Diagnostic Accuracy of Intraoperative Techniques for Margin Assessment in Breast Cancer Surgery: A Meta-analysis

Specimen tomosynthesis provides no additional value to specimen ultrasound in ultrasound-visible malignant breast lesions

BACKGROUND

The aim of this study was to evaluate the accuracy and added value of specimen tomosynthesis (ST) to specimen ultrasound (SUS) in margin assessment of excised breast specimens in breast-conserving therapy for non-palpable US-visible breast lesions.

MATERIALS

Between January 2018 and August 2019, all consecutive patients diagnosed with non-palpable breast cancer visible by ultrasound (US), treated with breast-conserving surgery (BCS) and requiring radiological intraoperative breast specimen assessment, were included in this study. Excised breast specimens were examined with SUS by radiologists blinded to the ST results, and margins smaller than 10 mm were recorded. STs were evaluated retrospectively by experienced radiologists.

RESULTS

A total of 120 specimens were included. SUS showed a statistically significant correlation with pathological margin measurements, while ST did not and provided no additional information. The odds ratios (ORs) for SUS to predict a positive margin was 3.429 (confidence interval (CI) = 0.548-21.432) using a 10-mm cut-off point and 14.182 (CI = 2.134-94.254) using a 5-mm cut-off point, while the OR for ST were 2.528 (CI = 0.400-15.994) and 3.188 (CI = 0.318-31.998), respectively.

CONCLUSIONS

SUS was superior in evaluating intraoperative resection margins of US-visible breast resection specimens when compared to ST. Therefore, ST could be considered redundant in applicable situations.

Prognostic Impact of Surgical Margin Status on Overall Survival of Patients with Early Breast Cancer: A Retrospective Analysis from the Department for Women's Medicine at Charité - University Hospital Berlin

Introduction

The impact of surgical margins on the prognosis of early breast cancer remains uncertain, particularly in the context of modern treatment approaches. This study aimed to investigate whether involved margins after surgery for early breast cancer affect overall survival.

Methods

We conducted a retrospective analysis of 3767 patients who underwent surgery for primary breast cancer or carcinoma in situ between 2006 and 2022 at Charité - University Hospital Berlin. Survival analysis based on margin status and a subsequent multivariate Cox regression analysis were conducted.

Results

With a median follow-up of 72.2 months, clear margins were achieved in 81.4% of patients (n = 3068) after primary surgery, while 16.2% (n = 610) required re-excision. Only 2.4% of patients (n = 89) had definitively involved margins. Margin involvement was more common in hormone receptor-positive disease, lobular subtype, carcinoma in situ, or locally advanced tumors, but less frequent in patients with previous neoadjuvant chemotherapy or triple-negative breast cancer. The Kaplan-Meier survival curves showed a significant separation with worse outcomes for patients with definitive R1 resections. However, the multivariate Cox regression analysis detected no statistically significant difference in overall survival based on margin status. Breast conserving surgery (HR 0.66; 95% CI 0.54-0.81) and HER2 overexpression (HR 0.65; 95% CI 0.48-0.89) were associated with improved survival.

Conclusion

Patients who underwent breast-conserving surgery in our study demonstrated favorable outcomes compared to patients after mastectomy. Although margin status did not significantly affect overall survival, larger multicenter studies are needed to evaluate the prognostic implications of margin involvement in breast cancer treatment in different tumor stages, tumor subtypes and local and systemic treatments.

Novel therapeutic agents in clinical trials: emerging approaches in cancer therapy

Novel therapeutic agents in clinical trials offer a paradigm shift in the approach to battling this prevalent and destructive disease, and the area of cancer therapy is on the precipice of a trans formative revolution. Despite the importance of tried-and-true cancer treatments like surgery, radiation, and chemotherapy, the disease continues to evolve and adapt, making new, more potent methods necessary. The field of cancer therapy is currently witnessing the emergence of a wide range of innovative approaches. Immunotherapy, including checkpoint inhibitors, CAR-T cell treatment, and cancer vaccines, utilizes the host's immune system to selectively target and eradicate malignant cells while minimizing harm to normal tissue. The development of targeted medicines like kinase inhibitors and monoclonal antibodies has allowed for more targeted and less harmful approaches to treating cancer. With the help of genomics and molecular profiling, "precision medicine" customizes therapies to each patient's unique genetic makeup to maximize therapeutic efficacy while minimizing unwanted side effects. Epigenetic therapies, metabolic interventions, radio-pharmaceuticals, and an increasing emphasis on combination therapy with synergistic effects further broaden the therapeutic landscape. Multiple-stage clinical trials are essential for determining the safety and efficacy of these novel drugs, allowing patients to gain access to novel treatments while also furthering scientific understanding. The future of cancer therapy is rife with promise, as the integration of artificial intelligence and big data has the potential to revolutionize early detection and prevention. Collaboration among researchers, and healthcare providers, and the active involvement of patients remain the bedrock of the ongoing battle against cancer. In conclusion, the dynamic and evolving landscape of cancer therapy provides hope for improved treatment outcomes, emphasizing a patient-centered, data-driven, and ethically grounded approach as we collectively strive towards a cancer-free world.

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.

Fluorescence imaging for real-time detection of breast cancer tumors using IV injection of indocyanine green with non-conventional imaging: a systematic review of preclinical and clinical studies of perioperative imaging technologies

BACKGROUND

This review summarizes the available data on the effectiveness of indocyanine green fluorescence imaging (ICG-FI) for real-time detection of breast cancer (BC) tumors with perioperative imaging technologies.

METHODS

PubMed and Scopus databases were exhaustively searched for publications on the use of the real-time ICG-FI evaluation of BC tumors with non-conventional breast imaging technologies.

RESULTS

Twenty-three studies were included in this review. ICG-FI has been used for BC tumor identification in 12 orthotopic animal tumor experiences, 4 studies on animal assessment, and for 7 human clinical applications. The BC tumor-to-background ratio (TBR) was 1.1-8.5 in orthotopic tumor models and 1.4-3.9 in animal experiences. The detection of primary human BC tumors varied from 40% to 100%. The mean TBR reported for human BC varied from 2.1 to 3.7. In two studies evaluating BC surgical margins, good sensitivity (93.3% and 100%) and specificity (60% and 96%) have been reported, with a negative predictive value of ICG-FI to predict margin involvement intraoperatively of 100% in one study.

CONCLUSIONS

The use of ICG-FI as a guiding tool for the real-time identification of BC tumors and for the assessment of tumor boundaries is promising. There is great variability between the studies with regard to timing and dose. Further evidence is needed to assess whether ICG-guided BC surgery may be implemented as a standard of care.

Breast tissue imaging atlas using ultra-fast confocal microscopy to identify cancer lesions

New generation ultra-fast fluorescence confocal microscopy (UFCM) allows to image histological architecture of fresh breast tissue and may be used for ex vivo intraoperative analysis for margin status. The criteria to identify breast tumoral and non-tumoral tissues in UFCM images are still objects of investigation. The objective of the study was to create an atlas of ex vivo UFCM images of breast tissues and breast carcinomas based on the first extensive collection of large field-of-view UFCM breast images. One hundred sixty patients who underwent conserving surgery for breast cancer were included. Their fresh surgical specimens were sliced, stained with acridine orange, and imaged at high resolution with large-field-of-view UFCM. The resulting images were digitally false colored to resemble frozen sections. Each UFCM image was correlated with the corresponding definitive histology. Representative images of normal tissue, inflammation, benign lesions, invasive carcinoma (IC), and ductal carcinoma in situ (DCIS) were collected. A total of 320 large-field images were recorded from 58 IC of no special type, 44 invasive lobular carcinomas, 1 invasive mucinous carcinoma, 47 DCIS, 2 lobular carcinomas in situ, and 8 specimens without cancer. Representative images of the main components of the normal breast and the main types of ICs and DCIS were annotated to establish an UFCM atlas. UFCM enables the imaging of the fresh breast tissue sections. Main morphological criteria defined in traditional histopathology such as tissue architecture and cell features can be applied to describe UFCM images content. The generated atlas of the main normal or tumoral tissue features will support the adoption of this optical technology for the intraoperative examination of breast specimens in clinical practice as it can be used to train physicians on UFCM images and develop artificial intelligence algorithms. Further studies are needed to document rare breast lesions.

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.

Digital breast tomosynthesis versus X-ray of the breast specimen for intraoperative margin assessment: A randomized trial

BACKGROUND

Involved resection margins after breast conserving surgery (BCS) often require a re-operation with increased patient anxiety and risk of impaired cosmesis. We investigated the number of re-operations due to involved resection margins after BCS comparing digital breast tomosynthesis(DBT) with X-ray for intraoperative margin evaluation. Furthermore, we assessed the diagnostic accuracy of these methods to predict histopathological margin status. Finally, we evaluated risk factors for re-operation.

METHODS

In this randomized, non-blinded study, 250 invasive breast cancer patients were randomized (1:1), whereof 241 were analyzed intraoperatively with either DBT (intervention, n = 119) or X-ray (standard, n = 122). Pearson's chi-squared test, Fisher's exact test, t-test, logistic and ordinal regression analysis was used as appropriate.

RESULTS

No difference was found in the number of re-operations between the DBT and X-ray group (16.8 % vs 19.7 %, p = 0.57), or in diagnostic accuracy to predict histopathological margin status (77.5 %, CI: 68.6-84.9 %) and (67.3 %, CI: 57.7-75.9 %), respectively. We evaluated 5 potential risk factors for re-operation: Ductal carcinoma in situ (DCIS) outside tumor, OR = 9.4 (CI: 4.3-20.6, p < 0.001); high mammographic breast density, OR = 6.1 (CI: 1.0-38.1, p = 0.047); non-evaluable margins on imaging, OR = 3.8 (CI: 1.3-10.8, p = 0.016); neoadjuvant chemotherapy, OR = 3.0 (CI: 1.0-8.8, p = 0.048); and T2 tumor-size, OR = 2.6 (CI: 1.0-6.4, p = 0.045).

CONCLUSIONS

No difference was found in the number of re-operations or in diagnostic accuracy to predict histopathological margin status between DBT and X-ray groups. DCIS outside the tumor showed the highest risk of re-operation. Intraoperative methods with improved visualization of DCIS are needed to obtain tumor free margins in BCS.

Accuracy of Ex-vivo Fluorescence Confocal Microscopy in Margin Assessment of Solid Tumors: A Systematic Review

Fluorescence confocal microscopy (FCM) is a novel technology that enables rapid high-resolution digital imaging of non-formalin-fixed tissue specimens and offers real-time positive surgical margin identification. In this systematic review, we evaluated the accuracy metrics of ex vivo FCM for intraoperative margin assessment of different tumor types. A systematic search of MEDLINE via PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus was performed for relevant papers (PROSPERO ID: CRD42022372558). We included 14 studies evaluating four types of microscopes in six different tumor types, including breast, prostate, central nervous system, kidney, bladder, and conjunctival tumors. Using the Quality Assessment of Diagnostic Accuracy Studies tool, we identified a high risk of bias in patient selection (21%) and index test (36%) of the included studies. Overall, we found that FCM has good accuracy metrics in all tumor types, with high sensitivity and specificity (>80%) and almost perfect concordance (>90%) against final pathology results. Despite these promising findings, the quality of the available evidence and bias concerns highlight the need for adequately designed studies to further define the role of ex vivo FCM in replacing the frozen section as the tool of choice for intraoperative margin assessment.

Analysis of Specimen Mammography with Artificial Intelligence to Predict Margin Status

BACKGROUND

Intraoperative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop an artificial intelligence model to predict the pathologic margin status of resected breast tumors using specimen mammography.

METHODS

A dataset of specimen mammography images matched with pathologic margin status was collected from our institution from 2017 to 2020. The dataset was randomly split into training, validation, and test sets. Specimen mammography models pretrained on radiologic images were developed and compared with models pretrained on nonmedical images. Model performance was assessed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC).

RESULTS

The dataset included 821 images, and 53% had positive margins. For three out of four model architectures tested, models pretrained on radiologic images outperformed nonmedical models. The highest performing model, InceptionV3, showed sensitivity of 84%, specificity of 42%, and AUROC of 0.71. Model performance was better among patients with invasive cancers, less dense breasts, and non-white race.

CONCLUSIONS

This study developed and internally validated artificial intelligence models that predict pathologic margins status for partial mastectomy from specimen mammograms. The models' accuracy compares favorably with published literature on surgeon and radiologist interpretation of specimen mammography. With further development, these models could more precisely guide the extent of resection, potentially improving cosmesis and reducing reoperations.

Advancements in Intraoperative Near-Infrared Fluorescence Imaging for Accurate Tumor Resection: A Promising Technique for Improved Surgical Outcomes and Patient Survival

Clear surgical margins for solid tumor resection are essential for preventing cancer recurrence and improving overall patient survival. Complete resection of tumors is often limited by a surgeon's ability to accurately locate malignant tissues and differentiate them from healthy tissue. Therefore, techniques or imaging modalities are required that would ease the identification and resection of tumors by real-time intraoperative visualization of tumors. Although conventional imaging techniques such as positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), or radiography play an essential role in preoperative diagnostics, these cannot be utilized in intraoperative tumor detection due to their large size, high cost, long imaging time, and lack of cancer specificity. The inception of several imaging techniques has paved the way to intraoperative tumor margin detection with a high degree of sensitivity and specificity. Particularly, molecular imaging using near-infrared fluorescence (NIRF) based nanoprobes provides superior imaging quality due to high signal-to-noise ratio, deep penetration to tissues, and low autofluorescence, enabling accurate tumor resection and improved survival rates. In this review, we discuss the recent developments in imaging technologies, specifically focusing on NIRF nanoprobes that aid in highly specific intraoperative surgeries with real-time recognition of tumor margins.

Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types

Pathological histology is the "gold standard" for clinical diagnosis of cancer. Incomplete or excessive sampling of the formalin-fixed excised cancer specimen will result in inaccurate histologic assessment or excessive workload. Conventionally, pathologists perform specimen sampling relying on naked-eye observation, which is subjective and limited by human perception. Precise identification of cancer tissue, size, and margin is challenging, especially for lesions with inconspicuous tumors. To overcome the limits of human eye perception (visible: 400-700 nm) and improve the sampling efficiency, in this study, we propose using a second near-infrared window (NIR-II: 900-1700 nm) hyperspectral imaging (HSI) system to assist specimen sampling on the strength of the verified deep anatomical penetration and low scattering characteristics of the NIR-II optical window. We used selected NIR-II HSI narrow bands to synthesize color images for human eye observation and also applied a machine learning-based algorithm on the complete NIR-II HSI data for automatic tissue classification to assist pathologists in specimen sampling. A total of 92 tumor samples were collected, including 7 types. Sixty-two (62/92) samples were used as the validation set. Five experienced pathologists marked the contour of the cancer tissue on conventional color images by using different methods, and compared it with the "gold standard," showing that NIR-II HSI-assisted methods had significant improvements in determining cancer tissue compared with conventional methods (conventional color image with or without X-ray). The proposed system can be easily integrated into the current workflow, with high imaging efficiency and no ionizing radiation. It may also find applications in intraoperative detection of residual lesions and identification of different tissues.

Cost-Efficacy Analysis of Use of Frozen Section Histology for Margin Assessment During Breast Conservation Surgery in Breast Cancer Patients

BACKGROUND

Margin assessment is an essential component of breast conservation surgery (BCS). Re-excision of infiltrated margin(s) detected on paraffin section histology (PSH) needs reoperation, adding time, inconvenience and cost. Intra-operative assessment of margins using frozen section histology (IFSH) can potentially obviate need for re-operation, thus facilitating one-step oncologically complete BCS.

METHODS

IFSH and PSH reports of consecutive patients undergoing BCS (2010-2020) were reviewed. Accuracy and cost-efficacy of IFSH were assessed, considering PSH as gold standard. Cost of achieving oncologically complete BCS in whole cohort with IFSH (Scenario-A) was calculated and compared using appropriate statistical tests, with hospital costs for the cohort in a hypothetical Scenario-B, where IFSH was presumed not to have been used and all patients with infiltrated margin(s) on PSH would have been re-operated.

RESULTS

Of the 367 patients screened, 39 were excluded due to incomplete IFSH data. Of 328 patients analyzed, 59 (18%) had one or more margins were reported infiltrated on IFSH, managed by re-excision or mastectomy in the same sitting, thus avoiding a reoperation. Additional 8 (2.4%) had involved margins on PSH (False negative IFSH). Significantly higher number of reoperations (p < 0.001) would have been needed in scenario-B. Average cost of the first operation with use of IFSH was Indian Rupees (INR) 25791 which included INR660 as IFSH cost. The average cost of reoperation was INR23724 which could be avoided in 59 (18%) by use of IFSH. The average cost per patient to achieve oncologically complete surgery in scenario A utilizing IFSH was significantly lower (p = 0.001) by INR3101 (11.7%), c.w. that in scenario B. Significant cost-saving with IFSH was maintained in cost-efficacy analysis undertaken with various higher and lower costs assumptions.

CONCLUSIONS

Use of IFSH facilitates one-step oncologically complete BCS in majority of patients and results in considerable cost saving, resulting in avoidance of reoperations, besides preventing patient anxiety and delay in adjuvant treatment.

TRIAL REGISTRATION

Clinical Trials Registry-India (CTRI/2021/08/035896).

Blood flow on ultrasound imaging is a predictor of lump margin status in breast-conserving patients: a retrospective matching study

PURPOSE

This study investigated the relationship between breast ultrasound features and lump margin status in breast-conserving patients.

METHODS

A single-institution database and medical records system were searched to identify patients who had undergone breast-conserving surgery between 2015 and 2022. Patients were divided into case and control groups based on their postoperative margin status, and different matching methods [case-control matching (CCM) and propensity score matching (PSM)] were used to match the cases and controls at a ratio of 1:1.

RESULTS

Before matching, patients with positive margins were more likely to have a tumor with increased blood flow (OR = 2.90, 95% CI 1.83-4.61, p < 0.001) and microcalcifications (OR = 2.22, 95% CI 1.44-3.42, p < 0.001). Among the 83 pairs of CCM subjects, patients with positive margins were prone to increased blood flow (p = 0.007) and crab sign (p = 0.040). In addition, there was a significant difference in blood flow (p = 0.030) among PSM subjects. After adjusting for the unbalanced factors, the same results were obtained.

CONCLUSIONS

Ultrasound blood flow significantly predicts the status of breast-conserving margins, but further studies are required to verify our findings.

Delineation and detection of breast cancer using novel label-free fluorescence

BACKGROUND

Accurate diagnosis of breast cancer (BC) plays a crucial role in clinical pathology analysis and ensuring precise surgical margins to prevent recurrence.

METHODS

Laser-induced fluorescence (LIF) technology offers high sensitivity to tissue biochemistry, making it a potential tool for noninvasive BC identification. In this study, we utilized hyperspectral (HS) imaging data of stimulated BC specimens to detect malignancies based on altered fluorescence characteristics compared to normal tissue. Initially, we employed a HS camera and broadband spectrum light to assess the absorbance of BC samples. Notably, significant absorbance differences were observed in the 440-460 nm wavelength range. Subsequently, we developed a specialized LIF system for BC detection, utilizing a low-power blue laser source at 450 nm wavelength for ten BC samples.

RESULTS

Our findings revealed that the fluorescence distribution of breast specimens, which carries molecular-scale structural information, serves as an effective marker for identifying breast tumors. Specifically, the emission at 561 nm exhibited the greatest variation in fluorescence signal intensity for both tumor and normal tissue, serving as an optical predictive biomarker. To enhance BC identification, we propose an advanced image classification technique that combines image segmentation using contour mapping and K-means clustering (K-mc, K = 8) for HS emission image data analysis.

CONCLUSIONS

This exploratory work presents a potential avenue for improving "in-vivo" disease characterization using optical technology, specifically our LIF technique combined with the advanced K-mc approach, facilitating early tumor diagnosis in BC.

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.

Instrumental in Surgery: A Narrative Review on Energy-based Surgical Cutting Devices and Surgical Smoke

OBJECTIVE

To provide an informed understanding of existing energy-based surgical cutting technologies and aerosol-generating surgical procedures. We provide a perspective on the future innovation and research potential in this space for the benefit of surgeons, physicians, engineers, and researchers alike.

BACKGROUND

Surgery is a treatment for many medical conditions, the success of which depends on surgical cutting instruments that enable surgeons to conduct surgical procedures for tissue cutting and manipulation. Energy-based surgical cutting tools improve accuracy and limit unnecessary destruction of healthy tissues and cells, but can generate surgical smoke and aerosols, which can be handled using surgical smoke evacuation technology.

METHODS

A narrative review was conducted to explore existing literature describing the history and development of energy-based surgical instruments, their mechanisms of action, aerosol-generating medical procedures, surgical smoke and aerosols from aerosol-generating medical procedures, and the recommended mitigation strategies, as well as research on rapid biological tissue analyzing devices to date.

CONCLUSIONS

Smoke evacuation technology may provide diagnostic information regarding tissue pathology, which could eliminate health concerns and revolutionize surgical accuracy. However, further research into surgical smoke is required to quantify the measurable risk to health it poses, the cutting conditions, under which it is generated and to develop advanced diagnostic approaches using this information.

Detection of breast cancer cells by a near-infrared fluorescent probe targeting mitochondrial viscosity

Monitoring abnormal viscosity in biological systems is important for basic research and clinical applications. Fluorescence imaging technology is adaptable for the visualization of tumor tissues due to its comprehensive features. However, fluorescence detection of intracellular viscosity in clinical samples remains challenging. We developed a promising near-infrared fluorescent probe, M556, for viscosity measurement. M556, which targets mitochondria, was successfully applied to monitor the mitochondrial viscosity in living cells. Furthermore, M556 was demonstrated to effectively discriminate tumors from normal tissues in a mouse tumor model and in clinical specimens from breast cancer patients, thus indicating the potential perioperative use of this probe by clinicians to assist with biopsy procedures.

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.

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.

Conventional specimen radiography in breast-conserving therapy: a useful tool for intraoperative margin assessment after neoadjuvant therapy?

PURPOSE

A previous study in our breast unit showed that the diagnostic accuracy of intraoperative specimen radiography and its potential to reduce second surgeries in a cohort of patients treated with neoadjuvant chemotherapy were low, which questions the routine use of Conventional specimen radiography (CSR) in this patient group. This is a follow-up study in a larger cohort to further evaluate these findings.

METHODS

This retrospective study included 376 cases receiving breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. CSR was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions.

RESULTS

362 patients with 2172 margins were assessed. The prevalence of positive margins was 102/2172 (4.7%). CSR had a sensitivity of 37.3%, a specificity of 85.6%, a positive predictive value (PPV) of 11.3%, and a negative predictive value (NPV) of 96.5%. The rate of secondary procedures was reduced from 75 to 37 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 10. In the subgroup of patients with clinical complete response (cCR), the prevalence of positive margins was 38/1002 (3.8%), PPV was 6.5% and the NNT was 34.

CONCLUSION

This study confirms our previous finding that the rate of secondary surgeries cannot be significantly reduced by CSR-guided intraoperative re-excisions in cases with cCR after NACT. The routine use CSR after NACT is questionable, and alternative tools of intraoperative margin assessment should be evaluated.

Diagnostic accuracy of intraoperative margin assessment techniques in surgery for head and neck squamous cell carcinoma: A meta-analysis

BACKGROUND

Positive margins following head and neck squamous cell carcinoma (HNSCC) surgery lead to significant morbidity and mortality. Existing Intraoperative Margin Assessment (IMA) techniques are not widely used due to limitations in sampling technique, time constraints and resource requirements. We performed a meta-analysis of the diagnostic performance of existing IMA techniques in HNSCC, providing a benchmark against which emerging techniques may be judged.

METHODS

The study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Studies were included if they reported diagnostic metrics of techniques used during HNSCC surgery, compared with permanent histopathology. Screening, manuscript review and data extraction was performed by multiple independent observers. Pooled sensitivity and specificity were estimated using the bivariate random effects model.

RESULTS

From an initial 2344 references, 35 studies were included for meta-analysis. Sensitivity (Sens), specificity (Spec), diagnostic odds ratio (DOR) and area under the receiver operating characteristic curve (AUROC) were calculated for each group (n, Sens, Spec, DOR, AUROC): frozen section = 13, 0.798, 0.991, 309.8, 0.976; tumour-targeted fluorescence (TTF) = 5, 0.957, 0.827, 66.4, 0.944; optical techniques = 10, 0.919, 0.855, 58.9, 0.925; touch imprint cytology = 3, 0.925, 0.988, 51.1, 0.919; topical staining = 4, 0.918, 0.759, 16.4, 0.833.

CONCLUSIONS

Frozen section and TTF had the best diagnostic performance. Frozen section is limited by sampling error. TTF shows promise but involves administration of a systemic agent. Neither is currently in widespread clinical use. Emerging techniques must demonstrate competitive diagnostic accuracy whilst allowing rapid, reliable, cost-effective results.

Simultaneous Detection of Multiple Tumor-targeted Gold Nanoparticles in HER2-Positive Breast Tumors Using Optoacoustic Imaging

Purpose To develop optoacoustic, spectrally distinct, actively targeted gold nanoparticle-based near-infrared probes (trastuzumab [TRA], TRA-Aurelia-1, and TRA-Aurelia-2) that can be individually identifiable at multispectral optoacoustic tomography (MSOT) of human epidermal growth factor receptor 2 (HER2)-positive breast tumors. Materials and Methods Gold nanoparticle-based near-infrared probes (Aurelia-1 and 2) that are optoacoustically active and spectrally distinct for simultaneous MSOT imaging were synthesized and conjugated to TRA to produce TRA-Aurelia-1 and 2. Freshly resected human HER2-positive (n = 6) and HER2-negative (n = 6) triple-negative breast cancer tumors were treated with TRA-Aurelia-1 and TRA-Aurelia-2 for 2 hours and imaged with MSOT. HER2-expressing DY36T2Q cells and HER2-negative MDA-MB-231 cells were implanted orthotopically into mice (n = 5). MSOT imaging was performed 6 hours following the injection, and the Friedman test was used for analysis. Results TRA-Aurelia-1 (absorption peak, 780 nm) and TRA-Aurelia-2 (absorption peak, 720 nm) were spectrally distinct. HER2-positive human breast tumors exhibited a significant increase in optoacoustic signal following TRA-Aurelia-1 (28.8-fold) or 2 (29.5-fold) (P = .002) treatment relative to HER2-negative tumors. Treatment with TRA-Aurelia-1 and 2 increased optoacoustic signals in DY36T2Q tumors relative to those in MDA-MB-231 controls (14.8-fold, P < .001; 20.8-fold, P < .001, respectively). Conclusion The study demonstrates that TRA-Aurelia 1 and 2 nanoparticles operate as a spectrally distinct HER2 breast tumor-targeted in vivo optoacoustic agent. Keywords: Molecular Imaging, Nanoparticles, Photoacoustic Imaging, Breast Cancer Supplemental material is available for this article. © RSNA, 2023.

Emerging Technology for Intraoperative Margin and Assisting in Post-Surgery tissue diagnostic for Future Breast-Conserving

INTRODUCTION

Tissue-preserving surgery is utilized progressively in cancer therapy, where a clear surgical margin is critical to avoid cancer recurrence, specifically in breast cancer (BC) surgery. The Intraoperative pathologic approaches that rely on tissue segmenting and staining have been recognized as the ground truth for BC diagnosis. Nevertheless, these methods are constrained by its complication and timewasting for tissue preparation.

OBJECTIVE

We present a non-invasive optical imaging system incorporating a hyperspectral (HS) camera to discriminate between cancerous and non-cancerous tissues in ex-vivo breast specimens, which could be an intraoperative diagnostic technique to aid surgeons during surgery and later a valuable tool to assist pathologists.

METHODS

We have established a hyperspectral Imaging (HSI) system comprising a push-broom HS camera at wavelength 380∼1050 nm with source light 390∼980 nm. We have measured the investigated samples' diffuse reflectance (R_d), fixed on slides from 30 distinct patients incorporating mutually normal and ductal carcinoma tissue. The samples were divided into two groups, stained tissues during the surgery (control group) and unstained samples (test group), both captured with the HSI system in the visible and near-infrared (VIS-NIR) range. Then, to address the problem of the spectral nonuniformity of the illumination device and the influence of the dark current, the radiance data were normalized to yield the radiance of the specimen and neutralize the intensity effect to focus on the spectral reflectance shift for each tissue. The selection of the threshold window from the measured R_d is carried out by exploiting the statistical analysis by calculating each region's mean and standard deviation. Afterward, we selected the optimum spectral images from the HS data cube to apply a custom K-means algorithm and contour delineation to identify the regular districts from the BC regions.

RESULTS

We noticed that the measured spectral R_d for the malignant tissues of the investigated case studies versus the reference source light varies regarding the cancer stage, as sometimes the R_d is higher for the tumor or vice versa for the normal tissue. Later, from the analysis of the whole samples, we found that the most appropriate wavelength for the BC tissues was 447 nm, which was highly reflected versus the normal tissue. However, the most convenient one for the normal tissue was at 545 nm with high reflection versus the BC tissue. Finally, we implement a moving average filter for noise reduction and a custom K-means clustering algorithm on the selected two spectral images (447, 551 nm) to identify the various regions and effectively-identified spectral tissue variations with a sensitivity of 98.95%, and specificity of 98.44%. A pathologist later confirmed these outcomes as the ground truth for the tissue sample investigations.

CONCLUSIONS

The proposed system could help the surgeon and the pathologist identify the cancerous tissue margins from the non-cancerous tissue with a non-invasive, rapid, and minimum time method achieving high sensitivity up to 98.95%.

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.

Computer Vision Analysis of Specimen Mammography to Predict Margin Status

Intra-operative specimen mammography is a valuable tool in breast cancer surgery, providing immediate assessment of margins for a resected tumor. However, the accuracy of specimen mammography in detecting microscopic margin positivity is low. We sought to develop a deep learning-based model to predict the pathologic margin status of resected breast tumors using specimen mammography. A dataset of specimen mammography images matched with pathology reports describing margin status was collected. Models pre-trained on radiologic images were developed and compared with models pre-trained on non-medical images. Model performance was assessed using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). The dataset included 821 images and 53% had positive margins. For three out of four model architectures tested, models pre-trained on radiologic images outperformed domain-agnostic models. The highest performing model, InceptionV3, showed a sensitivity of 84%, a specificity of 42%, and AUROC of 0.71. These results compare favorably with the published literature on surgeon and radiologist interpretation of specimen mammography. With further development, these models could assist clinicians with identifying positive margins intra-operatively and decrease the rate of positive margins and re-operation in breast-conserving surgery.

The impact of intraoperative cavity shaving on re-excision rates in breast-conserving surgery

BACKGROUND AND OBJECTIVES

This trial aimed to investigate the effects of circumferential shaving on reducing the reoperation rates during breast-conserving surgery (BCS).

METHODS

In the study, before 2014, 404 (39.9%) breast cancers (BCs) out of a total of 1012 BCs underwent BCS without intraoperative cavity shaving (ICS) and constituted the no-ICS group. After this date, ICS was added to 608 (60.1%) BCSs (ICS group) and intraoperative margin analysis was not requested from pathologists during these second BCS procedures.

RESULTS

The patient and BC characteristics in the no-ICS and ICS groups were similar. Carcinoma detection at the margin and reoperation rates were 13.9% in the no-ICS group and 7.6% in the ICS group (p = 0.001). No significant difference was detected between patients who underwent BCS with intraoperative frozen section analysis (FSA) and patients who underwent BCS with additional ICS (5.6% vs. 7.6%, p = 0.383).

CONCLUSIONS

ICS decreased the rates of positive margins and reoperations among patients with BCS to an acceptable level compared with intraoperative FSA. It may be concluded that ICS is feasible to achieve BC margin control.

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.

Diagnostic performance of tomosynthesis, digital mammography and a dedicated digital specimen radiography system versus pathological assessment of excised breast lesions

BACKGROUND

The aim of the study was to compare the performance of full-field digital mammography (FFDM), digital breast tomosynthesis and a dedicated digital specimen radiography system (SRS) in consecutive patients, and to compare the margin status of resected lesions versus pathological assessment.

PATIENTS AND METHODS

Resected tissue specimens from consecutive patients who underwent intraoperative breast specimen assessment following wide local excision or oncoplastic breast conservative surgery were examined by FFDM, tomosynthesis and SRS. Two independent observers retrospectively evaluated the visibility of lesions, size, margins, spiculations, calcifications and diagnostic certainty, and chose the best performing method in a blinded manner.

RESULTS

We evaluated 216 specimens from 204 patients. All target malignant lesions were removed with no tumouron-ink. One papilloma had positive microscopic margins and one patient underwent reoperation owing to extensive in situ components. There were no significant differences in measured lesion size among the three methods. However, tomosynthesis was the most accurate modality when compared with the final pathological report. Both observers reported that tomosynthesis had significantly better lesion visibility than SRS and FFDM, which translated into a significantly greater diagnostic certainty. Tomosynthesis was superior to the other two methods in identifying spiculations and calcifications. Both observers reported that tomosynthesis was the best performing method in 76.9% of cases. The interobserver reproducibilities of lesion visibility and diagnostic certainty were high for all three methods.

CONCLUSIONS

Tomosynthesis was superior to SRS and FFDM for detecting and evaluating the target lesions, spiculations and calcifications, and was therefore more reliable for assessing complete excision of breast lesions.

Specimen mammography for intraoperative margin assessment in breast conserving surgery: a meta-analysis

In breast conserving surgery (BCS), specimen mammography is one of the most widely used intraoperative methods of assessing margin status. We performed a meta-analysis to evaluate the diagnostic accuracy of specimen mammography. Literature databases including PubMed, Cochrane Library, Web of Science, and EMBASE were searched prior to Jun 2022. A total of 1967 patients were included from 20 studies. A pooled analysis, heterogeneity testing, threshold effect testing, publication bias analysis, and subgroup analyses were performed from extracted data. The pooled weighted values were a sensitivity of 0.55 (95% confidence interval [CI], 0.47-0.63), a specificity of 0.85 (95% CI, 0.78-0.90), a diagnostic odds ratio of 7 (95% CI, 4-12), and a pooled positive likelihood ratio of 3.7 (95% CI 2.6-5.5). The area under the receiver operator characteristic curve was 0.75 (95% CI 0.71-0.78). In the subgroup analysis, the pooled specificity in the positive margin defined as tumor at margin subgroup was lower than the other positive margin definition subgroup (0.82 [95% CI: 0.71, 0.92] vs. 0.87 [95% CI: 0.80, 0.94], p = 0.01). Our findings indicated that specimen mammography was an accurate intraoperative imaging technique for margin assessment in BCS.

Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery

Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld QME probe, designed to interrogate the surgical cavity, can detect residual cancer directly in the breast cavity in vivo during BCS. In a first-in-human study, 21 BCS patients were scanned in vivo with the QME probe by five surgeons. For validation, protocols were developed to coregister in vivo QME with postoperative histopathology of the resected tissue to assess the capability of QME to identify residual cancer. In four cavity aspects presenting cancer and 21 cavity aspects presenting benign tissue, QME detected elevated stiffness in all four cancer cases, in contrast to low stiffness observed in 19 of the 21 benign cases. The results indicate that in vivo QME can identify residual cancer by directly imaging the surgical cavity, potentially providing a reliable intraoperative solution that can enable more complete cancer excision during BCS.

SIGNIFICANCE

Optical imaging of microscale tissue stiffness enables the detection of residual breast cancer directly in the surgical cavity during breast-conserving surgery, which could potentially contribute to more complete cancer excision.

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.

Uncertainty estimation for margin detection in cancer surgery using mass spectrometry

PURPOSE

Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technology for clinical margin detection. Deployment of REIMS depends on construction of reliable deep learning models that can categorize tissue according to its metabolomic signature. Challenges associated with developing these models include the presence of noise during data acquisition and the variance in tissue signatures between patients. In this study, we propose integration of uncertainty estimation in deep models to factor predictive confidence into margin detection in cancer surgery.

METHODS

iKnife is used to collect 693 spectra of cancer and healthy samples acquired from 91 patients during basal cell carcinoma resection. A Bayesian neural network and two baseline models are trained on these data to perform classification as well as uncertainty estimation. The samples with high estimated uncertainty are then removed, and new models are trained using the clean data. The performance of proposed and baseline models, with different ratios of filtered data, is then compared.

RESULTS

The data filtering does not improve the performance of the baseline models as they cannot provide reliable estimations of uncertainty. In comparison, the proposed model demonstrates a statistically significant improvement in average balanced accuracy (75.2%), sensitivity (74.1%) and AUC (82.1%) after removing uncertain training samples. We also demonstrate that if highly uncertain samples are predicted and removed from the test data, sensitivity further improves to 88.2%.

CONCLUSIONS

This is the first study that applies uncertainty estimation to inform model training and deployment for tissue recognition in cancer surgery. Uncertainty estimation is leveraged in two ways: by factoring a measure of input noise in training the models and by including predictive confidence in reporting the outputs. We empirically show that considering uncertainty for model development can help improve the overall accuracy of a margin detection system using REIMS.

Is Routine Intraoperative Frozen Section Analysis of Sentinel Lymph Nodes Necessary in Every Early-Stage Breast Cancer?

Purpose

Clinical application of the ACOSOG Z0011 trial results allows clinically node-negative breast cancer patients who meet criteria to avoid axillary dissection even when 1–2 sentinel lymph nodes (SLNs) are positive for metastatic disease. Intraoperative frozen section (iFS) analyses of SLNs were thought to reduce re-operation rates despite variable reported sensitivity and possibility of a false negative result. This study evaluated the rate of re-operations prevented by SLN iFS in a tertiary care hospital in Bangkok, Thailand, over a 6-year time-frame.

Patients and Methods

From April 2016 to April 2022, 1284 sentinel lymph node biopsy (SLNB) procedures were performed. Of these, 214 cases were breast-conserving surgery in accordance with the ACOSOG criteria with concomitant usage of iFS. Clinicopathological features of these cases were collected and analyzed. Re-operation rates prevented by the additional intervention were reported.

Results

Only five additional operations were prevented with the usage of 214 iFS. The discordance rate between frozen and permanent sections in terms of presence of metastatic disease and number of total lymph nodes was around 15%. Tumor staging, node staging, Nottingham histologic grading and lymphovascular invasion are significant predictors of SLN metastasis.

Conclusion

iFS results in a very low prevention rate for follow-up ALND in patients with preoperative clinically negative axillary nodes and is associated with a non-negligible discordance rate with permanent sections. Our study suggests iFS may be avoided in most cases of early-stage clinically and radiographically node-negative breast cancer patients. Doing so may reduce surgical costs and total operative time without a significant impact on the overall quality of treatment and standard of care.

Novel rapid intraoperative qualitative tumor detection by a residual convolutional neural network using label-free stimulated Raman scattering microscopy

Determining the presence of tumor in biopsies and the decision-making during resections is often dependent on intraoperative rapid frozen-section histopathology. Recently, stimulated Raman scattering microscopy has been introduced to rapidly generate digital hematoxylin-and-eosin-stained-like images (stimulated Raman histology) for intraoperative analysis. To enable intraoperative prediction of tumor presence, we aimed to develop a new deep residual convolutional neural network in an automated pipeline and tested its validity. In a monocentric prospective clinical study with 94 patients undergoing biopsy, brain or spinal tumor resection, Stimulated Raman histology images of intraoperative tissue samples were obtained using a fiber-laser-based stimulated Raman scattering microscope. A residual network was established and trained in ResNetV50 to predict three classes for each image: (1) tumor, (2) non-tumor, and (3) low-quality. The residual network was validated on images obtained in three small random areas within the tissue samples and were blindly independently reviewed by a neuropathologist as ground truth. 402 images derived from 132 tissue samples were analyzed representing the entire spectrum of neurooncological surgery. The automated workflow took in a mean of 240 s per case, and the residual network correctly classified tumor (305/326), non-tumorous tissue (49/67), and low-quality (6/9) images with an inter-rater agreement of 89.6% (κ = 0.671). An excellent internal consistency was found among the random areas with 90.2% (Cα = 0.942) accuracy. In conclusion, the novel stimulated Raman histology-based residual network can reliably detect the microscopic presence of tumor and differentiate from non-tumorous brain tissue in resection and biopsy samples within 4 min and may pave a promising way for an alternative rapid intraoperative histopathological decision-making tool.

Fabrication of tumor targeting rare-earth nanocrystals for real-time NIR-IIb fluorescence imaging-guided breast cancer precise surgery

The near-infrared fluorescence imaging has been integrated into the operating room to guide tumor resection, potentially reducing the positive margin rates in breast-conserving surgery (BCS). Relative to the widely used first near-infrared fluorescence imaging, imaging in the second near-infrared (NIR-II) region possesses higher contrast and deeper tissue penetration, particularly in the NIR-IIb window, offering many new opportunities for imaging-guided BCS. Here, we fabricated the c(RGDfC) functionalized erbium-based rare-earth nanoparticles (ErNPs@cRGD) with superior optical property in NIR-IIb region. Owing to deeper tissue penetration and efficient tumor targeting, ErNPs@cRGD-based NIR-IIb fluorescence imaging achieved enhanced signal-to-background ratios in tumor visualization, which was able to guide more complete tumor resection, identify multiple microtumors and distinguish malignant lesions from normal tissues in various mice models. Based on these, this NIR-IIb imaging strategy for surgical navigation can significantly reduce positive margin rates and improve prognosis, laying a foundation for the clinical resection of breast cancer.

Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning

We demonstrate a convolutional neural network (CNN) for multi-class breast tissue classification as adipose tissue, benign dense tissue, or malignant tissue, using multi-channel optical coherence tomography (OCT) and attenuation images, and a novel Matthews correlation coefficient (MCC)-based loss function that correlates more strongly with performance metrics than the commonly used cross-entropy loss. We hypothesized that using multi-channel images would increase tumor detection performance compared to using OCT alone. 5,804 images from 29 patients were used to fine-tune a pre-trained ResNet-18 network. Adding attenuation images to OCT images yields statistically significant improvements in several performance metrics, including benign dense tissue sensitivity (68.0% versus 59.6%), malignant tissue positive predictive value (PPV) (79.4% versus 75.5%), and total accuracy (85.4% versus 83.3%), indicating that the additional contrast from attenuation imaging is most beneficial for distinguishing between benign dense tissue and malignant tissue.

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.

Evolution of Frozen Section in Carcinoma Breast: Systematic Review

Background. The frozen section (FS) has been a good technique in surgical management of breast lesions since many years. But complete agreement and cooperation have not been achieved everywhere among surgeons and pathologists especially in the developing countries. FS undergoes continuous criticism due to various shortcomings but continued to be evaluated especially in developing countries. Objectives. This review was conducted to synthesize information on the use of frozen section in carcinoma breast. Data Sources. The MEDLINE database for frozen section since its origin and its implication in recent breast surgery techniques was studied. Study Eligibility Criteria. Sixty-five articles were reviewed with complete analysis on FS in both benign and malignant breast lesions. Study Appraisal and Synthesis Methods. The analysis of frozen section was done as a diagnostic tool in breast lesions, margin status in breast conservative surgery in carcinoma breast, and sentinel lymph node and use of immunohistochemistry for sentinel lymph node FS. Results. It was analysed that the FS gives accurate results in margin status analysis, decreasing rerecurrence. Conclusion. The accuracy of FSA, low recurrence rate, avoidance of reoperation, and good cosmesis are the key points of its use in breast conservative surgery. Its use in sentinel lymph node biopsy (SLNB) is equivocal. However, application of immunohistochemistry on frozen section of SLNB is an evolving trend in today’s era.

Indocyanine green fluorescence image processing techniques for breast cancer macroscopic demarcation

Re-operation due to disease being inadvertently close to the resection margin is a major challenge in breast conserving surgery (BCS). Indocyanine green (ICG) fluorescence imaging could be used to visualize the tumor boundaries and help surgeons resect disease more efficiently. In this work, ICG fluorescence and color images were acquired with a custom-built camera system from 40 patients treated with BCS. Images were acquired from the tumor in-situ, surgical cavity post-excision, freshly excised tumor and histopathology tumour grossing. Fluorescence image intensity and texture were used as individual or combined predictors in both logistic regression (LR) and support vector machine models to predict the tumor extent. ICG fluorescence spectra in formalin-fixed histopathology grossing tumor were acquired and analyzed. Our results showed that ICG remains in the tissue after formalin fixation. Therefore, tissue imaging could be validated in freshly excised and in formalin-fixed grossing tumor. The trained LR model with combined fluorescence intensity (pixel values) and texture (slope of power spectral density curve) identified the tumor's extent in the grossing images with pixel-level resolution and sensitivity, specificity of 0.75 ± 0.3, 0.89 ± 0.2.This model was applied on tumor in-situ and surgical cavity (post-excision) images to predict tumor presence.

Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer

Histopathological diagnosis is the ultimate method of attaining the final diagnosis; however, the observation range is limited to the two‐dimensional plane, and it requires thin slicing of the tissue, which limits diagnostic information. To seek solutions for these problems, we proposed a novel imaging‐based histopathological examination. We used the multiphoton excitation microscopy (MPM) technique to establish a method for visualizing unfixed/unstained human breast tissues. Under near‐infrared ray excitation, fresh human breast tissues emitted fluorescent signals with three major peaks, which enabled visualizing the breast tissue morphology without any fixation or dye staining. Our study using human breast tissue samples from 32 patients indicated that experienced pathologists can estimate normal or cancerous lesions using only these MPM images with a kappa coefficient of 1.0. Moreover, we developed an image classification algorithm with artificial intelligence that enabled us to automatically define cancer cells in small areas with a high sensitivity of ≥0.942. Taken together, label‐free MPM imaging is a promising method for the real‐time automatic diagnosis of breast cancer.

Development and Validation of a Prediction Model for Positive Margins in Breast-Conserving Surgery

Background

The chances of second surgery due to positive margins in patients receiving breast-conversing surgery (BCS) were about 20-40%. This study aims to develop and validate a nomogram to predict the status of breast-conserving margins.

Methods

The database identified patients with core needle biopsy-proven ductal carcinoma in situ (DCIS) or invasive breast carcinoma who underwent BCS in Shanxi Bethune Hospital between January 1, 2015 and December 31, 2021 (n = 573). The patients were divided into two models: (1) The first model consists of 398 patients who underwent BCS between 2015 and 2019; (2) The validation model consists of 175 patients who underwent BCS between 2020 and 2021. The development of the nomogram was based on the findings of multivariate logistic regression analysis. Discrimination was assessed by computing the C-index. The Hosmer-Lemeshow goodness-of-fit test was used to validate the calibration performance.

Results

The final multivariate regression model was developed as a nomogram, including blood flow signals (OR = 2.88, p = 0.001), grade (OR = 2.46, p = 0.002), microcalcifications (OR = 2.39, p = 0.003), tumor size in ultrasound (OR = 2.12, p = 0.011) and cerbB-2 status (OR = 1.99, p = 0.042). C-indices were calculated of 0.71 (95% CI: 0.64-0.78) and 0.68 (95% CI: 0.59-0.78) for the modeling and the validation group, respectively. The calibration of the model was considered adequate in the validation group (p > 0.05).

Conclusion

We developed a nomogram that enables the estimation of the preoperative risk of positive BCS margins. Our nomogram provides a valuable tool for identifying high-risk patients who might have to undergo a wider excision.

Volumetric High-Resolution X-Ray Phase-Contrast Virtual Histology of Breast Specimens With a Compact Laboratory System

The assessment of margin involvement is a fundamental task in breast conserving surgery to prevent recurrences and reoperations. It is usually performed through histology, which makes the process time consuming and can prevent the complete volumetric analysis of large specimens. X-ray phase contrast tomography combines high resolution, sufficient penetration depth and high soft tissue contrast, and can therefore provide a potential solution to this problem. In this work, we used a high-resolution implementation of the edge illumination X-ray phase contrast tomography based on "pixel-skipping" X-ray masks and sample dithering, to provide high definition virtual slices of breast specimens. The scanner was originally designed for intra-operative applications in which short scanning times were prioritised over spatial resolution; however, thanks to the versatility of edge illumination, high-resolution capabilities can be obtained with the same system simply by swapping x-ray masks without this imposing a reduction in the available field of view. This makes possible an improved visibility of fine tissue strands, enabling a direct comparison of selected CT slices with histology, and providing a tool to identify suspect features in large specimens before slicing. Combined with our previous results on fast specimen scanning, this works paves the way for the design of a multi-resolution EI scanner providing intra-operative capabilities as well as serving as a digital pathology system.

Compression optical coherence elastography versus strain ultrasound elastography for breast cancer detection and differentiation: pilot study

The aims of this study are (i) to compare ultrasound strain elastography (US-SE) and compression optical coherence elastography (C-OCE) in characterization of elastically linear phantoms, (ii) to evaluate factors that can cause discrepancy between the results of the two elastographic techniques in application to real tissues, and (iii) to compare the results of US-SE and C-OCE in the differentiation of benign and malignant breast lesions. On 22 patients, we first used standard US-SE for in vivo assessment of breast cancer before and then after the lesion excision C-OCE was applied for intraoperative visualization of margins of the tumors and assessment of their type/grade using fresh lumpectomy specimens. For verification, the tumor grades and subtypes were determined histologically. We show that in comparison to US-SE, quantitative C-OCE has novel capabilities due to its ability to locally control stress applied to the tissue and obtain local stress-strain curves. For US-SE, we demonstrate examples of malignant tumors that were erroneously classified as benign and vice versa. For C-OCE, all lesions are correctly classified in agreement with the histology. The revealed discrepancies between the strain ratio given by US-SE and ratio of tangent Young's moduli obtained for the same samples by C-OCE are explained. Overall, C-OCE enables significantly improved specificity in breast lesion differentiation and ability to precisely visualize margins of malignant tumors compared. Such results confirm high potential of C-OCE as a high-speed and accurate method for intraoperative assessment of breast tumors and detection of their margins.