Fluorescence lifetime imaging for intraoperative cancer delineation in transoral robotic surgery

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32[Formula: see text]32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

Applications of machine learning in time-domain fluorescence lifetime imaging: a review

Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable human resources. In recent years, Fluorescence Lifetime Imaging (FLIm) has received increasing attention from the ML community. FLIm goes beyond conventional spectral imaging, providing additional lifetime information, and could lead to optical histopathology supporting real-time diagnostics. However, most current studies do not use the full potential of machine/deep learning models. As a developing image modality, FLIm data are not easily obtainable, which, coupled with an absence of standardisation, is pushing back the research to develop models which could advance automated diagnosis and help promote FLIm. In this paper, we describe recent developments that improve FLIm image quality, specifically time-domain systems, and we summarise sensing, signal-to-noise analysis and the advances in registration and low-level tracking. We review the two main applications of ML for FLIm: lifetime estimation and image analysis through classification and segmentation. We suggest a course of action to improve the quality of ML studies applied to FLIm. Our final goal is to promote FLIm and attract more ML practitioners to explore the potential of lifetime imaging.

Fluorescence lifetime of injected indocyanine green as a universal marker of solid tumours in patients

The surgical resection of solid tumours can be enhanced by fluorescence-guided imaging. However, variable tumour uptake and incomplete clearance of fluorescent dyes reduces the accuracy of distinguishing tumour from normal tissue via conventional fluorescence intensity-based imaging. Here we show that, after systemic injection of the near-infrared dye indocyanine green in patients with various types of solid tumour, the fluorescence lifetime (FLT) of tumour tissue is longer than the FLT of non-cancerous tissue. This tumour-specific shift in FLT can be used to distinguish tumours from normal tissue with an accuracy of over 97% across tumour types, and can be visualized at the cellular level using microscopy and in larger specimens through wide-field imaging. Unlike fluorescence intensity, which depends on imaging-system parameters, tissue depth and the amount of dye taken up by tumours, FLT is a photophysical property that is largely independent of these factors. FLT imaging with indocyanine green may improve the accuracy of cancer surgeries.

Trends in Positive Surgical Margins in cT3-T4 Oral Cavity Squamous Cell Carcinoma

OBJECTIVE

Positive surgical margins in oral cavity squamous cell carcinoma are associated with cost escalation, treatment intensification, and greater risk of recurrence and mortality. The positive margin rate has been decreasing for cT1-T2 oral cavity cancer over the past 2 decades. We aim to evaluate positive margin rates in cT3-T4 oral cavity cancer over time, and determine factors associated with positive margins.

STUDY DESIGN

Retrospective analysis of a national database.

SETTING

National Cancer Database 2004 to 2018.

METHODS

All adult patients diagnosed between 2004 and 2018 who underwent primary curative intent surgery for previously untreated cT3-T4 oral cavity cancer with known margin status were included. Logistic univariable and multivariable regression analyses were performed to identify factors associated with positive margins.

RESULTS

Among 16,326 patients with cT3 or cT4 oral cavity cancer, positive margins were documented in 2932 patients (18.1%). Later year of treatment was not significantly associated with positive margins (odds ratio [OR] 0.98, 95% confidence interval [CI] 0.96-1.00). The proportion of patients treated at academic centers increased over time (OR 1.02, 95% CI 1.01-1.03). On multivariable analysis, positive margins were significantly associated with hard palate primary, cT4 tumors, advancing N stage, lymphovascular invasion, poorly differentiated histology, and treatment at nonacademic or low-volume centers.

CONCLUSION

Despite increased treatment at academic centers for locally advanced oral cavity cancer, there has been no significant decrease in positive margin rates which remains high at 18.1%. Novel techniques for margin planning and assessment may be required to decrease positive margin rates in locally advanced oral cavity cancer.

Intraoperative Imaging Techniques to Improve Surgical Resection Margins of Oropharyngeal Squamous Cell Cancer: A Comprehensive Review of Current Literature

Inadequate resection margins in head and neck squamous cell carcinoma surgery necessitate adjuvant therapies such as re-resection and radiotherapy with or without chemotherapy and imply increasing morbidity and worse prognosis. On the other hand, taking larger margins by extending the resection also leads to avoidable increased morbidity. Oropharyngeal squamous cell carcinomas (OPSCCs) are often difficult to access; resections are limited by anatomy and functionality and thus carry an increased risk for close or positive margins. Therefore, there is a need to improve intraoperative assessment of resection margins. Several intraoperative techniques are available, but these often lead to prolonged operative time and are only suitable for a subgroup of patients. In recent years, new diagnostic tools have been the subject of investigation. This study reviews the available literature on intraoperative techniques to improve resection margins for OPSCCs. A literature search was performed in Embase, PubMed, and Cochrane. Narrow band imaging (NBI), high-resolution microendoscopic imaging, confocal laser endomicroscopy, frozen section analysis (FSA), ultrasound (US), computed tomography scan (CT), (auto) fluorescence imaging (FI), and augmented reality (AR) have all been used for OPSCC. NBI, FSA, and US are most commonly used and increase the rate of negative margins. Other techniques will become available in the future, of which fluorescence imaging has high potential for use with OPSCC.

Intraoperative delineation of p16+ oropharyngeal carcinoma of unknown primary origin with fluorescence lifetime imaging: Preliminary report

BACKGROUND

This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP).

METHODS

FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology.

RESULTS

Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no identifiable primary site in the oropharynx. FLIm correctly detected HNSCCUP in all three patients (ROC-AUC: 0.90 ± 0.06), and correctly predicted benign oropharyngeal tissue for the remaining three patients. The mean sensitivity was 95% ± 3.5%, and specificity 89% ± 12.7%.

CONCLUSIONS

FLIm may be a useful diagnostic adjunct for detecting HNSCCUP.

Intraoperative In Vivo Imaging Modalities in Head and Neck Cancer Surgical Margin Delineation: A Systematic Review

Surgical margin status is one of the strongest prognosticators in predicting patient outcomes in head and neck cancer, yet head and neck surgeons continue to face challenges in the accurate detection of these margins with the current standard of care. Novel intraoperative imaging modalities have demonstrated great promise for potentially increasing the accuracy and efficiency in surgical margin delineation. In this current study, we collated and analyzed various intraoperative imaging modalities utilized in head and neck cancer to evaluate their use in discriminating malignant from healthy tissues. The authors conducted a systematic database search through PubMed/Medline, Web of Science, and EBSCOhost (CINAHL). Study screening and data extraction were performed and verified by the authors, and more studies were added through handsearching. Here, intraoperative imaging modalities are described, including optical coherence tomography, narrow band imaging, autofluorescence, and fluorescent-tagged probe techniques. Available sensitivities and specificities in delineating cancerous from healthy tissues ranged from 83.0% to 100.0% and 79.2% to 100.0%, respectively, across the different imaging modalities. Many of these initial studies are in small sample sizes, with methodological differences that preclude more extensive quantitative comparison. Thus, there is impetus for future larger studies examining and comparing the efficacy of these intraoperative imaging technologies.

Development of a microstructured tissue phantom with adaptable optical properties for use with microscopes and fluorescence lifetime imaging systems

OBJECTIVES

For the development and validation of diagnostic procedures based on microscopic methods, knowledge about the imaging depth and achievable resolution in tissue is crucial. This poses the challenge to develop a microscopic artificial phantom focused on the microscopic instead of the macroscopic optical tissue characteristics.

METHODS

As existing artificial tissue phantoms designed for image forming systems are primarily targeted at wide field applications, they are unsuited for reaching the formulated objective. Therefore, a microscopy- and microendoscopy-suited artificial tissue phantom was developed and characterized. It is based on a microstructured glass surface coated with fluorescent beads at known depths covered by a scattering agent with modifiable optical properties. The phantom was examined with different kinds of microscopy systems in order to characterize its quality and stability and to demonstrate its usefulness for instrument comparison, for example, regarding structural as well as fluorescence lifetime analysis.

RESULTS

The analysis of the manufactured microstructured glass surfaces showed high regularity in their physical dimensions in accordance with the specifications. Measurements of the optical parameters of the scattering medium were consistent with simulations. The fluorescent beads coating proved to be stable for a respectable period of time (about a week). The developed artificial tissue phantom was successfully used to detect differences in image quality between a research microscope and an endoscopy based system. Plausible causes for the observed differences could be derived based on the well known microstructure of the phantom.

CONCLUSIONS

The artificial tissue phantom is well suited for the intended use with microscopic and microendoscopic systems. Due to its configurable design, it can be adapted to a wide range of applications. It is especially targeted at the characterization and calibration of clinical imaging systems that often lack extensive positioning capabilities such as an intrinsic z-stage.

First Clinical Results of Fluorescence Lifetime-enhanced Tumor Imaging Using Receptor-targeted Fluorescent Probes

PURPOSE

Fluorescence molecular imaging, using cancer-targeted near infrared (NIR) fluorescent probes, offers the promise of accurate tumor delineation during surgeries and the detection of cancer specific molecular expression in vivo. However, nonspecific probe accumulation in normal tissue results in poor tumor fluorescence contrast, precluding widespread clinical adoption of novel imaging agents. Here we present the first clinical evidence that fluorescence lifetime (FLT) imaging can provide tumor specificity at the cellular level in patients systemically injected with panitumumab-IRDye800CW, an EGFR-targeted NIR fluorescent probe.

EXPERIMENTAL DESIGN

We performed wide-field and microscopic FLT imaging of resection specimens from patients injected with panitumumab-IRDye800CW under an FDA directed clinical trial.

RESULTS

We show that the FLT within EGFR-overexpressing cancer cells is significantly longer than the FLT of normal tissue, providing high sensitivity (>98%) and specificity (>98%) for tumor versus normal tissue classification, despite the presence of significant nonspecific probe accumulation. We further show microscopic evidence that the mean tissue FLT is spatially correlated (r > 0.85) with tumor-specific EGFR expression in tissue and is consistent across multiple patients. These tumor cell-specific FLT changes can be detected through thick biological tissue, allowing highly specific tumor detection and noninvasive monitoring of tumor EFGR expression in vivo.

CONCLUSIONS

Our data indicate that FLT imaging is a promising approach for enhancing tumor contrast using an antibody-targeted NIR probe with a proven safety profile in humans, suggesting a strong potential for clinical applications in image guided surgery, cancer diagnostics, and staging.

Safety of use of the ENDOSWIR near-infrared optical imaging device on human tissues: prospective blind study

Cancer surgery requires removing the tumor tissue in necessary and sufficient quantities. Spectral optical imaging in the short-wave infrared (900-1700 nm) could provide an intraoperative guidance to the surgeon based on the absorption of the tissues without contrast agent. Our objective was to ensure the safety of our ENDOSWIR device on human tissues. Histological analysis of fresh human tonsils exposed to the SWIR light or not was compared and showed no histological differences. This demonstrates the safety of using the SWIR device on human tissues and allows us to initiate a clinical study for the resection of tumors intraoperatively.

Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules

Background

This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules.

Methods

Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy.

Results

One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentration_nodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort.

Conclusions

Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.

Multispectral fluorescence lifetime imaging device with a silicon avalanche photodetector

We report the design, development, and characterization of a novel multi-spectral fluorescence lifetime measurement device incorporating solid-state detectors and automated gain control. For every excitation pulse (∼1 µJ, 600 ps), this device records complete fluorescence decay from multiple spectral channels simultaneously within microseconds, using a dedicated UV enhanced avalanche photodetector and analog to digital convert (2.5 GS/s) in each channel. Fast (<2 ms) channel-wise dynamic range adjustment maximizes the signal-to-noise ratio. Fluorophores with known lifetime ranging from 0.5-6.0 ns were used to demonstrate the device accuracy. Current results show the clear benefits of this device compared to existing devices employing microchannel-plate photomultiplier tubes. This is demonstrated by 5-fold reduction of lifetime measurement variability in identical conditions, independent gain adjustment in each spectral band, and 4-times faster imaging speed. The use of solid-state detectors will also facilitate future improved performance and miniaturization of the instrument.

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

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

Intraoperative Mapping of Parathyroid Glands Using Fluorescence Lifetime Imaging

BACKGROUND

Hypoparathyroidism is a common complication following thyroidectomy. There is a need for technology to aid surgeons in identifying the parathyroid glands. In contrast to near infrared technologies, fluorescence lifetime imaging (FLIm) is not affected by ambient light and may be valuable in identifying parathyroid tissue, but has never been evaluated in this capacity.

METHODS

We used FLIm to measure the UV induced (355 nm) time-resolved autofluorescence signatures (average lifetimes in 3 spectral emission channels) of thyroid, parathyroid, lymphoid and adipose tissue in 21 patients undergoing thyroid and parathyroid surgery. The Mann-Whitney U test was used to assess the ability of FLIm to discriminate normocellular parathyroid from each of the other tissues. Various machine learning classifiers (random forests, neural network, support vector machine) were then evaluated to recognize parathyroid through a leave-one-out cross-validation.

RESULTS

Statistically significant differences in average lifetime were observed between parathyroid and each of the other tissue types in spectral channels 2 and 3 respectively. The largest change was observed between adipose tissue and parathyroid (P < 0.001), while less pronounced but still significant changes were observed when comparing parathyroid with lymphoid tissue (P < 0.05) and thyroid (P < 0.01). A random forest classifier trained on average lifetimes was found to detect parathyroid tissue with 100% sensitivity and 93% specificity at the acquisition run level.

CONCLUSION

We found that FLIm derived parameters can distinguish the parathyroid glands and other adjacent tissue types and has promise in scanning the surgical field to identify parathyroid tissue in real-time.

Imaging-based navigation technologies in head and neck surgery

PURPOSE OF REVIEW

Image guided navigation has had significant impact in head and neck surgery, and has been most prolific in endonasal surgeries. Although conventional image guidance involves static computed tomography (CT) images attained in the preoperative setting, the continual evolution of surgical navigation technologies is fast expanding to incorporate both real-time data and bioinformation that allows for improved precision in surgical guidance. With the rapid advances in technologies, this article allows for a timely review of the current and developing techniques in surgical navigation for head and neck surgery.

RECENT FINDINGS

Current advances for cross-sectional-based image-guided surgery include fusion of CT with other imaging modalities (e.g., magnetic resonance imaging and positron emission tomography) as well as the uptake in intraoperative real-time 'on the table' imaging (e.g., cone-beam CT). These advances, together with the integration of virtual/augmented reality, enable potential enhancements in surgical navigation. In addition to the advances in radiological imaging, the development of optical modalities such as fluorescence and spectroscopy techniques further allows the assimilation of biological data to improve navigation particularly for head and neck surgery.

SUMMARY

The steady development of radiological and optical imaging techniques shows great promise in changing the paradigm of head and neck surgery.

Intraoperative Margin Assessment in Oral and Oropharyngeal Cancer Using Label-Free Fluorescence Lifetime Imaging and Machine Learning

OBJECTIVE

To demonstrate the diagnostic ability of label-free, point-scanning, fiber-based Fluorescence Lifetime Imaging (FLIm) as a means of intraoperative guidance during oral and oropharyngeal cancer removal surgery.

METHODS

FLIm point-measurements acquired from 53 patients (n = 67893 pre-resection in vivo, n = 89695 post-resection ex vivo) undergoing oral or oropharyngeal cancer removal surgery were used for analysis. Discrimination of healthy tissue and cancer was investigated using various FLIm-derived parameter sets and classifiers (Support Vector Machine, Random Forests, CNN). Classifier output for the acquired set of point-measurements was visualized through an interpolation-based approach to generate a probabilistic heatmap of cancer within the surgical field. Classifier output for dysplasia at the resection margins was also investigated.

RESULTS

Statistically significant change (P 0.01) between healthy and cancer was observed in vivo for the acquired FLIm signal parameters (e.g., average lifetime) linked with metabolic activity. Superior classification was achieved at the tissue region level using the Random Forests method (ROC-AUC: 0.88). Classifier output for dysplasia (% probability of cancer) was observed to lie between that of cancer and healthy tissue, highlighting FLIm's ability to distinguish various conditions.

CONCLUSION

The developed approach demonstrates the potential of FLIm for fast, reliable intraoperative margin assessment without the need for contrast agents.

SIGNIFICANCE

Fiber-based FLIm has the potential to be used as a diagnostic tool during cancer resection surgery, including Transoral Robotic Surgery (TORS), helping ensure complete resections and improve the survival rate of oral and oropharyngeal cancer patients.

Assessment of breast cancer surgical margins with multimodal optical microscopy: A feasibility clinical study

Providing surgical margin information during breast cancer surgery is crucial for the success of the procedure. The margin is defined as the distance from the tumor to the cut surface of the resection specimen. The consensus among surgeons and radiation oncologists is that there should be no tumor left within 1 to maximum 2 mm from the surface of the surgical specimen. If a positive margin remains, there is substantial risk for tumor recurrence, which may also result in potentially reduced cosmesis and eventual need for mastectomy. In this paper we report a novel multimodal optical imaging instrument based on combined high-resolution confocal microscopy-optical coherence tomography imaging for assessing the presence of potential positive margins on surgical specimens. Since rapid specimen analysis is critical during surgery, this instrument also includes a fluorescence imaging channel to enable rapid identification of the areas of the specimen that have potential positive margins. This is possible by specimen incubation with a cancer specific agent prior to imaging. In this study we used a quenched contrast agent, which is activated by cancer specific enzymes, such as urokinase plasminogen activators (uPA). Using this agent or a similar one, one may limit the use of high-resolution optical imaging to only fluorescence-highlighted areas for visualizing tissue morphology at the sub-cellular scale and confirming or ruling out cancer presence. Preliminary evaluation of this technology was performed on 20 surgical specimens and testing of the optical imaging findings was performed against histopathology. The combination of the three imaging modes allowed for high correlation between optical image analysis and histological ground-truth. The initial results are encouraging, showing instrument capability to assess margins on clinical specimens with a positive predictive value of 1.0 and a negative predictive value of 0.83.

FLImBrush: dynamic visualization of intraoperative free-hand fiber-based fluorescence lifetime imaging

A free-hand scanning approach to medical imaging allows for flexible, lightweight probes to image intricate anatomies for modalities such as fluorescence lifetime imaging (FLIm), optical coherence tomography (OCT) and ultrasound. While very promising, this approach faces several key challenges including tissue motion during imaging, varying lighting conditions in the surgical field, and sparse sampling of the tissue surface. These challenges limit the coregistration accuracy and interpretability of the acquired imaging data. Here we report FLImBrush as a robust method for the localization and visualization of intraoperative free-hand fiber optic fluorescence lifetime imaging (FLIm). FLImBrush builds upon an existing method while employing deep learning-based image segmentation, block-matching based motion correction, and interpolation-based visualization to address the aforementioned challenges. Current results demonstrate that FLImBrush can provide accurate localization of FLIm point-measurements while producing interpretable and complete visualizations of FLIm data acquired from a tissue surface. Each of the main processing steps was shown to be capable of real-time processing (> 30 frames per second), highlighting the feasibility of FLImBrush for intraoperative imaging and surgical guidance. Current findings show the feasibility of integrating FLImBrush into a range of surgical applications including cancer margins assessment during head and neck surgery.

Real-time diagnosis and visualization of tumor margins in excised breast specimens using fluorescence lifetime imaging and machine learning

Tumor-free surgical margins are critical in breast-conserving surgery. In up to 38% of the cases, however, patients undergo a second surgery since malignant cells are found at the margins of the excised resection specimen. Thus, advanced imaging tools are needed to ensure clear margins at the time of surgery. The objective of this study was to evaluate a random forest classifier that makes use of parameters derived from point-scanning label-free fluorescence lifetime imaging (FLIm) measurements of breast specimens as a means to diagnose tumor at the resection margins and to enable an intuitive visualization of a probabilistic classifier on tissue specimen. FLIm data from fresh lumpectomy and mastectomy specimens from 18 patients were used in this study. The supervised training was based on a previously developed registration technique between autofluorescence imaging data and cross-sectional histology slides. A pathologist's histology annotations provide the ground truth to distinguish between adipose, fibrous, and tumor tissue. Current results demonstrate the ability of this approach to classify the tumor with 89% sensitivity and 93% specificity and to rapidly (∼ 20 frames per second) overlay the probabilistic classifier overlaid on excised breast specimens using an intuitive color scheme. Furthermore, we show an iterative imaging refinement that allows surgeons to switch between rapid scans with a customized, low spatial resolution to quickly cover the specimen and slower scans with enhanced resolution (400 μm per point measurement) in suspicious regions where more details are required. In summary, this technique provides high diagnostic prediction accuracy, rapid acquisition, adaptive resolution, nondestructive probing, and facile interpretation of images, thus holding potential for clinical breast imaging based on label-free FLIm.