Technologies and techniques to improve precision in breast conserving surgery.

Imprecision in breast conserving surgery results in high rates of take back to theatre for reexcision of margins. This paper reviews the various approaches to improving the precision of oncological margin control in breast conserving surgery. The review describes the rationale for improved tissue characterization over tumor localization and explores technology-free approaches, as well as progress being made to develop and test innovative technological solutions.

Utilizing deep learning model for assessing melanocytic density in resection margins of lentigo maligna.

BACKGROUND: Surgical excision with clear histopathological margins is the preferred treatment to prevent progression of lentigo maligna (LM) to invasive melanoma. However, the assessment of resection margins on sun-damaged skin is challenging. We developed a deep learning model for detection of melanocytes in resection margins of LM. METHODS: In total, 353 whole slide images (WSIs) were included. 295 WSIs were used for training and 58 for validation and testing. The algorithm was trained with 3,973 manual pixel-wise annotations. The AI analyses were compared to those of three blinded dermatopathologists and two pathology residents, who performed their evaluations without AI and AI-assisted. Immunohistochemistry (SOX10) served as the reference standard. We used a dichotomized cutoff for low and high risk of recurrence (≤ 25 melanocytes in an area of 0.5 mm for low risk and > 25 for high risk). RESULTS: The AI model achieved an area under the receiver operating characteristic curve (AUC) of 0.84 in discriminating margins with low and high recurrence risk. In comparison, the AUC for dermatopathologists ranged from 0.72 to 0.90 and for the residents in pathology, 0.68 to 0.80. Additionally, with aid of the AI model the performance of two pathologists significantly improved. CONCLUSIONS: The deep learning showed notable accuracy in detecting resection margins of LM with a high versus low risk of recurrence. Furthermore, the use of AI improved the performance of 2/5 pathologists. This automated tool could aid pathologists in the assessment or pre-screening of LM margins.

A handheld device for intra-cavity and ex vivo fluorescence imaging of breast conserving surgery margins with 5-aminolevulinic acid.

BACKGROUND: Visualization of cancer during breast conserving surgery (BCS) remains challenging; the BCS reoperation rate is reported to be 20-70% of patients. An urgent clinical need exists for real-time intraoperative visualization of breast carcinomas during BCS. We previously demonstrated the ability of a prototype imaging device to identify breast carcinoma in excised surgical specimens following 5-aminolevulinic acid (5-ALA) administration. However, this prototype device was not designed to image the surgical cavity for remaining carcinoma after the excised lumpectomy specimen is removed. A new handheld fluorescence (FL) imaging prototype device, designed to image both excised specimens and within the surgical cavity, was assessed in a clinical trial to evaluate its clinical utility for first-in-human, real-time intraoperative imaging during index BCS. RESULTS: The imaging device combines consumer-grade imaging sensory technology with miniature light-emitting diodes (LEDs) and multiband optical filtering to capture high-resolution white light (WL) and FL digital images and videos. The technology allows for visualization of protoporphyrin IX (PpIX), which fluoresces red when excited by violet-blue light. To date, n = 17 patients have received 20 mg kg bodyweight (BW) 5-ALA orally 2-4 h before imaging to facilitate the accumulation of PpIX within tumour cells. Tissue types were identified based on their colour appearance. Breast tumours in sectioned lumpectomies appeared red, which contrasted against the green connective tissues and orange-brown adipose tissues. In addition, ductal carcinoma in situ (DCIS) that was missed during intraoperative standard of care was identified at the surgical margin at <1 mm depth. In addition, artifacts due to the surgical drape, illumination, and blood within the surgical cavity were discovered. CONCLUSIONS: This study has demonstrated the detection of a grossly occult positive margin intraoperatively. Artifacts from imaging within the surgical cavity have been identified, and potential mitigations have been proposed. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01837225 (Trial start date is September 2010. It was registered to ClinicalTrials.gov retrospectively on April 23, 2013, then later updated on April 9, 2020, to reflect the introduction of the new imaging device.).

Intraoperative Assessment of Margin Accuracy in Patients Diagnosed With Oral Squamous Cell Carcinoma in a Tertiary Hospital of Jharkhand: Frozen Section Versus Histopathology.

Background The incidence of head and neck carcinoma is increasing. The use of an intraoperative frozen section plays a vital role in the evaluation of margin status in patients undergoing surgery for oral squamous cell carcinoma. A negative margin is not only an indication of successful surgery but also decreases the recurrence of disease and improves the overall survival of patients. Aims and objective The aim of this study is to assess the accuracy of margin in patients undergoing surgery for oral squamous cell carcinoma by intraoperative frozen section and compare it with conventional histopathological examination. Methodology The approach of our study was a hospital-based prospective study conducted on 28 patients diagnosed with oral squamous cell carcinoma. A frozen section was done on all patients undergoing surgery and compared with histopathological examination. Results Out of 28 patients undergoing surgery, the incidence of males was more than females, with a ratio of 6:1. The most common site of the tumor was left buccal mucosa comprising 28.57%, followed by gingivobuccal sulcus comprising 17.85%. In our study, the frozen assessed margin showed a sensitivity of 58.33%, specificity of 98.76%, and accuracy of 95.25%. Conclusion Frozen section is a reliable method for confirmation of margin accuracy and thus reduces the chance of re-surgery and recurrence of disease and increases overall patient survival.

Margin assessment during breast conserving surgery using diffuse reflectance spectroscopy.

Significance: During breast-conserving surgeries, it is essential to evaluate the resection margins (edges of breast specimen) to determine whether the tumor has been removed completely. In current surgical practice, there are no methods available to aid in accurate real-time margin evaluation. Aim: In this study, we investigated the diagnostic accuracy of diffuse reflectance spectroscopy (DRS) combined with tissue classification models in discriminating tumorous tissue from healthy tissue up to 2 mm in depth on the actual resection margin of in vivo breast tissue. Approach: We collected an extensive dataset of DRS measurements on ex vivo breast tissue and in vivo breast tissue, which we used to develop different classification models for tissue classification. Next, these models were used in vivo to evaluate the performance of DRS for tissue discrimination during breast conserving surgery. We investigated which training strategy yielded optimum results for the classification model with the highest performance. Results: We achieved a Matthews correlation coefficient of 0.76, a sensitivity of 96.7% (95% CI 95.6% to 98.2%), a specificity of 90.6% (95% CI 86.3% to 97.9%) and an area under the curve of 0.98 by training the optimum model on a combination of ex vivo and in vivo DRS data. Conclusions: DRS allows real-time margin assessment with a high sensitivity and specificity during breast-conserving surgeries.

Spatial and Spectral Reconstruction of Breast Lumpectomy Hyperspectral Images.

(1) Background: Hyperspectral imaging has emerged as a promising margin assessment technique for breast-conserving surgery. However, to be implicated intraoperatively, it should be both fast and capable of yielding high-quality images to provide accurate guidance and decision-making throughout the surgery. As there exists a trade-off between image quality and data acquisition time, higher resolution images come at the cost of longer acquisition times and vice versa. (2) Methods: Therefore, in this study, we introduce a deep learning spatial-spectral reconstruction framework to obtain a high-resolution hyperspectral image from a low-resolution hyperspectral image combined with a high-resolution RGB image as input. (3) Results: Using the framework, we demonstrate the ability to perform a fast data acquisition during surgery while maintaining a high image quality, even in complex scenarios where challenges arise, such as blur due to motion artifacts, dead pixels on the camera sensor, noise from the sensor's reduced sensitivity at spectral extremities, and specular reflections caused by smooth surface areas of the tissue. (4) Conclusion: This gives the opportunity to facilitate an accurate margin assessment through intraoperative hyperspectral imaging.

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.

Toward the use of diffuse reflection spectroscopy for intra-operative tissue discrimination during sarcoma surgery.

Significance: Accurately distinguishing tumor tissue from normal tissue is crucial to achieve complete resections during soft tissue sarcoma (STS) surgery while preserving critical structures. Incomplete tumor resections are associated with an increased risk of local recurrence and worse patient prognosis. Aim: We evaluate the performance of diffuse reflectance spectroscopy (DRS) to distinguish tumor tissue from healthy tissue in STSs. Approach: DRS spectra were acquired from different tissue types on multiple locations in 20 freshly excised sarcoma specimens. A k-nearest neighbors classification model was trained to predict the tissue types of the measured locations, using binary and multiclass approaches. Results: Tumor tissue could be distinguished from healthy tissue with a classification accuracy of 0.90, sensitivity of 0.88, and specificity of 0.93 when well-differentiated liposarcomas were included. Excluding this subtype, the classification performance increased to an accuracy of 0.93, sensitivity of 0.94, and specificity of 0.93. The developed model showed a consistent performance over different histological subtypes and tumor locations. Conclusions: Automatic tissue discrimination using DRS enables real-time intra-operative guidance, contributing to more accurate STS resections.

Current clinical applications of Cerenkov luminescence for intraoperative molecular imaging.

BACKGROUND: Cerenkov luminescence imaging (CLI) is a new emerging technology that can be used for optical imaging of approved radiotracers, both in a preclinical, and even more recently, in a clinical context with rapid imaging times, low costs, and detection in real-time (Grootendorst et al. Clin Transl Imaging 4(5):353-66, 2016); Wang et al. Photonics 9(6):390, 2022). This brief review provides an overview of clinical applications of CLI with a focus on intraoperative margin assessment (IMA) to address shortcomings and provide insight for future work in this application. METHODS: A literature review was performed using PubMed using the search words Cerenkov luminescence imaging (CLI), intraoperative margin assessment (IMA), and image-guided surgery. Articles were selected based on title, abstract, content, and application. RESULTS: Original research was summarized to examine advantages and limitations of CLI compared to other modalities for IMA. The characteristics of Cerenkov luminescence (CL) are defined, and results from relevant clinical trials are discussed. Prospects of ongoing clinical trials are reviewed, along with technological advancements related to CLI. CONCLUSION: CLI is a proven method for molecular imaging and shows feasibility for determining intraoperative margins if future work involves establishing quantitative approaches for attenuation and scattering, depth analysis, and radiation safety for CLI at a larger scale.

Identification of Optimal Tissue-Marking Dye Color for Pathological Evaluation in Fluorescence Imaging Using IRDye800CW.

PURPOSE: Fluorescence-guided surgery using a tumor-specific antibody-dye conjugate is useful in various cancer types. Fluorescence imaging is a valuable tool both intraoperatively and postoperatively for ex vivo imaging. The color of inks used for tumor specimens during ex vivo specimen processing in pathology is an important consideration for fluorescence imaging since the absorption/emission of the dyes may interfere with the fluorescent dye. This study assesses suitable ink colors for use specifically with IRDye800CW fluorescence imaging. PROCEDURES: Eight tissue-marking inks or dyes (TMDs) commonly used for pathological evaluation were assessed. Agarose tissue-mimicking phantoms containing Panitumumab-IRDye800CW were used as an initial model. Mean fluorescence intensity was measured at 800 nm using both Pearl Trilogy as a closed-field fluorescence imaging system and pde-neo II as an open-field fluorescence imaging system before and after TMD application. An in vivo mouse xenograft model using the human head and neck squamous cell carcinoma FaDu cell line was then used in conjunction with TMDs. RESULTS: The retained IRDye800CW fluorescence on Pearl Trilogy was as follows: yellow at 91.0 ± 4.5%, red at 90.6 ± 2.7%, orange at 88.2 ± 2.2%, violet at 56.6 ± 1.1%, lime at 40.9 ± 1.8%, green at 19.3 ± 2.8%, black at 13.3 ± 0.6%, and blue at 8.1 ± 0.2%. The retained IRDye800CW fluorescence on pde-neo II was as follows: yellow at 86.5 ± 6.4%, red at 77.0 ± 6.2%, orange at 76.9 ± 2.8%, lime at 72.5 ± 9.5%, violet at 59.7 ± 0.4%, green at 30.1 ± 6.9%, black at 17.0 ± 2.7%, and blue at 6.7 ± 1.7%. The retained IRDye800CW fluorescence in yellow and blue TMDs was 42.1 ± 14.9% and 0.2 ± 0.2%, respectively in the mouse experiment (p = 0.039). CONCLUSION: Yellow, red, and orange TMDs should be used, and blue and black TMDs should be avoided for evaluating tumor specimens through fluorescence imaging using IRDye800CW.

Tumor Segmentation in Colorectal Ultrasound Images Using an Ensemble Transfer Learning Model: Towards Intra-Operative Margin Assessment.

Tumor boundary identification during colorectal cancer surgery can be challenging, and incomplete tumor removal occurs in approximately 10% of the patients operated for advanced rectal cancer. In this paper, a deep learning framework for automatic tumor segmentation in colorectal ultrasound images was developed, to provide real-time guidance on resection margins using intra-operative ultrasound. A colorectal ultrasound dataset was acquired consisting of 179 images from 74 patients, with ground truth tumor annotations based on histopathology results. To address data scarcity, transfer learning techniques were used to optimize models pre-trained on breast ultrasound data for colorectal ultrasound data. A new custom gradient-based loss function (GWDice) was developed, which emphasizes the clinically relevant top margin of the tumor while training the networks. Lastly, ensemble learning methods were applied to combine tumor segmentation predictions of multiple individual models and further improve the overall tumor segmentation performance. Transfer learning outperformed training from scratch, with an average Dice coefficient over all individual networks of 0.78 compared to 0.68. The new GWDice loss function clearly decreased the average tumor margin prediction error from 1.08 mm to 0.92 mm, without compromising the segmentation of the overall tumor contour. Ensemble learning further improved the Dice coefficient to 0.84 and the tumor margin prediction error to 0.67 mm. Using transfer and ensemble learning strategies, good tumor segmentation performance was achieved despite the relatively small dataset. The developed US segmentation model may contribute to more accurate colorectal tumor resections by providing real-time intra-operative feedback on tumor margins.

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.

3D Ultrasound and MRI in Assessing Resection Margins during Tongue Cancer Surgery: A Research Protocol for a Clinical Diagnostic Accuracy Study.

Surgery is the primary treatment for tongue cancer. The goal is a complete resection of the tumor with an adequate margin of healthy tissue around the tumor.Inadequate margins lead to a high risk of local cancer recurrence and the need for adjuvant therapies. Ex vivo imaging of the resected surgical specimen has been suggested for margin assessment and improved surgical results. Therefore, we have developed a novel three-dimensional (3D) ultrasound imaging technique to improve the assessment of resection margins during surgery. In this research protocol, we describe a study comparing the accuracy of 3D ultrasound, magnetic resonance imaging (MRI), and clinical examination of the surgical specimen to assess the resection margins during cancer surgery. Tumor segmentation and margin measurement will be performed using 3D ultrasound and MRI of the ex vivo specimen. We will determine the accuracy of each method by comparing the margin measurements and the proportion of correctly classified margins (positive, close, and free) obtained by each technique with respect to the gold standard histopathology.

Care Pathway Analysis to Inform the Earliest Stages of Technology Development: Scoping Oncological Indications in Need of Innovation.

OBJECTIVES: Identifying unmet needs for innovative solutions across disease contexts is challenging but important for directing funding and research efforts and informing early-stage decisions during the innovation process. Our aim was to study the merits of care pathway analysis to scope disease contexts and guide the development of innovative devices. We used oncologic surgery as a case study, for which many intraoperative imaging techniques are under development. METHODS: Care pathway analysis is a mapping process, which produces graphical maps of clinical pathways using important outcomes and subsequent consequences. We performed care pathway analyses for glioblastoma, breast, bladder, prostate, renal, pancreatic, and oral cavity cancer. Differences between a "perfect" care pathway and the current care pathway in terms of percentage of inadequate margins, associated recurrences, quality of life, and 5-year overall survival were calculated to determine unmet needs. Data from The Netherlands Cancer Registry and literature were used. RESULTS: Care pathway analysis showed that highest percentages of inadequate margins were found in oral cavity cancer (72.5%), glioblastoma (48.7%), and pancreatic cancer (43.9%). Inadequate margins showed the strongest increase in recurrences in cancer of oral cavity, and bladder (absolute increases of 43.5% and 41.2%, respectively). Impact on survival was largest for bladder and oral cavity cancer with positive margins. CONCLUSIONS: Care pathway analysis provides overviews of current clinical paths in multiple indications. Disease contexts can be compared via effectiveness gaps that show the potential need for innovative solutions. This information can be used as basis for stakeholder involvement processes to prioritize care pathways in need of innovation.

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.

Tissue Classification of Breast Cancer by Hyperspectral Unmixing.

(1) Background: Assessing the resection margins during breast-conserving surgery is an important clinical need to minimize the risk of recurrent breast cancer. However, currently there is no technique that can provide real-time feedback to aid surgeons in the margin assessment. Hyperspectral imaging has the potential to overcome this problem. To classify resection margins with this technique, a tissue discrimination model should be developed, which requires a dataset with accurate ground-truth labels. However, establishing such a dataset for resection specimens is difficult. (2) Methods: In this study, we therefore propose a novel approach based on hyperspectral unmixing to determine which pixels within hyperspectral images should be assigned to the ground-truth labels from histopathology. Subsequently, we use this hyperspectral-unmixing-based approach to develop a tissue discrimination model on the presence of tumor tissue within the resection margins of ex vivo breast lumpectomy specimens. (3) Results: In total, 372 measured locations were included on the lumpectomy resection surface of 189 patients. We achieved a sensitivity of 0.94, specificity of 0.85, accuracy of 0.87, Matthew's correlation coefficient of 0.71, and area under the curve of 0.92. (4) Conclusion: Using this hyperspectral-unmixing-based approach, we demonstrated that the measured locations with hyperspectral imaging on the resection surface of lumpectomy specimens could be classified with excellent performance.

Exploring knowledge gaps in the understanding of peripheral and deep en face margin assessment.

In 2022, National Comprehensive Cancer Network updated the phrase of "complete circumferential peripheral and deep margin assessment (CCPDMA)" to "peripheral and deep en face margin assessment (PDEMA)," which was meant to create more consistency across all treatment modalities and provide clarity to the meaning of total margin evaluation. The aim of this project was to investigate the interpretation of PDEMA across pertinent specialties and to identify any existing knowledge gaps in hopes of improving clinical performance of institutional practice. An electronic survey was administered to medical professionals within the divisions of dermatology and otolaryngology retrieving demographic data and assessing respondents' knowledge on tissue processing techniques and PDEMA. Of the four knowledge-based assessment questions administered, dermatology respondents answered three questions with > 80% accuracy and one question with < 65% accuracy. Otolaryngology respondents answered one question with > 80% accuracy and three with < 65% accuracy. Both groups answered the knowledge-based question evaluating the concept of "what must be true for Mohs or PDEMA to have value" with under 65% accuracy. When comparing dermatology and otolaryngology respondents, only one question which evaluated the proper methods to "achieve processing of the epidermal edge and the base of the tumor along a single plane in the lab" significantly differed between groups, with a percentage correct of 96% for dermatologists compared to 54% for otolaryngologists (p < 0.001). Results were found to be similar when resident physicians were removed from analysis. The overall percent correct for knowledge-based questions was shifted higher for dermatologists compared to otolaryngologists (p = 0.014). This trend was also redemonstrated when analyzing the data excluding residents (p = 0.053).

Intraoperative Assessment of Margin Accuracy in Early Oral Squamous Cell Carcinoma (cT1, T2, N0): Clinical Versus Frozen Section Analysis.

Background The incidence of oral cavity cancer is increasing. During oral carcinoma surgery, to achieve a tumor-free margin, intraoperative margin assessment includes two primary methods, namely, clinical examination and frozen section analysis. With extensive preoperative imaging investigations and intraoperative clinical margin assessment, the need for further cost and resource-intensive frozen section analysis has recently come under question. This study aimed to assess whether frozen section analysis can be safely omitted in most cases of early oral squamous cell carcinoma surgeries for cost-effectiveness. Methodology A hospital-based, observational study including 30 admitted cases of early oral squamous cell carcinoma was conducted at the Department of General Surgery, Pradyumna Bal Memorial Hospital, Bhubaneswar. All consecutive confirmed cases of early oral squamous cell carcinoma of all age groups and both genders after considering the inclusion and exclusion criteria were involved in the study. A comparative assessment of the free margins after tumor excision was done by the surgeon followed by frozen section analysis. Results The mean age was 53.03 ± 13.72 years, with a male-to-female ratio of 6.5:1. Carcinoma of the lower alveolus with gingivobuccal sulcus was the most common presentation of the study (33.33%). In our study, clinically assessed margins had a sensitivity of 75.39%, a specificity of 94.43%, and an accuracy of 92.77%. Frozen section assessed margins had a sensitivity of 66.5%, a specificity of 96.94%, and an accuracy of 92.77%. Conclusions Based on the accuracy of clinically assessed and frozen section assessed margins, this study concluded that surgically resected/excised specimen by the surgeon plays a vital role in assessing the adequacy of resected/excised margins in early oral squamous cell carcinoma (cT1, T2, N0) cases, which can possibly replace the costly frozen section analysis.

Dual probe difference specimen imaging for prostate cancer margin assessment.

Significance: Positive margin status due to incomplete removal of tumor tissue during radical prostatectomy for high-risk localized prostate cancer requires reoperation or adjuvant therapy, which increases morbidity and mortality. Adverse effects of prostate cancer treatments commonly include erectile dysfunction, urinary incontinence, and bowel dysfunction, making successful initial curative prostatectomy imperative. Aim: Current intraoperative tumor margin assessment is largely limited to frozen section analysis, which is a lengthy, labor-intensive process that is obtrusive to the clinical workflow within the operating room (OR). Therefore, a rapid method for prostate cancer margin assessment in the OR could improve outcomes for patients. Approach: Dual probe difference specimen imaging (DDSI), which uses paired antibody-based probes that are labeled with spectrally distinct fluorophores, was shown herein for prostate cancer margin assessment. The paired antibody-based probes consisted of a targeted probe to prostate-specific membrane antigen (PSMA) and an untargeted probe, which were used as a cocktail to stain resected murine tissue specimens including prostate tumor, adipose, muscle, and normal prostate. Ratiometric images (i.e., DDSI) of the difference between targeted and untargeted probe uptake were calculated and evaluated for accuracy using receiver operator characteristic curve analysis with area under the curve values used to evaluate the utility of the DDSI method to detect PSMA positive prostate cancer. Results: Targeted and untargeted probe uptake was similar between the high and low PSMA expressing tumor due to nonspecific probe uptake after topical administration. The ratiometric DDSI approach showed substantial contrast difference between the PSMA positive tumors and their respective normal tissues (prostate, adipose, muscle). Furthermore, DDSI showed substantial contrast difference between the high PSMA expressing tumors and the minimally PSMA expressing tumors due to the ratiometric correction for the nonspecific uptake patterns in resected tissues. Conclusions: Previous work has shown that ratiometic imaging has strong predictive value for breast cancer margin status using topical administration. Translation of the ratiometric DDSI methodology herein from breast to prostate cancers demonstrates it as a robust, ratiometric technique that provides a molecularly specific imaging modality for intraoperative margin detection. Using the validated DDSI protocol on resected prostate cancers permitted rapid and accurate assessment of PSMA status as a surrogate for prostate cancer margin status. Future studies will further evaluate the utility of this technology to quantitatively characterize prostate margin status using PSMA as a biomarker.

Simple and effective immobilization for radiation treatment of choroidal melanoma.

At our institution, patients diagnosed with choroidal melanoma requiring external beam radiation therapy are treated with two 6 MV volumetric-modulated arcs delivering 50 Gy over 5 daily fractions. The patient is immobilized using an Orfit head and neck mask and is directed to look at a light emitting diode (LED) during CT simulation and treatment to minimize eye movement. Patient positioning is checked with cone beam computed tomography (CBCT) daily. Translational and rotational displacements greater than 1 mm or 1° off the planned isocenter position are corrected using a Hexapod couch. The aim of this study is to verify that the mask system provides adequate immobilization and to verify our 2-mm planning target volume (PTV) margins are sufficient. Residual displacements provided by pretreatment verification and post-treatment CBCT data sets were used to assess the impact of patient mobility during treatment on the reconstructed delivered dose to the target and organs at risk. The PTV margin calculated using van Herk's method1 was used to assess patient motion plus other factors that affect treatment position, such as kV-MV isocenter coincidence. Patient position variations were small and were shown to not cause significant dose variations between the planned and reconstructed dose to the target and organs at risk. The PTV margin analysis showed patient translational motion alone required a PTV margin of 1 mm. Given other factors that affect treatment delivery accuracy, a 2-mm PTV margin was shown to be sufficient for treatment of 95% of our patients with 100% of dose delivered to the GTV. The mask immobilization with LED focus is robust and we showed a 2-mm PTV margin is adequate with this technique.