual sensitivities and specificities had more variation between experience groups. This study demonstrates the ability of evaluators to correctly classify OCT images with overall low levels of experience and training and also illustrates areas where increased training can improve accuracy of evaluators in interpretation of OCT surgical margin images.

Three-dimensional virtual histology in unprocessed resected tissues with photoacoustic remote sensing (PARS) microscopy and optical coherence tomography (OCT)

Histological images are critical in the diagnosis and treatment of cancers. Unfortunately, current methods for capturing these microscopy images require resource intensive tissue preparation that may delay diagnosis for days or weeks. To streamline this process, clinicians are limited to assessing small macroscopically representative subsets of tissues. Here, a combined photoacoustic remote sensing (PARS) microscope and swept source optical coherence tomography system designed to circumvent these diagnostic limitations is presented. The proposed multimodal microscope provides label-free three-dimensional depth resolved virtual histology visualizations, capturing nuclear and extranuclear tissue morphology directly on thick unprocessed specimens. The capabilities of the proposed method are demonstrated directly in unprocessed formalin fixed resected tissues. The first images of nuclear contrast in resected human tissues, and the first three-dimensional visualization of subsurface nuclear morphology in resected Rattus tissues, captured with a non-contact photoacoustic system are presented here. Moreover, the proposed system captures the first co-registered OCT and PARS images enabling direct histological assessment of unprocessed tissues. This work represents a vital step towards the development of a rapid histological imaging modality to circumvent the limitations of current histopathology techniques.

Novel imaging techniques for intraoperative margin assessment in surgical oncology: A systematic review

Inadequate margins continue to occur frequently in patients who undergo surgical resection of a tumor, suggesting that current intraoperative methods are not sufficiently reliable in determining the margin status. This clinical demand has inspired the development of many novel imaging techniques that could help surgeons with intraoperative margin assessment. This systematic review provides an overview of novel imaging techniques for intraoperative margin assessment in surgical oncology, and reports on their technical properties, feasibility in clinical practice and diagnostic accuracy. PubMed, Embase, Web of Science and the Cochrane library were systematically searched (2013‐2018) for studies reporting on imaging techniques for intraoperative margin assessment. Patient and study characteristics, technical properties, feasibility characteristics and diagnostic accuracy were extracted. This systematic review identified 134 studies that investigated and developed 16 groups of techniques for intraoperative margin assessment: fluorescence, advanced microscopy, ultrasound, specimen radiography, optical coherence tomography, magnetic resonance imaging, elastic scattering spectroscopy, bio‐impedance, X‐ray computed tomography, mass spectrometry, Raman spectroscopy, nuclear medicine imaging, terahertz imaging, photoacoustic imaging, hyperspectral imaging and pH measurement. Most studies were in early developmental stages (IDEAL 1 or 2a, n = 98); high‐quality stage 2b and 3 studies were rare. None of the techniques was found to be clearly superior in demonstrating high feasibility as well as high diagnostic accuracy. In conclusion, the field of imaging techniques for intraoperative margin assessment is highly evolving. This review provides a unique overview of the opportunities and limitations of the currently available imaging techniques.

What's new?

While surgical resection is critical in the treatment of primary solid tumors, resection at tumor margins remains problematic, with inadequately resected margins facilitating tumor recurrence. In this systematic review, the authors collected information on novel imaging techniques applied to the intraoperative assessment of tumor margins across cancer types. A total of 16 groups of techniques were identified, with many in early stages of clinical application. Following comparison, no single technique was clearly superior in clinical feasibility or diagnostic accuracy. The review highlights the evolving nature of imaging techniques for intraoperative margin assessment and identifies opportunities and limitations in the field.

Differentiation of breast tissue types for surgical margin assessment using machine learning and polarization-sensitive optical coherence tomography

We report an automated differentiation model for classifying malignant tumor, fibro-adipose, and stroma in human breast tissues based on polarization-sensitive optical coherence tomography (PS-OCT). A total of 720 PS-OCT images from 72 sites of 41 patients with H&E histology-confirmed diagnoses as the gold standard were employed in this study. The differentiation model is trained by the features extracted from both one standard OCT-based metric (i.e., intensity) and four PS-OCT-based metrics (i.e., phase difference between two channels (PD), phase retardation (PR), local phase retardation (LPR), and degree of polarization uniformity (DOPU)). Further optimized by forward searching and validated by leave-one-site-out-cross-validation (LOSOCV) method, the best feature subset was acquired with the highest overall accuracy of 93.5% for the model. Furthermore, to show the superiority of our differentiation model based on PS-OCT images over standard OCT images, the best model trained by intensity-only features (usually obtained by standard OCT systems) was also obtained with an overall accuracy of 82.9%, demonstrating the significance of the polarization information in breast tissue differentiation. The high performance of our differentiation model suggests the potential of using PS-OCT for intraoperative human breast tissue differentiation during the surgical resection of breast cancer.

Optical palpation for tumor margin assessment in breast-conserving surgery

Intraoperative margin assessment is needed to reduce the re-excision rate of breast-conserving surgery. One possibility is optical palpation, a tactile imaging technique that maps stress (force applied across the tissue surface) as an indicator of tissue stiffness. Images (optical palpograms) are generated by compressing a transparent silicone layer on the tissue and measuring the layer deformation using optical coherence tomography (OCT). This paper reports, for the first time, the diagnostic accuracy of optical palpation in identifying tumor within 1 mm of the excised specimen boundary using an automated classifier. Optical palpograms from 154 regions of interest (ROIs) from 71 excised tumor specimens were obtained. An automated classifier was constructed to predict the ROI margin status by first choosing a circle diameter, then searching for a location within the ROI where the circle was ≥ 75% filled with high stress (indicating a positive margin). A range of circle diameters and stress thresholds, as well as the impact of filtering out non-dense tissue regions, were tested. Sensitivity and specificity were calculated by comparing the automated classifier results with the true margin status, determined from co-registered histology. 83.3% sensitivity and 86.2% specificity were achieved, compared to 69.0% sensitivity and 79.0% specificity obtained with OCT alone on the same dataset using human readers. Representative optical palpograms show that positive margins containing a range of cancer types tend to exhibit higher stress compared to negative margins. These results demonstrate the potential of optical palpation for margin assessment.

Diagnostic accuracy of optical coherence tomography for assessing surgical margins of canine soft tissue sarcomas in observers of different specialties

OBJECTIVE

To determine the diagnostic accuracy of optical coherence tomography (OCT) to assess surgical margins of canine soft tissue sarcoma (STS) and determine the influence of observer specialty and training.

STUDY DESIGN

Blinded clinical prospective study.

ANIMALS

Twenty-five dogs undergoing surgical excision of STS.

METHODS

In vivo and ex vivo surgical margins were imaged with OCT after tumor resection. Representative images and videos were used to generate a training presentation and data sets. These were completed by 16 observers of four specialties (surgery, radiology, pathology, and OCT researchers). Images and videos from data sets were classified as cancerous or noncancerous.

RESULTS

The overall sensitivity and specificity were 88.2% and 92.8%, respectively, for in vivo tissues and 82.5% and 93.3%, respectively, for ex vivo specimens. The overall accurate classification for all specimens was 91.4% in vivo and 89.5% ex vivo. There was no difference in accuracy of interpretation of OCT imaging by observers of different specialties or experience levels.

CONCLUSION

Use of OCT to accurately assess surgical margins after STS excision was associated with a high sensitivity and specificity among various specialties. Personnel of all specialties and experience levels could effectively be trained to interpret OCT imaging.

CLINICAL SIGNIFICANCE

Optical coherence tomography can be used by personnel of different specialty experience levels and from various specialties to accurately identify canine STS in vivo and ex vivo after a short training session. These encouraging results provide evidence to justify further research to assess the ability of OCT to provide real-time assessments of surgical margins and its applicability to other neoplasms.

Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study

The possibility to assess molecular-biological and morphological features of particular breast cancer types can improve the precision of resection margin detection and enable accurate determining of the tumor aggressiveness, which is important for treatment selection. To enable reliable differentiation of breast-cancer subtypes and evaluation of resection margin, without performing conventional histological procedures, here we apply cross-polarization optical coherence tomography (CP-OCT) and compare it with a novel variant of compressional optical coherence elastography (C-OCE) in terms of the diagnostic accuracy (Ac) with histological verification. The study used 70 excised breast cancer specimens with different morphological structure and molecular status (Luminal A, Luminal B, Her2/Neo+, non-luminal and triple-negative cancer). Our first aim was to formulate convenient criteria of visual assessment of CP-OCT and C-OCE images intended (i) to differentiate tumorous and non-tumorous tissues and (ii) to enable more precise differentiation among different malignant states. We identified such criteria based on the presence of heterogeneities and characteristics of signal attenuation in CP-OCT images, as well as the presence of inclusions/mosaic structures combined with visually feasible assessment of several stiffness grades in C-OCE images. Secondly, we performed a blinded reader study of the Ac of C-OCE versus CP-OCT, for delineation of tumorous versus non-tumorous tissues followed by identification of breast cancer subtypes. For tumor detection, C-OCE showed higher specificity than CP-OCT (97.5% versus 93.3%) and higher Ac (96.0 versus 92.4%). For the first time, the Ac of C-OCE and CP-OCT were evaluated for differentiation between non-invasive and invasive breast cancer (90.4% and 82.5%, respectively). Furthermore, for invasive cancers, the difference between invasive but low-aggressive and highly-aggressive subtypes can be detected. For differentiation between non-tumorous tissue and low-aggressive breast-cancer subtypes, Ac was 95.7% for C-OCE and 88.1% for CP-OCT. For differentiation between non-tumorous tissue and highly-aggressive breast cancers, Ac was found to be 98.3% for C-OCE and 97.2% for CP-OCT. In all cases C-OCE showed better diagnostic parameters independently of the tumor type. These findings confirm the high potential of OCT-based examinations for rapid and accurate diagnostics during breast conservation surgery.

Statistical evaluation of reader variability in assessing the diagnostic performance of optical coherence tomography

SIGNIFICANCE

Optical coherence tomography (OCT) is widely used as a potential diagnostic tool for a variety of diseases including various types of cancer. However, sensitivity and specificity analyses of OCT in different cancers yield results varying from 11% to 100%. Hence, there is a need for more detailed statistical analysis of blinded reader studies.

AIM

Extensive statistical analysis is performed on results from a blinded study involving OCT of breast tumor margins to assess the impact of reader variability on sensitivity and specificity.

APPROACH

Five readers with varying levels of experience reading OCT images assessed 50 OCT images of breast tumor margins collected using an intraoperative OCT system. Statistical modeling and analysis was performed using the R language to analyze reader experience and variability.

RESULTS

Statistical analysis showed that the readers' prior experience with OCT images was directly related to the probability of the readers' assessment agreeing with histology. Additionally, results from readers with prior experience specific to OCT in breast cancer had a higher probability of agreement with histology compared to readers with experience with OCT in other (noncancer) diseases.

CONCLUSIONS

The results from this study demonstrate the potential impact of reader training and experience in the assessment of sensitivity and specificity. They also demonstrate even greater potential improvement in diagnostic performance by combining results from multiple readers. These preliminary findings suggest valuable directions for further study.

Development of Multispectral Optoacoustic Tomography as a Clinically Translatable Modality for Cancer Imaging

The use of optoacoustic imaging takes advantage of the photoacoustic effect to generate high-contrast, high-resolution medical images at penetration depths of up to 5 cm. Multispectral optoacoustic tomography (MSOT) is a type of optoacoustic imaging system that has seen promising preclinical success with a recent emergence into the clinic. Multiwavelength illumination of tissue allows for the mapping of multiple chromophores, which are generated endogenously or exogenously. However, translation of MSOT to the clinic is still in its preliminary stages. For successful translation, MSOT requires refinement of probes and data-acquisition systems to tailor to the human body, along with more intuitive, real-time visualization settings. The possibilities of optoacoustic imaging, namely MSOT, in the clinic are reviewed here. ©RSNA, 2020.

Accuracy of gross intraoperative margin assessment for breast cancer: experience since the SSO-ASTRO margin consensus guidelines

Gross intraoperative assessment can be used to ensure negative margins at the time of surgery. Previous studies of this technique were conducted before the introduction of consensus guidelines defining a “positive” margin. We performed a retrospective study examining the accuracy of this technique since these guidelines were published. We identified all specimens that were grossly examined at the time of breast conserving surgery from January 2014 to July 2020. Gross and final microscopic diagnoses were compared and the performance of intraoperative examination was assessed in terms of false positive and false negative rates. Logistic regression models were used to examine the effect of clinicopathologic covariates on discordance. 327 cases were reviewed. Gross exam prompted re-excision in 166 cases (61%). The rate of false negative discordance was 8.6%. In multivariate analysis, multifocality on final pathology was associated with discordance. We consider the false negative rate acceptable for routine clinical use; however, there is an ongoing need for more accurate methods for the intraoperative assessment of margins.

Diagnostic Accuracy of Quantitative Micro-Elastography for Margin Assessment in Breast-Conserving Surgery

Inadequate margins in breast-conserving surgery (BCS) are associated with an increased likelihood of local recurrence of breast cancer. Currently, approximately 20% of BCS patients require repeat surgery due to inadequate margins at the initial operation. Implementation of an accurate, intraoperative margin assessment tool may reduce this re-excision rate. This study determined, for the first time, the diagnostic accuracy of quantitative micro-elastography (QME), an optical coherence tomography (OCT)-based elastography technique that produces images of tissue microscale elasticity, for detecting tumor within 1 mm of the margins of BCS specimens. Simultaneous OCT and QME were performed on the margins of intact, freshly excised specimens from 83 patients undergoing BCS and on dissected specimens from 7 patients undergoing mastectomy. The resulting three-dimensional images (45 × 45 × 1 mm) were coregistered with postoperative histology to determine tissue types present in each scan. Data from 12 BCS patients and the 7 mastectomy patients served to build a set of images for reader training. One hundred and fifty-four subimages (10 × 10 × 1 mm) from the remaining 71 BCS patients were included in a blinded reader study, which resulted in 69.0% sensitivity and 79.0% specificity using OCT images, versus 92.9% sensitivity and 96.4% specificity using elasticity images. The quantitative nature of QME also facilitated development of an automated reader, which resulted in 100.0% sensitivity and 97.7% specificity. These results demonstrate high accuracy of QME for detecting tumor within 1 mm of the margin and the potential for this technique to improve outcomes in BCS. SIGNIFICANCE: An optical imaging technology probes breast tissue elasticity to provide accurate assessment of tumor margin involvement in breast-conserving surgery.

The feasibility and utility of optical coherence tomography directed histopathology for surgical margin assessment of canine mast cell tumours

Histopathologic surgical margin assessment in veterinary patients is an imprecise science with assessment limited to a small proportion of the surgical margin due to time and finances. Incomplete excision of canine mast cell tumours (MCTs) alters treatment recommendations and prognosis. Optical coherence tomography (OCT) is a novel imaging modality that has been reported in a single veterinary study for surgical margin assessment. Twenty-five dogs with 34 MCTs were enrolled in a prospective pilot-study to assess the imaging characteristics of canine MCTs with OCT and to evaluate the feasibility and utility of OCT-guided histopathology. All dogs underwent routine surgical excision of MCTs. OCT imaging was used to assess the entire surgical margin prior to placement in formalin. Either normal areas or areas suspected of incomplete MCT excision were inked. Standard histopathologic sectioning and tangential sectioning of inked areas were performed and compared to OCT results. OCT identified MCT near the surgical margin in 10 of 26 specimens (38.4%). Four specimens suspicious for incomplete margins on OCT had incomplete MCT excision that was missed on standard histopathologic sectioning. Six specimens had OCT-guided sections taken as suspicious, which did not show MCT on histopathology. OCT-guided pathology sections were able to detect incompletely excised MCT near the surgical margin with a sensitivity of 90% and specificity of 56.2% in this preliminary study. OCT imaging shows promise for guiding pathologists to areas of interest to improve the diagnostic accuracy of surgical margin assessment in excised canine MCTs.

Optoacoustic characterization of breast conserving surgery specimens - A pilot study

In this pilot study, we tested an ultrasound-guided optoacoustic tomography (US-OT) two-dimensional (2D) array scanner to understand the optoacoustic patterns of excised breastconserving surgery (BCS) specimens. We imaged 14 BCS specimens containing malignant tumors at eight wavelengths spanning 700-1100 nm. Spectral unmixing across multiple wavelengths allowed for visualizing major intrinsic chromophores in the breast tissue including hemoglobin and lipid up to a depth of 7 mm. We identified less/no lipid signals within the tumor and intense deoxy-hemoglobin (Hb) signals on the rim of the tumor as unique characteristics of malignant tumors in comparison to no tumor region. We also observed continuous broad lipid signals as features of negative margins and compromised lipid signals interrupted by vasculature as features of positive margins. These differentiating patterns can form the basis of US-OT to be explored as an alternate, fast and efficient intraoperative method for evaluation of tumor resection margins.

Evaluating optical coherence tomography for surgical margin assessment of canine mammary tumours

Optical coherence tomography (OCT) uses near-infrared light waves to generate real-time, high-resolution images on the microscopic scale similar to low power histopathology. Previous studies have demonstrated the use of OCT for real-time surgical margin assessment for human breast cancer. The use of OCT for canine mammary tumours (CMT) could allow intra-operative visualisation of residual tumour at the surgical margins. The purpose of this study was to assess OCT imaging for the detection of incomplete tumour resection following CMT surgery. We hypothesized that the OCT images would have comparable features to histopathological images of tissues at the surgical margins of CMT resections along with a high sensitivity of OCT detection of incomplete surgical excision of CMT. Thirty surgical specimens were obtained from nineteen client-owned dogs undergoing surgical resection of CMT. OCT image appearance and characteristics of adipose tissue, skin, mammary tissue and mammary tumour at the surgical margins were distinct and different. The OCT images of normal and abnormal tissues at the surgical margins were utilized to develop a dataset of OCT images for observer evaluation. The sensitivity and specificity for ex vivo images were 83.3% and 82.0% (observer 1) and 70.0% and 67.9% (observer 2). The sensitivity and specificity for in vivo images were 70.0% and 89.3% (observer 1) and 76.7% and 67.9% (observer 2). These results indicate a potential use of OCT for surgical margin assessment for CMT to optimize surgical intervention and clinical outcomes. Improved training and experience of observers may improve sensitivity and specificity.

Optical coherence tomography imaging of excised canine apocrine gland anal sac adenocarcinoma tumours

Optical coherence tomography (OCT) is an optical imaging modality that has been investigated for real-time surgical margin evaluation in human breast cancer patients. Previous veterinary OCT studies have been limited to surgical margin imaging for soft tissue sarcoma (STS) tumours. To the authors knowledge, OCT has never been used to characterize or evaluate other types of neoplasia in dogs. The goal of this study was to characterize the OCT imaging appearance of apocrine gland anal sac adenocarcinoma (AGASACA) in excised ex vivo specimens from five client-owned dogs. All excised tissue surgical margins were imaged using a clinical spectral domain OCT system and two to four areas suspicious for incomplete surgical margins were selected. These areas were inked and sections were trimmed for histopathology. This enabled OCT imaging from each area of interest to be compared with corresponding H&E stained histology imaging from the same location. OCT was able to identify the presence of AGASACA at or within 1 mm of the surgical margin in all areas of interest. AGASACA, similar to the previously described canine STS, generated a dense, highly scattering image without any specific textural architecture. This study was able to validate the ability of OCT to accurately identify another type of tumour presence at or close to the surgical margin in the dog. Further study is needed to assess OCT accuracy at identifying other tumour types in dogs to understand its potential clinical applications.

Three-dimensional mapping of the attenuation coefficient in optical coherence tomography to enhance breast tissue microarchitecture contrast

Effective intraoperative tumor margin assessment is needed to reduce re-excision rates in breast-conserving surgery (BCS). Mapping the attenuation coefficient in optical coherence tomography (OCT) throughout a sample to create an image (attenuation imaging) is one promising approach. For the first time, three-dimensional OCT attenuation imaging of human breast tissue microarchitecture using a wide-field (up to ~45 × 45 × 3.5 mm) imaging system is demonstrated. Representative results from three mastectomy and one BCS specimen (from 31 specimens) are presented with co-registered postoperative histology. Attenuation imaging is shown to provide substantially improved contrast over OCT, delineating nuanced features within tumors (including necrosis and variations in tumor cell density and growth patterns) and benign features (such as sclerosing adenosis). Additionally, quantitative micro-elastography (QME) images presented alongside OCT and attenuation images show that these techniques provide complementary contrast, suggesting that multimodal imaging could increase tissue identification accuracy and potentially improve tumor margin assessment.

Emerging Technologies for Real-Time Intraoperative Margin Assessment in Future Breast-Conserving Surgery

Clean surgical margins in breast-conserving surgery (BCS) are essential for preventing recurrence. Intraoperative pathologic diagnostic methods, such as frozen section analysis and imprint cytology, have been recognized as crucial tools in BCS. However, the complexity and time-consuming nature of these pathologic procedures still inhibit their broader applicability worldwide. To address this situation, two issues should be considered: 1) the development of nonpathologic intraoperative diagnosis methods that have better sensitivity, specificity, speed, and cost; and 2) the promotion of new imaging algorithms to standardize data for analyzing positive margins, as represented by artificial intelligence (AI), without the need for judgment by well-trained pathologists. Researchers have attempted to develop new methods or techniques; several have recently emerged for real-time intraoperative management of breast margins in live tissues. These methods include conventional imaging, spectroscopy, tomography, magnetic resonance imaging, microscopy, fluorescent probes, and multimodal imaging techniques. This work summarizes the traditional pathologic and newly developed techniques and discusses the advantages and disadvantages of each method. Taking into consideration the recent advances in analyzing pathologic data from breast cancer tissue with AI, the combined use of new technologies with AI algorithms is proposed, and future directions for real-time intraoperative margin assessment in BCS are discussed.

Fully Automated Postlumpectomy Breast Margin Assessment Utilizing Convolutional Neural Network Based Optical Coherence Tomography Image Classification Method

BACKGROUND

The purpose of this study was to develop a deep learning classification approach to distinguish cancerous from noncancerous regions within optical coherence tomography (OCT) images of breast tissue for potential use in an intraoperative setting for margin assessment.

METHODS

A custom ultrahigh-resolution OCT (UHR-OCT) system with an axial resolution of 2.7 μm and a lateral resolution of 5.5 μm was used in this study. The algorithm used an A-scan-based classification scheme and the convolutional neural network (CNN) was implemented using an 11-layer architecture consisting of serial 3 × 3 convolution kernels. Four tissue types were classified, including adipose, stroma, ductal carcinoma in situ, and invasive ductal carcinoma.

RESULTS

The binary classification of cancer versus noncancer with the proposed CNN achieved 94% accuracy, 96% sensitivity, and 92% specificity. The mean five-fold validation F1 score was highest for invasive ductal carcinoma (mean standard deviation, 0.89 ± 0.09) and adipose (0.79 ± 0.17), followed by stroma (0.74 ± 0.18), and ductal carcinoma in situ (0.65 ± 0.15).

CONCLUSION

It is feasible to use CNN based algorithm to accurately distinguish cancerous regions in OCT images. This fully automated method can overcome limitations of manual interpretation including interobserver variability and speed of interpretation and may enable real-time intraoperative margin assessment.

Near-infrared imaging and optical coherence tomography for intraoperative visualization of tumors

Surgical excision is the foundation of treatment for early-stage solid tumors in man and companion animals. Complete excision with appropriate margins of surrounding tumor-free tissue is crucial to survival. Intraoperative imaging allows real-time visualization of tumors, assessment of surgical margins, and, potentially, lymph nodes and satellite metastatic lesions, allowing surgeons to perform complete tumor resections while sparing surrounding vital anatomic structures. This Review will focus on the use of near-infrared imaging and optical coherence tomography for intraoperative tumor visualization.

Evaluation of surgically excised breast tissue microstructure using wide-field optical coherence tomography

BACKGROUND

Currently, positive margins at lumpectomy contribute to health care cost, patient anxiety, and treatment delay. Multiple technology solutions are being explored with the aim of lowering re-excision rates for breast-conserving surgery (BCS). We examined wide-field optical coherence tomography (WF-OCT), an innovative adjunct intraoperative imaging tool for tissue visualization of margins.

METHODS

This IRB-approved pilot study included women with invasive or in situ carcinoma scheduled for primary BCS. Lumpectomy specimens and any final/revised margins were imaged by optical coherence tomography immediately prior to standard histological processing. The optical coherence tomography used provided two-dimensional, cross-sectional, real-time depth visualization of the margin widths around excised specimens. A volume of images was captured for 10 × 10 cm tissue surface at high resolution (sub-30 μm) to a depth of 2 mm. Integrated interpretation was performed incorporating final pathology linked with the optical image data for correlation.

RESULTS

Wide-field optical coherence tomography was performed on 185 tissue samples (50 lumpectomy specimens and 135 additional margin shaves) in 50 subjects. Initial diagnosis was invasive ductal carcinoma (IDC) in 10, ductal carcinoma in situ (DCIS) in 14, IDC/DCIS in 22, invasive lobular carcinoma (ILC) in 2, ILC/DCIS in 1, and sarcoma in 1. Optical coherence tomography was concordant with final pathology in 178/185 tissue samples for overall accuracy of 86% and 96.2% (main specimen alone and main specimen + shave margins). Of seven samples that were discordant, 57% (4/7) were considered close (DCIS < 2 mm from margin) per final pathology.

CONCLUSION

Wide-field optical coherence tomography demonstrated concordance with histology at tissue margins, supporting its potential for use as a real-time adjunct intraoperative imaging tool for margin assessment. Further studies are needed for comprehensive evaluation in the intraoperative setting.

Ex Vivo Microscopy: A Promising Next-Generation Digital Microscopy Tool for Surgical Pathology Practice

CONTEXT.—

The rapid evolution of optical imaging modalities in recent years has opened the opportunity for ex vivo tissue imaging, which has significant implications for surgical pathology practice. These modalities have promising potential to be used as next-generation digital microscopy tools for examination of fresh tissue, with or without labeling with contrast agents.

OBJECTIVE.—

To review the literature regarding various types of ex vivo optical imaging platforms that can generate digital images for tissue recognition with potential for utilization in anatomic pathology clinical practices.

DATA SOURCES.—

Literature relevant to ex vivo tissue imaging obtained from the PubMed database.

CONCLUSIONS.—

Ex vivo imaging of tissues can be performed by using various types of optical imaging techniques. These next-generation digital microscopy tools have a promising potential for utilization in surgical pathology practice.

Insights into Hypoxia: Non-invasive Assessment through Imaging Modalities and Its Application in Breast Cancer

Oxygen is crucial to maintain the homeostasis in aerobic cells. Hypoxia is a condition in which cells are deprived of the oxygen supply necessary for their optimum performance. Whereas oxygen deprivation may occur in normal physiological processes, hypoxia is frequently associated with pathological conditions. It has been identified as a stressor in the tumor microenvironment, acting as a key mediator of cancer development. Numerous pathways are activated in hypoxic cells that affect cell signaling and gene regulation to promote the survival of these cells by stimulating angiogenesis, switching cellular metabolism, slowing their growth rate, and preventing apoptosis. The induction of dysregulated metabolism in cancer cells by hypoxia results in aggressive tumor phenotypes that are characterized by rapid progression, treatment resistance, and poor prognosis. A non-invasive assessment of hypoxia-induced metabolic and architectural changes in tumors is advisable to fully improve breast cancer (BC) patient management, by potentially reducing the need for invasive biopsy procedures and evaluating tumor response to treatment. This review provides a comprehensive overview of the molecular changes in breast tumors secondary to hypoxia and the non-invasive imaging alternatives to evaluate oxygen deprivation, with an emphasis on their application in BC and the advantages and limitations of the currently available techniques.

Towards mm-wave spectroscopy for dielectric characterization of breast surgical margins

PURPOSE

The evaluation of the surgical margin in breast conservative surgery is a matter of general interest as such treatments are subject to the critical issue of margin status as positive surgical margins can undermine the effectiveness of the procedure. The relatively unexplored ability of millimeter-wave (mm-wave) spectroscopy to provide insight into the dielectric properties of breast tissues was investigated as a precursor to their possible use in assessment of surgical margins.

METHODS

We assessed the ability of a mm-wave system with a roughly hemispherical sensitive volume of ∼3 mm radius to distinguish malignant breast lesions in prospectively and consecutively collected tumoral and non-tumoral ex-vivo breast tissue samples from 91 patients. We characterized the dielectric properties of 346 sites in these samples, encompassing malignant, fibrocystic disease and normal breast tissues. An expert pathologist subsequently evaluated all measurement sites.

RESULTS

At multivariate analysis, mm-wave dielectric properties were significantly correlated to histologic diagnosis and fat content. Further, using 5-fold cross-validation in a Bayesian logistic mixed model that considered the patient as a random effect, the mm-wave dielectric properties of neoplastic tissues were significantly different from normal breast tissues, but not from fibrocystic tissue.

CONCLUSION

Reliable discrimination of malignant from normal, fat-rich breast tissue to a depth compatible with surgical margin assessment requirements was achieved with mm-wave spectroscopy.

Clinical feasibility of optical coherence micro-elastography for imaging tumor margins in breast-conserving surgery

It has been demonstrated that optical coherence micro-elastography (OCME) provides additional contrast of tumor compared to optical coherence tomography (OCT) alone. Previous studies, however, have predominantly been performed on mastectomy specimens. Such specimens typically differ substantially in composition and geometry from the more clinically relevant wide-local excision (WLE) specimens excised during breast-conserving surgery. As a result, it remains unclear if the mechanical contrast observed is maintained in WLE specimens. In this manuscript, we begin to address this issue by performing a feasibility study of OCME on 17 freshly excised, intact WLE specimens. In addition, we present two developments required to sustain the progression of OCME towards intraoperative deployment. First, to enable the rapid visualization of en face images required for intraoperative assessment, we describe an automated segmentation algorithm to fuse en face micro-elastograms with OCT images to provide dual contrast images. Secondly, to validate contrast in micro-elastograms, we present a method that enables co-registration of en face images with histology of WLE specimens, sectioned in the orthogonal plane, without any modification to the standard clinical workflow. We present a summary of the observations across the 17 specimens imaged in addition to representative micro-elastograms and OCT images demonstrating contrast in a number of tumor margins, including those involved by invasive ductal carcinoma, mucinous carcinoma, and solid-papillary carcinoma. The results presented here demonstrate the potential of OCME for imaging tumor margins.

Interpretation of Optical Coherence Tomography Images for Breast Tissue Assessment

PURPOSE

Initial studies have shown that optical coherence tomography (OCT) is an effective margin-evaluation tool for breast-conserving surgery, but methods for the interpretation of breast OCT images have not been directly studied. In this work, breast pathologies were assessed with a handheld OCT probe. OCT images and corresponding histology were used to develop guidelines for the identification of breast tissue features in OCT images.

METHODS

Mastectomy and breast-conserving surgery specimens from 26 women were imaged with a handheld OCT probe. During standard pathology specimen dissection, representative 1-cm × 1-cm tissue regions were grossly identified, assessed with OCT, inked for orientation and image-matching purposes, and processed. Histology slides corresponding to the OCT image region were digitally photographed. OCT and histology images from the same region were paired by selecting the best structural matches.

RESULTS

In total, 2880 OCT images were acquired from 26 breast specimens (from 26 patients) and 48 matching OCT-histology image pairs were identified. These matched image pairs illustrate tissue types including adipose tissue, dense fibrosis, fibroadipose tissue, blood vessels, regular and hyperplastic ducts and lobules, cysts, cyst, fibroadenoma, invasive ductal carcinoma, invasive lobular carcinoma, ductal carcinoma in situ, calcifications, and biopsy cavities. Differentiation between pathologies was achieved by considering feature boundaries, interior appearance, posterior shadowing or enhancement, and overall morphologic patterns.

CONCLUSIONS

This is the first work to systematically catalog the critical features of breast OCT images. The results indicate that OCT can be used to identify and distinguish between benign and malignant features in human breast tissue.

Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks

Assessing the surgical margin during breast lumpectomy operations can avoid the need for additional surgery. Optical coherence tomography (OCT) is an imaging technique that has been proven to be efficient for this purpose. However, to avoid overloading the surgeon during the operation, automatic cancer detection at the surface of the removed tissue is needed. This work explores automated margin assessment on a sample of patient data collected at the Pathology Department, Severance Hospital (Seoul, South Korea). Some methods based on the spatial statistics of the images have been developed, but the obtained results are still far from human performance. In this work, we investigate the possibility to use deep neural networks (DNNs) for real time margin assessment, demonstrating performance significantly better than the reported literature and close to the level of a human expert. Since the goal is to detect the presence of cancer, a patch-based classification method is proposed, as it is sufficient for detection, and requires training data that is easier and cheaper to collect than for other approaches such as segmentation. For that purpose, we train a DNN architecture that was proved to be efficient for small images on patches extracted from images containing only cancer or only normal tissue as determined by pathologists in a university hospital. As the number of available images in all such studies is by necessity small relative to other deep network applications such as ImageNet, a good regularization method is needed. In this work, we propose to use a recently introduced function norm regularization that attempts to directly control the function complexity, in contrast to classical approaches such as weight decay and DropOut. As neither the code nor the data of previous results are publicly available, the obtained results are compared with reported results in the literature for a conservative comparison. Moreover, our method is applied to locally collected data on several data configurations. The reported results are the average over the different trials. The experimental results show that the use of DNNs yields significantly better results than other techniques when evaluated in terms of sensitivity, specificity, F1 score, G-mean and Matthews correlation coefficient. Function norm regularization yielded higher and more robust results than competing regularization methods. We have demonstrated a system that shows high promise for (partially) automated margin assessment of human breast tissue, Equal error rate (EER) is reduced from approximately 12% (the lowest reported in the literature) to 5% - a 58% reduction. The method is computationally feasible for intraoperative application (less than 2 s per image) at the only cost of a longer offline training time.