Review of methods for intraoperative margin detection for breast conserving surgery

Deep learning-assisted low-cost autofluorescence microscopy for rapid slide-free imaging with virtual histological staining

Slide-free imaging techniques have shown great promise in improving the histological workflow. For example, computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP) has achieved high resolution with a long depth of field, which, however, requires a costly ultraviolet laser. Here, simply using a low-cost light-emitting diode (LED), we propose a deep learning-assisted framework of enhanced widefield microscopy, termed EW-LED, to generate results similar to CHAMP (the learning target). Comparing EW-LED and CHAMP, EW-LED reduces the cost by 85×, shortening the image acquisition time and computation time by 36× and 17×, respectively. This framework can be applied to other imaging modalities, enhancing widefield images for better virtual histology.

Intraoperative Evaluation of Breast Tissues During Breast Cancer Operations Using the MasSpec Pen

Importance

Surgery with complete tumor resection remains the main treatment option for patients with breast cancer. Yet, current technologies are limited in providing accurate assessment of breast tissue in vivo, warranting development of new technologies for surgical guidance.

Objective

To evaluate the performance of the MasSpec Pen for accurate intraoperative assessment of breast tissues and surgical margins based on metabolic and lipid information.

Design, Setting, and Participants

In this diagnostic study conducted between February 23, 2017, and August 19, 2021, the mass spectrometry-based device was used to analyze healthy breast and invasive ductal carcinoma (IDC) banked tissue samples from adult patients undergoing breast surgery for ductal carcinomas or nonmalignant conditions. Fresh-frozen tissue samples and touch imprints were analyzed in a laboratory. Intraoperative in vivo and ex vivo breast tissue analyses were performed by surgical staff in operating rooms (ORs) within 2 different hospitals at the Texas Medical Center. Molecular data were used to build statistical classifiers.

Main Outcomes and Measures

Prediction results of tissue analyses from classification models were compared with gross assessment, frozen section analysis, and/or final postoperative pathology to assess accuracy.

Results

All data acquired from the 143 banked tissue samples, including 79 healthy breast and 64 IDC tissues, were included in the statistical analysis. Data presented rich molecular profiles of healthy and IDC banked tissue samples, with significant changes in relative abundances observed for several metabolic species. Statistical classifiers yielded accuracies of 95.6%, 95.5%, and 90.6% for training, validation, and independent test sets, respectively. A total of 25 participants enrolled in the clinical, intraoperative study; all were female, and the median age was 58 years (IQR, 44-66 years). Intraoperative testing of the technology was successfully performed by surgical staff during 25 breast operations. Of 273 intraoperative analyses performed during 25 surgical cases, 147 analyses from 22 cases were subjected to statistical classification. Testing of the classifiers on 147 intraoperative mass spectra yielded 95.9% agreement with postoperative pathology results.

Conclusions and Relevance

The findings of this diagnostic study suggest that the mass spectrometry-based system could be clinically valuable to surgeons and patients by enabling fast molecular-based intraoperative assessment of in vivo and ex vivo breast tissue samples and surgical margins.

Artifact suppression for breast specimen imaging in micro CBCT using deep learning

BACKGROUND

Cone-beam computed tomography (CBCT) has been introduced for breast-specimen imaging to identify a free resection margin of abnormal tissues in breast conservation. As well-known, typical micro CT consumes long acquisition and computation times. One simple solution to reduce the acquisition scan time is to decrease of the number of projections, but this method generates streak artifacts on breast specimen images. Furthermore, the presence of a metallic-needle marker on a breast specimen causes metal artifacts that are prominently visible in the images. In this work, we propose a deep learning-based approach for suppressing both streak and metal artifacts in CBCT.

METHODS

In this work, sinogram datasets acquired from CBCT and a small number of projections containing metal objects were used. The sinogram was first modified by removing metal objects and up sampling in the angular direction. Then, the modified sinogram was initialized by linear interpolation and synthesized by a modified neural network model based on a U-Net structure. To obtain the reconstructed images, the synthesized sinogram was reconstructed using the traditional filtered backprojection (FBP) approach. The remaining residual artifacts on the images were further handled by another neural network model, ResU-Net. The corresponding denoised image was combined with the extracted metal objects in the same data positions to produce the final results.

RESULTS

The image quality of the reconstructed images from the proposed method was improved better than the images from the conventional FBP, iterative reconstruction (IR), sinogram with linear interpolation, denoise with ResU-Net, sinogram with U-Net. The proposed method yielded 3.6 times higher contrast-to-noise ratio, 1.3 times higher peak signal-to-noise ratio, and 1.4 times higher structural similarity index (SSIM) than the traditional technique. Soft tissues around the marker on the images showed good improvement, and the mainly severe artifacts on the images were significantly reduced and regulated by the proposed.

METHOD

CONCLUSIONS

Our proposed method performs well reducing streak and metal artifacts in the CBCT reconstructed images, thus improving the overall breast specimen images. This would be beneficial for clinical use.

Robot-assisted PSMA-radioguided Surgery to Assess Surgical Margins and Nodal Metastases in Prostate Cancer Patients: Report on Three Cases Using an Intraoperative PET-CT Specimen Imager

INTRODUCTION

The aim of this feasibility study was to test the intraoperative use of this brand-new specimen PET/CT to guide robot-assisted radical prostatectomy and pelvic lymph node dissection.

MATERIALS AND METHODS

Three cases of robot-assisted radical prostatectomy and pelvic lymph node dissection were performed with intraoperative use of the specimen imager. Surgeries were performed with Da Vinci Xi robot. An intravenous injection of 68Ga-PSMA-11 was performed in the OR and after complete excision, the specimens were analyzed with the imager.

RESULTS

The average nodal yield was 17.3 (5.8 SD) nodes per patient. Specimen PET/CT images showed a focal uptake in a metastatic node (TBR 13.6), and no uptake or diffuse, faint uptake in negative nodes (TBR range: 1-5.3). The specimen imager provided intraoperative PET/CT images that clearly showed negative surgical margins in two patients, whereas the results were uncertain in a locally advanced case.

CONCLUSION

The intraoperative use of the specimen PET/CT imager is safe and feasible and could improve the evaluation of prostate surgical margins and lymph node status.

Understanding Fibroadenoma of the Breast: A Comprehensive Review of Pre-operative and Post-operative Clinicopathological Correlations

Fibroadenomas of the breast are common benign lesions that predominantly affect young women. This review provides a comprehensive overview of fibroadenoma management, encompassing their definition, clinical presentation, diagnostic tools, surgical management, clinicopathological correlations, treatment outcomes, complications, and emerging research. Fibroadenomas typically present as palpable breast lumps, often with no associated nipple discharge, and their diagnosis relies on a combination of clinical examination, breast imaging, and pathological confirmation. Surgical interventions, including excisional biopsy and lumpectomy, offer symptom relief and favorable long-term outcomes. Minimally invasive techniques and ongoing research into genomics and molecular aspects hold promise for the future of fibroadenoma management. Multidisciplinary collaboration among healthcare providers is paramount, ensuring accurate diagnosis, personalized treatment decisions, and holistic patient care. As research advances, the management of fibroadenomas is poised to evolve, providing improved diagnostic accuracy, minimally invasive treatments, and enhanced patient outcomes.

Fluorescence-based absolute quantification of near-infrared probes in tissue extracts for biodistribution analyses

In recent years, significant progress has been made in the development of fluorescent contrast agents for clinical applications. For the development of a fluorescent probe, it is crucial to evaluate its safety profile, including biodistribution. Specific methods need to be developed for the absolute quantification of fluorescent probes in tissue specimens from animals administered with test compounds in the framework of biodistribution/efficacy/toxicity studies. Here, we describe a new method for the absolute quantification of fluorescent probes in tissue specimens from animals administered with compounds that have absorption and emission wavelength in the Near-Infrared region (600-800 nm). The protocol is based on the standard addition approach in order to minimize the interference of the matrix on the analyte signal causing inaccuracy in the absolute determination of the concentration. The measurement of the fluorescence intensity is done via a microplate reader. The method has been fully validated and applied for the quantification of a fluorescence-guided surgery targeted contrast agent in a Good Laboratory Practice (GLP) biodistribution study. Results clearly demonstrate that this procedure is fully applicable in a preclinical setting and that it overcomes common issues associated with fluorescence signal quantification in tissue extracts.

Breast-Conserving Surgery Margin Guidance Using Micro-Computed Tomography: Challenges When Imaging Radiodense Resection Specimens

BACKGROUND

Breast-conserving surgery (BCS) is an integral component of early-stage breast cancer treatment, but costly reexcision procedures are common due to the high prevalence of cancer-positive margins on primary resections. A need exists to develop and evaluate improved methods of margin assessment to detect positive margins intraoperatively.

METHODS

A prospective trial was conducted through which micro-computed tomography (micro-CT) with radiological interpretation by three independent readers was evaluated for BCS margin assessment. Results were compared to standard-of-care intraoperative margin assessment (i.e., specimen palpation and radiography [abbreviated SIA]) for detecting cancer-positive margins.

RESULTS

Six hundred margins from 100 patients were analyzed. Twenty-one margins in 14 patients were pathologically positive. On analysis at the specimen-level, SIA yielded a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 42.9%, 76.7%, 23.1%, and 89.2%, respectively. SIA correctly identified six of 14 margin-positive cases with a 23.5% false positive rate (FPR). Micro-CT readers achieved sensitivity, specificity, PPV, and NPV ranges of 35.7-50.0%, 55.8-68.6%, 15.6-15.8%, and 86.8-87.3%, respectively. Micro-CT readers correctly identified five to seven of 14 margin-positive cases with an FPR range of 31.4-44.2%. If micro-CT scanning had been combined with SIA, up to three additional margin-positive specimens would have been identified.

DISCUSSION

Micro-CT identified a similar proportion of margin-positive cases as standard specimen palpation and radiography, but due to difficulty distinguishing between radiodense fibroglandular tissue and cancer, resulted in a higher proportion of false positive margin assessments.

Image-guided cancer surgery: a narrative review on imaging modalities and emerging nanotechnology strategies

Surgical resection is the cornerstone of solid tumour treatment. Current techniques for evaluating margin statuses, such as frozen section, imprint cytology, and intraoperative ultrasound, are helpful. However, an intraoperative assessment of tumour margins that is accurate and safe is clinically necessary. Positive surgical margins (PSM) have a well-documented negative effect on treatment outcomes and survival. As a result, surgical tumour imaging methods are now a practical method for reducing PSM rates and improving the efficiency of debulking surgery. Because of their unique characteristics, nanoparticles can function as contrast agents in image-guided surgery. While most image-guided surgical applications utilizing nanotechnology are now in the preclinical stage, some are beginning to reach the clinical phase. Here, we list the various imaging techniques used in image-guided surgery, such as optical imaging, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine imaging, and the most current developments in the potential of nanotechnology to detect surgical malignancies. In the coming years, we will see the evolution of nanoparticles tailored to specific tumour types and the introduction of surgical equipment to improve resection accuracy. Although the promise of nanotechnology for producing exogenous molecular contrast agents has been clearly demonstrated, much work remains to be done to put it into practice.

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.

High Dynamic Range Dual-Modal White Light Imaging Improves the Accuracy of Tumor Bed Sampling After Neoadjuvant Therapy for Breast Cancer

OBJECTIVES

Accurate evaluation of residual cancer burden remains challenging because of the lack of appropriate techniques for tumor bed sampling. This study evaluated the application of a white light imaging system to help pathologists differentiate the components and location of tumor bed in specimens.

METHODS

The high dynamic range dual-mode white light imaging (HDR-DWI) system was developed to capture antiglare reflection and multiexposure HDR transmission images. It was tested in 60 specimens of modified radical mastectomy after neoadjuvant therapy. We observed the differential transmittance among tumor tissue, fibrosis tissue, and adipose tissue.

RESULTS

The sensitivity and specificity of HDR-DWI were compared with x-ray or visual examination to determine whether HDR-DWI was superior in identifying tumor beds. We found that tumor tissue had lower transmittance (0.12 ± 0.03) than fibers (0.15 ± 0.04) and fats (0.27 ± 0.07) (P < .01).

CONCLUSIONS

HDR-DWI was more sensitive in identifying fiber and tumor tissues than cabinet x-ray and visual observation (P < .01). In addition, HDR-DWI could identify more fibrosis areas than the currently used whole slide imaging did in 12 samples (12/60). We have determined that HDR-DWI can provide more in-depth tumor bed information than x-ray and visual examination do, which will help prevent diagnostic errors in tumor bed sampling.

Volumetric Tissue Imaging of Surgical Tissue Specimens Using Micro-Computed Tomography: An Emerging Digital Pathology Modality for Nondestructive, Slide-Free Microscopy-Clinical Applications of Digital Pathology in 3 Dimensions

OBJECTIVES

Micro-computed tomography (micro-CT) is a novel, nondestructive, slide-free digital imaging modality that enables the acquisition of high-resolution, volumetric images of intact surgical tissue specimens. The aim of this systematic mapping review is to provide a comprehensive overview of the available literature on clinical applications of micro-CT tissue imaging and to assess its relevance and readiness for pathology practice.

METHODS

A computerized literature search was performed in the PubMed, Scopus, Web of Science, and CENTRAL databases. To gain insight into regulatory and financial considerations for performing and examining micro-CT imaging procedures in a clinical setting, additional searches were performed in medical device databases.

RESULTS

Our search identified 141 scientific articles published between 2000 and 2021 that described clinical applications of micro-CT tissue imaging. The number of relevant publications is progressively increasing, with the specialties of pulmonology, cardiology, otolaryngology, and oncology being most commonly concerned. The included studies were mostly performed in pathology departments. Current micro-CT devices have already been cleared for clinical use, and a Current Procedural Terminology (CPT) code exists for reimbursement of micro-CT imaging procedures.

CONCLUSIONS

Micro-CT tissue imaging enables accurate volumetric measurements and evaluations of entire surgical specimens at microscopic resolution across a wide range of clinical applications.

Challenges in, and recommendations for, hyperspectral imaging in ex vivo malignant glioma biopsy measurements

The visualization of protoporphyrin IX (PPIX) fluorescence with the help of surgical microscopes during 5-aminolevulinic acid-mediated fluorescence-guided resection (FGR) of gliomas is still limited at the tumor margins. Hyperspectral imaging (HI) detects PPIX more sensitively but is not yet ready for intraoperative use. We illustrate the current status with three experiments and summarize our own experience using HI: (1) assessment of HI analysis algorithm using pig brain tissue, (2) a partially retrospective evaluation of our experience from HI projects, and (3) device comparison of surgical microscopy and HI. In (1), we address the problem that current algorithms for evaluating HI data are based on calibration with liquid phantoms, which have limitations. Their pH is low compared to glioma tissue; they provide only one PPIX photo state and only PPIX as fluorophore. Testing the HI algorithm with brain homogenates, we found proper correction for optical properties but not pH. Considerably more PPIX was measured at pH 9 than at pH 5. In (2), we indicate pitfalls and guide HI application. In (3), we found HI superior to the microscope for biopsy diagnosis (AUC = 0.845 ± 0.024 (cut-off 0.75 µg PPIX/ml) vs. 0.710 ± 0.035). HI thus offers potential for improved FGR.

Cysteine Cathepsins in Breast Cancer: Promising Targets for Fluorescence-Guided Surgery

The majority of breast cancer patients is treated with breast-conserving surgery (BCS) combined with adjuvant radiation therapy. Up to 40% of patients has a tumor-positive resection margin after BCS, which necessitates re-resection or additional boost radiation. Cathepsin-targeted near-infrared fluorescence imaging during BCS could be used to detect residual cancer in the surgical cavity and guide additional resection, thereby preventing tumor-positive resection margins and associated mutilating treatments. The cysteine cathepsins are a family of proteases that play a major role in normal cellular physiology and neoplastic transformation. In breast cancer, the increased enzymatic activity and aberrant localization of many of the cysteine cathepsins drive tumor progression, proliferation, invasion, and metastasis. The upregulation of cysteine cathepsins in breast cancer cells indicates their potential as a target for intraoperative fluorescence imaging. This review provides a summary of the current knowledge on the role and expression of the most important cysteine cathepsins in breast cancer to better understand their potential as a target for fluorescence-guided surgery (FGS). In addition, it gives an overview of the cathepsin-targeted fluorescent probes that have been investigated preclinically and in breast cancer patients. The current review underscores that cysteine cathepsins are highly suitable molecular targets for FGS because of favorable expression and activity patterns in virtually all breast cancer subtypes. This is confirmed by cathepsin-targeted fluorescent probes that have been shown to facilitate in vivo breast cancer visualization and tumor resection in mouse models and breast cancer patients. These findings indicate that cathepsin-targeted FGS has potential to improve treatment outcomes in breast cancer patients.

Adaptive Design of Fluorescence Imaging Systems for Custom Resolution, Fields of View, and Geometries

Objective and Impact Statement: We developed a generalized computational approach to design uniform, high-intensity excitation light for low-cost, quantitative fluorescence imaging of in vitro, ex vivo, and in vivo samples with a single device. Introduction: Fluorescence imaging is a ubiquitous tool for biomedical applications. Researchers extensively modify existing systems for tissue imaging, increasing the time and effort needed for translational research and thick tissue imaging. These modifications are application-specific, requiring new designs to scale across sample types. Methods: We implemented a computational model to simulate light propagation from multiple sources. Using a global optimization algorithm and a custom cost function, we determined the spatial positioning of optical fibers to generate 2 illumination profiles. These results were implemented to image core needle biopsies, preclinical mammary tumors, or tumor-derived organoids. Samples were stained with molecular probes and imaged with uniform and nonuniform illumination. Results: Simulation results were faithfully translated to benchtop systems. We demonstrated that uniform illumination increased the reliability of intraimage analysis compared to nonuniform illumination and was concordant with traditional histological findings. The computational approach was used to optimize the illumination geometry for the purposes of imaging 3 different fluorophores through a mammary window chamber model. Illumination specifically designed for intravital tumor imaging generated higher image contrast compared to the case in which illumination originally optimized for biopsy images was used. Conclusion: We demonstrate the significance of using a computationally designed illumination for in vitro, ex vivo, and in vivo fluorescence imaging. Application-specific illumination increased the reliability of intraimage analysis and enhanced the local contrast of biological features. This approach is generalizable across light sources, biological applications, and detectors.

High-Frequency (30 MHz-6 GHz) Breast Tissue Characterization Stabilized by Suction Force for Intraoperative Tumor Margin Assessment

A gigahertz (GHz) range antenna formed by a coaxial probe has been applied for sensing cancerous breast lesions in the scanning platform with the assistance of a suction tube. The sensor structure was a planar central layer and a metallic sheath of size of 3 cm² connected to a network analyzer (keySight FieldFox N9918A) with operational bandwidth up to 26.5 GHz. Cancer tumor cells have significantly higher water content (as a dipolar molecule) than normal breast cells, changing their polarization responses and dielectric losses to incoming GHz-based stimulation. Principal component analysis named S₁₁, related to the dispersion ratio of the input signal, is used as a parameter to identify malignant tumor cells in a mouse model (in vivo) and tumor specimens of breast cancer patients (in vitro) (both central and marginal parts). The results showed that S₁₁ values in the frequency range from 5 to 6 GHz were significantly higher in cancer-involved breast lesions. Histopathological analysis was the gold standard for achieving the S₁₁ calibration to distinguish normal from cancerous lesions. Our calibration on tumor specimens presented 82% positive predictive value (PPV), 100% negative predictive value (NPV), and 86% accuracy. Our goal is to apply this system as an in vivo non-invasive tumor margin scanner after further investigations in the future.

Automated breast ultrasound (ABUS) for intraoperative margin control on surgical specimens in breast conserving surgery

PURPOSE

As breast-conserving surgery (BCS) has become the standard for treatment of early breast cancer, the need for new technologies to improve intraoperative margin assessment has become clear. Close or positive margins during BCS lead to additional surgeries, treatment delay, additional stress for patients and increasing healthcare cost. Automated three-dimensional breast ultrasound (ABUS) systems are meant to overcome the shortcomings of hand-held ultrasound (HHUS). In this study, we investigate the feasibility of ABUS to conduct ultrasound on surgical specimens in breast conserving therapy.

METHODS

In this monocentric, non-interventional study, specimens of 40 women were examined via ABUS. A construction with isotonic saline solution, gel pads and ABUS membranes was invented by our team to produce images of breast cancer specimens using ABUS. Evaluation of the ABUS images was carried out by two independent physicians trained on ABUS evaluation.

RESULTS

ABUS was conducted on 40 specimens. 90% of the generated images were of high quality. Measured tumor sizes with ABUS were bigger than measured tumor size with HHUS (mean tumor size 22.9 vs. 18.1 mm, CI 2.38-7.35, p < 0.05). The mean difference between the ABUS tumor size and the pathological tumor size was 1.8 mm (CI - 0.84-4.53, p = 0.17). The mean difference between the HHUS tumor size and the pathological tumor size was 3.2 mm (CI - 5.35 to - 1.03, p = 0.005).

CONCLUSION

ABUS seems to be a suitable method to conduct specimen ultrasound. Further studies are required to evaluate the accuracy of ABUS for intraoperative margin assessment and possible implementation in clinical work routine.

Investigating the feasibility of a hand-held photoacoustic imaging probe for margin assessment during breast conserving surgery

Approximately 19 % of breast cancer patients undergoing breast conserving surgery (BCS) must return for a secondary surgery due to incomplete tumour removal. Our previous work demonstrated that the lower lipid content, characteristic of tumour tissue, was observed as regions of hypo-intense photoacoustic (PA) contrast. The goal of this work was to evaluate feasibility of a low-frequency, hand-held PA imaging probe for surgical margin assessment based on lipid content differences. Here, we describe (i) the design of a prototype hand-held PA imaging probe, (ii) the effect of limited-bandwidth on image contrast, (iii) accuracy towards hypo-intense contrast detection, (iv) the limited-view characteristics of the single sensor design, and (iv) early imaging results of an ex-vivo breast cancer specimen. The probe incorporates a single polyvinylidene fluoride acoustic sensor, a 1-to-4 optical fibre bundle and a polycarbonate axicon lens for light delivery. Imaging results on phantoms designed to mimic positive margins demonstrated the ability to detect gaps in optical absorption as small as 1 mm in width. Compared to images from a near full-view PAI system, the hand-held PAI probe had higher signal to noise ratio but suffered from negativity image artifacts. Lumpectomy specimen imaging showed that strong signals can be obtained from the fatty tissue. Taken together, the results show this imaging approach with a hand-held probe has potential for detection of residual breast cancer tissue during BCS; however, more work is needed to reduce the size of the probe to fit within the surgical cavity.

Accuracy of cone-beam computed tomography, digital mammography and digital breast tomosynthesis for microcalcifications and margins to microcalcifications in breast specimens

Accurate determination of resection margins in breast specimens is important as complete removal of malignancy is a prerequisite for patients' outcome. Mammography (DM) as 2D-technique provides only limited value in margin assessment. Therefore, we investigated whether cone-beam computed tomography (CBCT) or digital breast tomosynthesis (DBT) has incremental value in assessing margins to microcalcifications. Three independent readers investigated breast specimens for presence of microcalcifications and the smallest distance to margins. Histopathology served as gold standard. Microcalcifications were detected in 15 out of 21 included specimens (71%). Pooled sensitivity for DM, DBT and CBCT for microcalcifications compared to preoperative DM was 0.98 (CI 0.94-0.99), 0.83 (CI 0.73-0.94) and 0.94 (CI 0.87-0.99), pooled specificity was 0.99 (CI 0.99-0.99), 0.73 (CI 0.51-0.96) and 0.60 (CI 0.35-0.85). Mean measurement error for margin determination for DM, DBT and CBCT was 10 mm, 14 mm and 6 mm (p = 0.002) with significant difference between CBCT and the other devices (p < 0.03). Mean reading time required by the readers to analyze DM, DBT and CBCT, was 36, 43 and 54 s (p < 0.001). Although DM allows reliable detection of microcalcifications, measurement of resection margin was significantly more accurate with CBCT. Thus, a combination of methods or improved CBCT might provide a more accurate determination of disease-free margins in breast specimens.

Diagnostic accuracy of radiography, digital breast tomosynthesis, micro-CT and ultrasound for margin assessment during breast surgery: A systematic review and meta-analysis

RATIONALE AND OBJECTIVES

Achieving adequate resection margins in breast conserving surgery is challenging and often demands more than one surgical procedure. We evaluated pooled diagnostic sensitivity, and specificity of radiological methods for intraoperative margin assessment and their impact on repeat surgery rate.

MATERIALS AND METHODS

We included studies using radiography, digital breast tomosynthesis (DBT), micro-CT, and ultrasound for intraoperative margin assessment with the histological assessment as the reference method. A systematic search was performed in PubMed, Embase, Cochrane Library, Scopus, and Web of Science. Two investigators screened the studies for eligibility criteria and extracted data of the included studies independently. The quality assessment on diagnostic accuracy studies (QUADAS)-2 tool was used. A bivariate random effect model was used to obtained pooled sensitivity and specificity of the index tests in the meta-analysis.

RESULTS

The systematic search resulted in screening of 798 unique records. Twenty-two articles with 29 radiological imaging methods were selected for meta-analysis. Pooled sensitivity and specificity and area under the curve were calculated for each of the 4 subgroups in the meta-analysis respectively: Radiography; 52%, 77%, 60%, DBT; 67%, 76%, 76%, micro-CT; 68%, 69%, 72%, and ultrasound; 72%, 78%, 80%. The repeat surgery rate was poorly reported in the included studies.

CONCLUSION

Ultrasound showed the highest and radiography the lowest diagnostic performance for intraoperative margin assessment. However, the heterogeneity between studies was high and the subgroups small. The radiological methods for margin assessment need further improvement to provide reliable guidance in the clinical workflow and to prevent repeat surgeries.

Automated assessment of breast margins in deep ultraviolet fluorescence images using texture analysis

Microscopy with ultraviolet surface excitation (MUSE) is increasingly studied for intraoperative assessment of tumor margins during breast-conserving surgery to reduce the re-excision rate. Here we report a two-step classification approach using texture analysis of MUSE images to automate the margin detection. A study dataset consisting of MUSE images from 66 human breast tissues was constructed for model training and validation. Features extracted using six texture analysis methods were investigated for tissue characterization, and a support vector machine was trained for binary classification of image patches within a full image based on selected feature subsets. A weighted majority voting strategy classified a sample as tumor or normal. Using the eight most predictive features ranked by the maximum relevance minimum redundancy and Laplacian scores methods has achieved a sample classification accuracy of 92.4% and 93.0%, respectively. Local binary pattern alone has achieved an accuracy of 90.3%.

Applications of Magnetic Particle Imaging in Biomedicine: Advancements and Prospects

Magnetic particle imaging (MPI) is a novel emerging noninvasive and radiation-free imaging modality that can quantify superparamagnetic iron oxide nanoparticles tracers. The zero endogenous tissue background signal and short image scanning times ensure high spatial and temporal resolution of MPI. In the context of precision medicine, the advantages of MPI provide a new strategy for the integration of the diagnosis and treatment of diseases. In this review, after a brief explanation of the simplified theory and imaging system, we focus on recent advances in the biomedical application of MPI, including vascular structure and perfusion imaging, cancer imaging, the MPI guidance of magnetic fluid hyperthermia, the visual monitoring of cell and drug treatments, and intraoperative navigation. We finally optimize MPI in terms of the system and tracers, and present future potential biomedical applications of MPI.

Nuclear‐medicine probes: where we are and where we are going

Nuclear medicine probes turned into the key for the identification and precise location of sentinel lymph nodes and other occult lesions (i.e., tumors) by using the systemic administration of radiotracers. Intraoperative nuclear probes are key in the surgical management of some malignancies as well as in the determination of positive surgical margins, thus reducing the extent and potential surgery morbidity.

Depending on their application, nuclear probes are classified into two main categories, namely, counting and imaging. Although counting probes present a simple design, are handheld (to be moved rapidly), and provide only acoustic signals when detecting radiation, imaging probes, also known as cameras, are more hardware‐complex and also able to provide images but at the cost of an increased intervention time as displacing the camera has to be done slowly.

This review article begins with an introductory section to highlight the relevance of nuclear‐based probes and their components as well as the main differences between ionization‐ (semiconductor) and scintillation‐based probes. Then, the most significant performance parameters of the probe are reviewed (i.e., sensitivity, contrast, count rate capabilities, shielding, energy, and spatial resolution), as well as the different types of probes based on the target radiation nature, namely: gamma (γ), beta (β) (positron and electron), and Cherenkov. Various available intraoperative nuclear probes are finally compared in terms of performance to discuss the state‐of‐the‐art of nuclear medicine probes.

The manuscript concludes by discussing the ideal probe design and the aspects to be considered when selecting nuclear‐medicine probes.

Progress on deep learning in digital pathology of breast cancer: a narrative review

BACKGROUND AND OBJECTIVE

Pathology is the gold standard criteria for breast cancer diagnosis and has important guiding value in formulating the clinical treatment plan and predicting the prognosis. However, traditional microscopic examinations of tissue sections are time consuming and labor intensive, with unavoidable subjective variations. Deep learning (DL) can evaluate and extract the most important information from images with less need for human instruction, providing a promising approach to assist in the pathological diagnosis of breast cancer. To provide an informative and up-to-date summary on the topic of DL-based diagnostic systems for breast cancer pathology image analysis and discuss the advantages and challenges to the routine clinical application of digital pathology.

METHODS

A PubMed search with keywords ("breast neoplasm" or "breast cancer") and ("pathology" or "histopathology") and ("artificial intelligence" or "deep learning") was conducted. Relevant publications in English published from January 2000 to October 2021 were screened manually for their title, abstract, and even full text to determine their true relevance. References from the searched articles and other supplementary articles were also studied.

KEY CONTENT AND FINDINGS

DL-based computerized image analysis has obtained impressive achievements in breast cancer pathology diagnosis, classification, grading, staging, and prognostic prediction, providing powerful methods for faster, more reproducible, and more precise diagnoses. However, all artificial intelligence (AI)-assisted pathology diagnostic models are still in the experimental stage. Improving their economic efficiency and clinical adaptability are still required to be developed as the focus of further researches.

CONCLUSIONS

Having searched PubMed and other databases and summarized the application of DL-based AI models in breast cancer pathology, we conclude that DL is undoubtedly a promising tool for assisting pathologists in routines, but further studies are needed to realize the digitization and automation of clinical pathology.

Laser desorption tissue imaging with Differential Mobility Spectrometry

Pathological gross examination of breast carcinoma samples is sometimes laborious. A tissue pre-mapping method could indicate neoplastic areas to the pathologist and enable focused sampling. Differential Mobility Spectrometry (DMS) is a rapid and affordable technology for complex gas mixture analysis. We present an automated tissue laser analysis system for imaging approaches (iATLAS), which utilizes a computer-controlled laser evaporator unit coupled with a DMS gas analyzer. The system is demonstrated in the classification of porcine tissue samples and three human breast carcinomas. Tissue samples from eighteen landrace pigs were classified with the system based on a pre-designed matrix (spatial resolution 1-3 mm). The smoke samples were analyzed with DMS, and tissue classification was performed with several machine learning approaches. Porcine skeletal muscle (n = 1030), adipose tissue (n = 1329), normal breast tissue (n = 258), bone (n = 680), and liver (n = 264) were identified with 86% cross-validation (CV) accuracy with a convolutional neural network (CNN) model. Further, a panel tissue that comprised all five tissue types was applied as an independent validation dataset. In this test, 82% classification accuracy with CNN was achieved. An analogous procedure was applied to demonstrate the feasibility of iATLAS in breast cancer imaging according to 1) macroscopically and 2) microscopically annotated data with 10-fold CV and SVM (radial kernel). We reached a classification accuracy of 94%, specificity of 94%, and sensitivity of 93% with the macroscopically annotated data from three breast cancer specimens. The microscopic annotation was applicable to two specimens. For the first specimen, the classification accuracy was 84% (specificity 88% and sensitivity 77%). For the second, the classification accuracy was 72% (specificity 88% and sensitivity 24%). This study presents a promising method for automated tissue imaging in an animal model and lays foundation for breast cancer imaging.

Finite Element Modeling of Quantitative Ultrasound Analysis of the Surgical Margin of Breast Tumor

Ultrasound is commonly used as an imaging tool in the medical sector. Compared to standard ultrasound imaging, quantitative ultrasound analysis can provide more details about a material microstructure. In this study, quantitative ultrasound analysis was conducted through computational modeling to detect various breast duct pathologies in the surgical margin tissue. Both pulse-echo and pitch-catch methods were evaluated for a high-frequency (22–41 MHz) ultrasound analysis. The computational surgical margin modeling was based on various conditions of breast ducts, such as normal duct, ductal hyperplasia, DCIS, and calcification. In each model, ultrasound pressure magnitude variation in the frequency spectrum was analyzed through peak density and mean-peak-to-valley distance (MPVD) values. Furthermore, the spectral patterns of all the margin models were compared to extract more pathology-based information. For the pitch-catch mode, only peak density provided a trend in relation to different duct pathologies. For the pulse-echo mode, only the MPVD was able to do that. From the spectral comparison, it was found that overall pressure magnitude, spectral variation, peak pressure magnitude, and corresponding frequency level provided helpful information to differentiate various pathologies in the surgical margin.

Is Real-Time Microscopy on the Horizon? A Brief Review of the Potential Future Directions in Clinical Breast Tumor Microscopy Implementation

We will briefly review the current paradigm and some recent developments in the area of clinical breast microscopy, highlighting several promising commercially available, and research-based platforms. Confocal microscopy (reflectance, fluorescence, and spectrally encoded), optical coherence tomography (wide field and full field), stereomicroscopy, open-top light sheet microscopy, microscopy with ultraviolet surface excitation, nonlinear microscopy, Raman scattering microscopy, photoacoustic microscopy, and needle microendoscopy will be discussed. Non-microscopic methods for breast pathology assessment are beyond the scope of this review. These microscopic technologies have to varying degrees the potential for transforming breast cancer care, but in order for any of these to be integrated into clinical practice there are several hurdles to overcome. In our review we will focus on what needs to be done in order for the commercially available technologies to become more established, what the technologies in the research domain need to do in order to reach the commercial realm; and finally, what the field of breast pathology might look like if these technologies were to be widely adopted.

Improved automated early detection of breast cancer based on high resolution 3D micro-CT microcalcification images

Background

The detection of suspicious microcalcifications on mammography represents one of the earliest signs of a malignant breast tumor. Assessing microcalcifications’ characteristics based on their appearance on 2D breast imaging modalities is in many cases challenging for radiologists. The aims of this study were to: (a) analyse the association of shape and texture properties of breast microcalcifications (extracted by scanning breast tissue with a high resolution 3D scanner) with malignancy, (b) evaluate microcalcifications’ potential to diagnose benign/malignant patients.

Methods

Biopsy samples of 94 female patients with suspicious microcalcifications detected during a mammography, were scanned using a micro-CT scanner at a resolution of 9 μm. Several preprocessing techniques were applied on 3504 extracted microcalcifications. A high amount of radiomic features were extracted in an attempt to capture differences among microcalcifications occurring in benign and malignant lesions. Machine learning algorithms were used to diagnose: (a) individual microcalcifications, (b) samples. For the samples, several methodologies to combine individual microcalcification results into sample results were evaluated.

Results

We could classify individual microcalcifications with 77.32% accuracy, 61.15% sensitivity and 89.76% specificity. At the sample level diagnosis, we achieved an accuracy of 84.04%, sensitivity of 86.27% and specificity of 81.39%.

Conclusions

By studying microcalcifications’ characteristics at a level of details beyond what is currently possible by using conventional breast imaging modalities, our classification results demonstrated a strong association between breast microcalcifications and malignancies. Microcalcification’s texture features extracted in transform domains, have higher discriminating power to classify benign/malignant individual microcalcifications and samples compared to pure shape-features.

Information entropy of quantitative chemometric endogenous fluorescence improves photonic lung cancer diagnosis

Quantitative chemometric widefield endogenous fluorescence microscopy (CFM) maps the endogenous absolute chromophore concentration and spatial distribution in cells and tissue sections label-free from fluorescence color images under broadband excitation and detection. By quantifying the endogenous chromophores, including tryptophan, elastin, reduced nicotinamide adenine dinucleotide [NAD(P)H], and flavin adenine dinucleotide (FAD), CFM reveals the biochemical environment and subcellular structure. Here we show that the chromophore information entropy, marking its spatial distribution pattern of quantitative chemometric endogenous fluorescence at the microscopic scale, improves photonic lung cancer diagnosis with independent diagnostic power to the cellular metabolism biomarker. NAD(P)H and FAD's information entropy is found to decrease from normal to perilesional to cancerous tissue, whereas the information entropy for the redox ratios [FAD/tryptophan and FAD/NAD(P)H] is smaller for the normal tissue than both perilesional and cancerous tissue. CFM imaging of the specimen's inherent biochemical and structural properties eliminates the dependence on measurement details and facilitates robust, accurate diagnosis. The synergy of quantifying absolute chromophore concentration and information entropy achieves high accuracies for a three-class classification of lung tissue into normal, perilesional, and cancerous ones and a three-class classification of lung cancers into grade 1, grade 2, and grade 3 using a support vector machine, outperforming the chromophore concentration biomarkers.

Application of Intraoperative Mass Spectrometry and Data Analytics for Oncological Margin Detection, A Review

OBJECTIVE

A common phase of early-stage oncological treatment is the surgical resection of cancerous tissue. The presence of cancer cells on the resection margin, referred to as positive margin, is correlated with the recurrence of cancer and may require re-operation, negatively impacting many facets of patient outcomes. There exists a significant gap in the surgeons ability to intraoperatively delineate between tissues. Mass spectrometry methods have shown considerable promise as intraoperative tissue profiling tools that can assist with the complete resection of cancer. To do so, the vastness of the information collected through these modalities must be digested, relying on robust and efficient extraction of insights through data analysis pipelines.

METHODS

We review clinical mass spectrometry literature and prioritize intraoperatively applied modalities. We also survey the data analysis methods employed in these studies.

RESULTS

Our review outlines the advantages and shortcomings of mass spectrometry imaging and point-based tissue probing methods. For each modality, we identify statistical, linear transformation and machine learning techniques that demonstrate high performance in classifying cancerous tissues across several organ systems. A limited number of studies presented results captured intraoperatively.

CONCLUSION

Through continued research of data centric techniques, like mass spectrometry, and the development of robust analysis approaches, intraoperative margin assessment is becoming feasible.

SIGNIFICANCE

By establishing the relatively short history of mass spectrometry techniques applied to surgical studies, we hope to inform future applications and aid in the selection of suitable data analysis frameworks for the development of intraoperative margin detection technologies.

Fundamentals and developments in fluorescence-guided cancer surgery

Fluorescence-guided surgery using tumour-targeted imaging agents has emerged over the past decade as a promising and effective method of intraoperative cancer detection. An impressive number of fluorescently labelled antibodies, peptides, particles and other molecules related to cancer hallmarks have been developed for the illumination of target lesions. New approaches are being implemented to translate these imaging agents into the clinic, although only a few have made it past early-phase clinical trials. For this translational process to succeed, target selection, imaging agents and their related detection systems and clinical implementation have to operate in perfect harmony to enable real-time intraoperative visualization that can benefit patients. Herein, we review key aspects of this imaging cascade and focus on imaging approaches and methods that have helped to shed new light onto the field of intraoperative fluorescence-guided cancer surgery with the singular goal of improving patient outcomes.

Proof of concept for the sapphire scalpel combining tissue dissection and optical diagnosis

OBJECTIVES

The development of compact diagnostic probes and instruments with an ability to direct access to organs and tissues and integration of these instruments into surgical workflows is an important task of modern physics and medicine. The need for such tools is essential for surgical oncology, where intraoperative visualization and demarcation of tumor margins define further prognosis and survival of patients. In this paper, the possible solution for this intraoperative imaging problem is proposed and its feasibility to detect tumorous tissue is studied experimentally.

METHODS

For this aim, the sapphire scalpel was developed and fabricated using the edge-defined film-fed growth technique aided by mechanical grinding, polishing, and chemical sharpening of the cutting edge. It possesses optical transparency, mechanical strength, chemical inertness, and thermal resistance alongside the presence of the as-grown hollow capillary channels in its volume for accommodating optical fibers. The rounding of the cutting edge exceeds the same for metal scalpels and can be as small as 110 nm. Thanks to these features, sapphire scalpel combines tissue dissection with light delivering and optical diagnosis. The feasibility for the tumor margin detection was studied, including both gelatin-based tissue phantoms and ex vivo freshly excised specimens of the basal cell carcinoma from humans and the glioma model 101.8 from rats. These tumors are commonly diagnosed either non-invasively or intraoperatively using different modalities of fluorescence spectroscopy and imaging, which makes them ideal candidates for our feasibility test. For this purpose, fiber-based spectroscopic measurements of the backscattered laser radiation and the fluorescence signals were carried out in the visible range.

RESULTS

Experimental studies show the feasibility of the proposed sapphire scalpel to provide a 2-mm-resolution of the tumor margins' detection, along with an ability to distinguish the tumor invasion region, which results from analysis of the backscattered optical fields and the endogenous or exogenous fluorescence data.

CONCLUSIONS

Our findings justified a strong potential of the sapphire scalpel for surgical oncology. However, further research and engineering efforts are required to optimize the sapphire scalpel geometry and the optical diagnosis protocols to meet the requirements of oncosurgery, including diagnosis and resection of neoplasms with different localizations and nosologies.

Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures

High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e-11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e-14). Extending the radiomics approach to high-dimensional optical data-termed "optomics" in this study-offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.

The Impact of Temporal Variation in Indocyanine Green Administration on Tumor Identification During Fluorescence Guided Breast Surgery

BACKGROUND

On average, 21% of women in the USA treated with Breast Conserving Surgery (BCS) undergo a second operation because of close positive margins. Tumor identification with fluorescence imaging could improve positive margin rates through demarcating location, size, and invasiveness of tumors. We investigated the technique's diagnostic accuracy in detecting tumors during BCS using intravenous indocyanine green (ICG) and a custom-built fluorescence camera system.

METHODS

In this single-center prospective clinical study, 40 recruited BCS patients were sub-categorized into two cohorts. In the first 'enhanced permeability and retention' (EPR) cohort, 0.25 mg/kg ICG was injected ~ 25 min prior to tumor excision, and in the second 'angiography' cohort, ~ 5 min prior to tumor excision. Subsequently, an in-house imaging system was used to image the tumor in situ prior to resection, ex vivo following resection, the resection bed, and during grossing in the histopathology laboratory to compare the technique's diagnostic accuracy between the cohorts.

RESULTS

The two cohorts were matched in patient and tumor characteristics. The majority of patients had invasive ductal carcinoma with concomitant ductal carcinoma in situ. Tumor-to-background ratio (TBR) in the angiography cohort was superior to the EPR cohort (TBR = 3.18 ± 1.74 vs 2.10 ± 0.92 respectively, p = 0.023). Tumor detection reached sensitivity and specificity scores of 0.82 and 0.93 for the angiography cohort and 0.66 and 0.90 for the EPR cohort, respectively (p = 0.1051 and p = 0.9099).

DISCUSSION

ICG administration timing during the angiography phase compared with the EPR phase improved TBR and diagnostic accuracy. Future work will focus on image pattern analysis and adaptation of the camera system to targeting fluorophores specific to breast cancer.

High-Resolution Full-3D Specimen Imaging for Lumpectomy Margin Assessment in Breast Cancer

BACKGROUND

Two-dimensional (2D) specimen radiography (SR) and tomosynthesis (DBT) for breast cancer yield data that lack high-depth resolution. A volumetric specimen imager (VSI) was developed to provide full-3D and thin-slice cross-sectional visualization at a 360° view angle. The purpose of this prospective trial was to compare VSI, 2D SR, and DBT interpretation of lumpectomy margin status with the final pathologic margin status of breast lumpectomy specimens.

METHODS

The study enrolled 200 cases from two institutions. After standard imaging and interpretation was performed, the main lumpectomy specimen was imaged with the VSI device. Image interpretation was performed by three radiologists after surgery based on VSI, 2D SR, and DBT. A receiver operating characteristic (ROC) curve was created for each method. The area under the curve (AUC) was computed to characterize the performance of the imaging method interpreted by each user.

RESULTS

From 200 lesions, 1200 margins were interpreted. The AUC values of VSI for the three radiologists were respectively 0.91, 0.90, and 0.94, showing relative improvement over the AUCs of 2D SR by 54%, 13%, and 40% and DBT by 32% and 11%, respectively. The VSI has sensitivity ranging from 91 to 94%, specificity ranging from 81 to 85%, a positive predictive value ranging from 25 to 30%, and a negative predicative value of 99%.

CONCLUSIONS

The ROC curves of the VSI were higher than those of the other specimen imaging methods. Full-3D specimen imaging can improve the correlation between the main lumpectomy specimen margin status and surgical pathology. The findings from this study suggest that using the VSI device for intraoperative margin assessment could further reduce the re-excision rates for women with malignant disease.

Accuracy of cancer diagnostic probe for intra-surgical checking of cavity side margins in neoadjuvant breast cancer cases: A human model study

BACKGROUND

Background Recently, a real-time system, named cancer diagnostic probe (CDP), has been developed to diagnose the presence of pre-neoplastic/neoplastic cells in breast cavity side margins. Detecting mechanism is real-time determination of the ROS/H₂ O₂ released from cancer or atypical cells, through reverse Warburg effect and hypoxia glycolysis pathways.

AIMS

Here, we designed a human model study based on real-time checking of 387 internal margins (IM) from 39 neoadjuvant breast cancer cases by CDP. MATERIALS & METHODS: Each lesion was checked by entered needle sensor and electrical scores were recorded. The permanent pathology result of each tested lesion was our gold standard to evaluate CDP scoring. CDP results were compared with permanent pathology of tumour side margins (as a conventional margin evaluation procedure).

RESULTS

Results showed that the sensitivity of CDP in scoring the cavity side margins of those cases is 91%. A total of 18 involved IM which had been detected by CDP were declared as free margins in pathology section of tumour side samples. Just five involved IM were missed by CDP.

DISCUSSIONS

Such sensitivity revealed that metabolism based (here: hypoxia glycolysis) tracing of cancer cells show distinct electrochemical responses between clear and involved cavity side margin evaluation.

CONCLUSION

This human study showed the promising role of CDP to achieve clear margins after BCS of neoadjuvant cases.

Using a mobile device for margin assessment of specimen mammography in breast-conserving surgery

To compare the performance of margin assessment of specimen mammography (SM) in patients with breast-conserving surgery (BCS) on mobile devices and 5-megapixel (5M) thin film transistor liquid crystal display (TFT-LCD) monitors based on the safety margin for pathologic results.This retrospective study was approved by the institutional review board, and the requirement for informed consent was waived. A total of 105 consecutive breast cancer SM samples from 104 women who underwent BCS were included in the study. The SM were independently reviewed by two radiologists using mobile devices and by two additional radiologists using 5M TFT-LCD monitor. Each reader was asked to measure the shortest distance between the lesion and the lesion margin. The interpretation time was recorded. The sensitivity, specificity, and interobserver agreement were analyzed.In total, 19% (20/105) breast specimens had a positive surgical margin (<1 mm). The mean absolute difference from the pathologic margin was 0.60 ± 0.57 cm and 0.54 ± 0.47 cm using the 5 M TFT-LCD monitor and the mobile device, respectively (without any statistical significance, P = .273). The mean interpretation time was 49.5 and 47.6 s for the 5M TFT-LCD monitor and the mobile device, respectively (P = .012). The pooled sensitivity and specificity were 60% and 74% for 5M TFT-LCD monitor, and 60% and 69% for the mobile device (P = 1.00 and P = .190, respectively). The kappa coefficient indicated moderate agreement for both the displays.The diagnostic performance for margin assessment of SM in BCS patients on mobile devices and 5M TFT-LCD monitors are showed not statistically difference. The findings of the study provide evidence of the benefit of the mobile device for SM interpretation in patients who underwent BCS. However, a large sample size study is warranted before using a mobile device for margin evaluation on SM.The mobile device showed comparable diagnostic performance with 5M TFT-LCD monitor in the evaluation of SM margin in patients with BCS and could be used as a display tool for immediate assessment when a dedicated LCD monitor is unavailable.

How accurate is frozen section pathology compared to permanent pathology in detecting involved margins and lymph nodes in breast cancer?

Background

Frozen section (FS) pathology has multiple limitations, and different institutions report variable experiences with the use of FS for diagnosis of tumor involvement. We aimed to compare the FS accuracy with that of permanent pathology (gold standard) regarding marginal involvement and lymph node status using data from the largest breast cancer registry in Iran.

Methods

In this retrospective study, women who had both FS and permanent pathology reports were included. The two pathology reports were cross compared with regard to the involvement of tumor margins and sentinel lymph nodes.

Results

Overall, 2786 patients entered the study. Mean age of patients was 48.96±11.44 years. A total of 1742 margins were analyzed. Accordingly, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FS pathology for detection of involvement of involved margins were 78.49%, 97.63%, 65.1%, and 98.7%, respectively. The accuracy and area under the curve (AUC) for FS pathology were 96.61% and 0.73 (95% CI: 0.64–0.831), respectively.

A total of 1702 sentinel lymph node biopsies were assessed. Sensitivity, specificity, PPV, and NPV, of FS pathology for detection of lymph node involvement, were 87.1%, 98%, 95.5%, and 93.3%, respectively. Accuracy and AUC of FS for diagnosis of involved lymph nodes were 94.1% and 0.926 (95% CI: 0.909–0.942), respectively.

Conclusion

Frozen pathology is a suitable method for identifying involved sentinel lymph nodes in patients with breast cancer, but this method has a less than optimum efficacy for detecting and confirming marginal involvement.

Low-Field NMR Relaxometry for Intraoperative Tumour Margin Assessment in Breast-Conserving Surgery

Simple Summary

Breast cancer is the most diagnosed cancer for women, and clear surgical margins in breast-conserving surgery (BCS) are essential for preventing recurrence. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new tool for intraoperative margin assessment was evaluated. The technique allows the determination of the tissue proton relaxation rates as a function of the applied magnetic field on small tissue samples excised from surgical specimens, at the margins of tumour resection, prior to histopathological analysis. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved. The discriminating ability shown by the relaxometric assay relies mainly on the difference of fat/water content between healthy and tumour cells. The information obtained has the potential to support the surgeon in real-time margin assessment during BCS.

Abstract

As conserving surgery is routinely applied for the treatment of early-stage breast cancer, the need for new technology to improve intraoperative margin assessment has become increasingly important. In this study, the potential of fast field-cycling ¹H-NMR relaxometry as a new diagnostic tool was evaluated. The technique allows the determination of the tissue proton relaxation rates (R₁), as a function of the applied magnetic field, which are affected by the changes in the composition of the mammary gland tissue occurring during the development of neoplasia. The study involved 104 small tissue samples obtained from surgical specimens destined for histopathology. It was found that a good accuracy in margin assessment, i.e., a sensitivity of 92% and a specificity of 85%, can be achieved by using two quantifiers, namely (i) the slope of the line joining the R₁ values measured at 0.02 and 1 MHz and (ii) the sum of the R₁ values measured at 0.39 and 1 MHz. The method is fast, and it does not rely on the expertise of a pathologist or cytologist. The obtained results suggest that a simplified, low-cost, automated instrument might compete well with the currently available tools in margin assessment.

Feasibility of dual-contrast fluorescence imaging of pathological breast tissues

The combination of intravital dye, methylene blue (MB), with molecular cancer marker, pH low insertion peptide (pHLIP) conjugated with fluorescent Alexa532 (Alexa532-pHLIP), was evaluated for enhancing contrast of pathological breast tissue ex vivo. Fresh, thick breast specimens were stained sequentially with Alexa532-pHLIP and aqueous MB and imaged using dual-channel fluorescence microscopy. MB and Alexa532-pHLIP accumulated in the nuclei and cytoplasm of cancer cells, respectively. MB also stained nuclei of normal cells. Some Alexa532-pHLIP fluorescence emission was detected from connective tissue and benign cell membranes. Overall, Alexa532-pHLIP showed high affinity to cancer, while MB highlighted tissue morphology. The results indicate that MB and Alexa532-pHLIP provide complementary information and show promise for the detection of breast cancer.

Intraoperative fluorescence imaging with aminolevulinic acid detects grossly occult breast cancer: a phase II randomized controlled trial

BACKGROUND

Re-excision due to positive margins following breast-conserving surgery (BCS) negatively affects patient outcomes and healthcare costs. The inability to visualize margin involvement is a significant challenge in BCS. 5-Aminolevulinic acid hydrochloride (5-ALA HCl), a non-fluorescent oral prodrug, causes intracellular accumulation of fluorescent porphyrins in cancer cells. This single-center Phase II randomized controlled trial evaluated the safety, feasibility, and diagnostic accuracy of a prototype handheld fluorescence imaging device plus 5-ALA for intraoperative visualization of invasive breast carcinomas during BCS.

METHODS

Fifty-four patients were enrolled and randomized to receive no 5-ALA or oral 5-ALA HCl (15 or 30 mg/kg). Forty-five patients (n = 15/group) were included in the analysis. Fluorescence imaging of the excised surgical specimen was performed, and biopsies were collected from within and outside the clinically demarcated tumor border of the gross specimen for blinded histopathology.

RESULTS

In the absence of 5-ALA, tissue autofluorescence imaging lacked tumor-specific fluorescent contrast. Both 5-ALA doses caused bright red tumor fluorescence, with improved visualization of tumor contrasted against normal tissue autofluorescence. In the 15 mg/kg 5-ALA group, the positive predictive value (PPV) for detecting breast cancer inside and outside the grossly demarcated tumor border was 100.0% and 55.6%, respectively. In the 30 mg/kg 5-ALA group, the PPV was 100.0% and 50.0% inside and outside the demarcated tumor border, respectively. No adverse events were observed, and clinical feasibility of this imaging device-5-ALA combination approach was confirmed.

CONCLUSIONS

This is the first known clinical report of visualization of 5-ALA-induced fluorescence in invasive breast carcinoma using a real-time handheld intraoperative fluorescence imaging device.

TRIAL REGISTRATION

Clinicaltrials.gov identifier NCT01837225 . Registered 23 April 2013.

Nanoparticle Formulation of Indocyanine Green Improves Image-Guided Surgery in a Murine Model of Breast Cancer

PURPOSE

Negative surgical margins (NSMs) have favorable prognostic implications in breast tumor resection surgery. Fluorescence image-guided surgery (FIGS) has the ability to delineate surgical margins in real time, potentially improving the completeness of tumor resection. We have recently developed indocyanine green (ICG)-loaded self-assembled hyaluronic acid (HA) nanoparticles (NanoICG) for solid tumor imaging, which were shown to enhance intraoperative contrast.

PROCEDURES

This study sought to assess the efficacy of NanoICG on completeness of breast tumor resection and post-surgical survival. BALB/c mice bearing iRFP⁺/luciferase⁺ 4T1 syngeneic breast tumors were administered NanoICG or ICG, underwent FIGS, and were compared to bright light surgery (BLS) and sham controls.

RESULTS

NanoICG increased the number of complete resections and improved tumor-free survival. This was a product of improved intraoperative contrast enhancement and the identification of a greater number of small, occult lesions than ICG and BLS. Additionally, NanoICG identified chest wall invasion and predicted recurrence in a model of late-stage breast cancer.

CONCLUSIONS

NanoICG is an efficacious intraoperative contrast agent and could potentially improve surgical outcomes in breast cancer.

Signal to Noise Ratio as a Cross-Platform Metric for Intraoperative Fluorescence Imaging

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.

Concept for using magnetic particle imaging for intraoperative margin analysis in breast-conserving surgery

Breast-conserving surgery (BCS) is a commonly utilized treatment for early stage breast cancers but has relatively high reexcision rates due to post-surgical identification of positive margins. A fast, specific, sensitive, easy-to-use tool for assessing margins intraoperatively could reduce the need for additional surgeries, and while many techniques have been explored, the clinical need is still unmet. We assess the potential of Magnetic Particle Imaging (MPI) for intraoperative margin assessment in BCS, using a passively or actively tumor-targeted iron oxide agent and two hardware devices: a hand-held Magnetic Particle detector for identifying residual tumor in the breast, and a small-bore MPI scanner for quickly imaging the tumor distribution in the excised specimen. Here, we present both hardware systems and demonstrate proof-of-concept detection and imaging of clinically relevant phantoms.

Intraoperative Specimen Ultrasonography: Is It a Reliable Tool for Margin Assessment Following Breast Conservation Surgery for Breast Carcinoma?

BACKGROUND

Assessment of margins after breast conservation surgery is an essential part of management in breast cancer and is important in prognostication of the patient. Various intra-operative techniques like frozen section and imprint cytology are in use to ensure negative margins but have their limitations in the fact that 3D evaluation is not feasible. These lead to false negatives and also are operator dependent. In order to obviate these shortcomings, various centers are using specimen imaging (specimen mammogram and ultrasonography).

AIMS AND OBJECTIVES

1) To evaluate the accuracy of specimen ultrasonography in assessing the margins following breast conservation surgery (BCS). 2) To compare the accuracy of intra-operative specimen ultra-sonography with frozen section for assessment of excision margins following BCS.

MATERIALS AND METHODS

Sixty-two biopsy-proven patients with breast cancer who underwent BCS were included in this prospective study at a tertiary cancer care center. The oriented specimens were evaluated by specimen ultrasonography and later by frozen section. The final histopathology served as the gold standard.

RESULTS

Specimen ultrasonography is found to be superior to frozen section in providing detailed assessment of margins in patients undergoing breast conservation. Specimen ultrasonography was also able to detect additional lesions which might be missed on frozen section, especially the in-situ carcinoma.

Optical scatter imaging of resected breast tumor structures matches the patterns of micro-computed tomography

In patients undergoing breast-conserving surgery (BCS), the rate of re-excision procedures to remove residual tumor left behind after initial resection can be high. Projection radiography, and recently, volumetric x-ray imaging are used to assess margin adequacy, but x-ray imaging lacks contrast between healthy, abnormal benign, and malignant fibrous tissues important for surgical decision making. The purpose of this study was to compare micro-CT and optical scatter imagery of surgical breast specimens and to demonstrate enhanced contrast-to intra-tumoral morphologies and tumor boundary features revealed by optical scatter imaging. A total of 57 breast tumor slices from 57 patients were imagedex vivoby spatially co-registered micro-CT and optical scatter scanning. Optical scatter exhibited greater similarity with micro-CT in 89% (51/57) of specimens versus diffuse white light (DWL) luminance using mutual information (mean ± standard deviation of 0.48 ± 0.21 versus 0.24 ± 0.12;p < 0.001) and in 81% (46/57) of specimens using the Sørensen-Dice coefficient (0.48 ± 0.21 versus 0.33 ± 0.18;p < 0.001). The coefficient of variation (CV) quantified the feature content in each image. Optical scatter exhibited the highest CV in every specimen (optical scatter: 0.70 ± 0.17; diffuse luminance: 0.24 ± 01; micro-CT: 0.15 ± 0.03 for micro-CT;p < 0.001). Optical scatter also exhibited the highest contrast ratios across representative tumor boundaries with adjacent healthy/benign fibrous tissues (1.5-3.7 for optical scatter; 1.0-1.1 for diffuse luminance; 1.0-1.1 for micro-CT). The two main findings from this study were: first, optical scatter contrast was in general similar to the radiological view of the tissue relative to DWL imaging; and second, optical scatter revealed additional features associated with fibrous tissue structures of similar radiodensity that may be relevant to diagnosis. The value of micro-CT lies in its rapid three-dimensional scanning of specimen morphology, and combined with optical scatter imaging with sensitivity to fibrous surface tissues, may be an attractive solution for margin assessment during BCS.

Mesoscopic fluorescence lifetime imaging: Fundamental principles, clinical applications and future directions

Fluorescence lifetime imaging (FLIm) is an optical spectroscopic imaging technique capable of real-time assessments of tissue properties in clinical settings. Label-free FLIm is sensitive to changes in tissue structure and biochemistry resulting from pathological conditions, thus providing optical contrast to identify and monitor the progression of disease. Technical and methodological advances over the last two decades have enabled the development of FLIm instrumentation for real-time, in situ, mesoscopic imaging compatible with standard clinical workflows. Herein, we review the fundamental working principles of mesoscopic FLIm, discuss the technical characteristics of current clinical FLIm instrumentation, highlight the most commonly used analytical methods to interpret fluorescence lifetime data and discuss the recent applications of FLIm in surgical oncology and cardiovascular diagnostics. Finally, we conclude with an outlook on the future directions of clinical FLIm.

Domain adaptation and self-supervised learning for surgical margin detection

PURPOSE

One in five women who undergo breast conserving surgery will need a second revision surgery due to remaining tumor. The iKnife is a mass spectrometry modality that produces real-time margin information based on the metabolite signatures in surgical smoke. Using this modality and real-time tissue classification, surgeons could remove all cancerous tissue during the initial surgery, improving many facets of patient outcomes. An obstacle in developing a iKnife breast cancer recognition model is the destructive, time-consuming and sensitive nature of the data collection that limits the size of the datasets.

METHODS

We address these challenges by first, building a self-supervised learning model from limited, weakly labeled data. By doing so, the model can learn to contextualize the general features of iKnife data from a more accessible cancer type. Second, the trained model can then be applied to a cancer classification task on breast data. This domain adaptation allows for the transfer of learnt weights from models of one tissue type to another.

RESULTS

Our datasets contained 320 skin burns (129 tumor burns, 191 normal burns) from 51 patients and 144 breast tissue burns (41 tumor and 103 normal) from 11 patients. We investigate the effect of different hyper-parameters on the performance of the final classifier. The proposed two-step method performed statistically significantly better than a baseline model (p-value < 0.0001), by achieving an accuracy, sensitivity and specificity of 92%, 88% and 92%, respectively.

CONCLUSION

This is the first application of domain transfer for iKnife REIMS data. We showed that having a limited number of breast data samples for training a classifier can be compensated by self-supervised learning and domain adaption on a set of unlabeled skin data. We plan to confirm this performance by collecting new breast samples and extending it to incorporate other cancer tissues.