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FLASH radiotherapy (FLASH-RT) is an emerging ultra-high dose (>40 Gy/s) delivery that promises to improve the therapeutic potential by limiting toxicities compared to conventional RT while maintaining similar tumor eradication efficacy. Image-guidance is an essential component of modern RT that should be harnessed to meet the special emerging needs of FLASH-RT and its associated high risks in planning and delivering of such ultra-high doses in short period of times. Hence, this contribution will elaborate on the imaging requirements and possible solutions in the entire chain of FLASH-RT treatment, from the planning, through the setup and delivery with online in vivo imaging and dosimetry, up to the assessment of biological mechanisms and treatment response. In patient setup and delivery, higher temporal sampling than in conventional RT should ensure that the short treatment is delivered precisely to the targeted region. Additionally, conventional imaging tools such as cone-beam computed tomography (CBCT) will continue to play an important role in improving patient setup prior to delivery, while techniques based on magnetic resonance imaging (MRI) or positron-emission-tomography (PET) may be extremely valuable for either Linac or particle FLASH therapy, to monitor and track anatomical changes during delivery. In either planning or assessing outcomes, quantitative functional imaging could supplement conventional imaging for more accurate utilization of the biological window of the FLASH effect, selecting for or verifying things such as tissue oxygen and existing or transient hypoxia on the relevant time scales of FLASH-RT delivery. Perhaps most importantly at this time, these tools might help improve the understanding of the biological mechanisms of FLASH-RT response in tumor and normal tissues. The high dose deposition of FLASH provides an opportunity to utilize pulse-to-pulse imaging tools such as Cherenkov or radiation acoustic emission imaging. These could provide individual pulse mapping or assessing the 3D dose delivery superficially or at tissue depth, respectively. In summary, the most promising components of modern RT should be used for safer application of FLASH-RT, and new promising developments could be advanced to cope with its novel demands but also exploit new opportunities in connection with the unique nature of pulsed delivery at unprecedented dose rates, opening a new era of biological image guidance and ultra-fast, pulse-based in vivo dosimetry.

Indocyanine green (ICG)-based dynamic contrast-enhanced fluorescence imaging (DCE-FI) can objectively assess bone perfusion intraoperatively. However, it is susceptible to motion artifacts due to patient’s involuntary respiration during the 4.5-minute DCE-FI data acquisition. An automated motion correction approach based on mutual information (MI) frameby-frame was developed to overcome this problem. In this approach, MIs were calculated between the reference and the adjacent frame translated and the maximal MI corresponded to the optimal translation. The images obtained from eighteen amputation cases were utilized to validate the approach and the results show that this correction can significantly reduce the motion artifacts and can improve the accuracy of bone perfusion assessment.

Cherenkov images can be used for the quality assurance of dose homogeneity in total skin electron therapy (TSET). For the dose mapping purpose, this study reconstructed the patient model from 3D scans using registration algorithms and computer animation techniques. The Cherenkov light emission of the patient’s surface was extracted from multi-view Cherenkov images, converted into dose distribution, and projected onto the patient’s 3D model, allowing for dose cumulation and evaluation. The projected result from multiple Cherenkov cameras provides additional information about Cherenkov emission on the sides of the patients, which improves the agreement between the Cherenkov converted dose and the OSLD measurements.

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Details of Selfrec-Net and the framework of DSL

Classical fluorescence guided surgery uses long laser pulses to excite fluorescent tracers, only providing the practitioner with 2D information. In this work, we develop and test a 3D imaging technique using LiDAR technology to sense target tissue depths up to 5 mm below the surface. Imaging through highly scattering medium like tissues implies that temporal information used for 3D reconstruction is convolved with diffuse dynamics of the medium. Using diffuse reflectance as an indicator of the medium’s optical properties, correction of the time-of-flight is made possible. Time-of-flight fluorescence imaging, captures intensity as well as temporal profile of fluorescence excited by ultra-short pulses.

ICG-based dynamic contrast-enhanced fluorescence imaging (DCE-FI) and intraoperative DCE- magnetic resonance imaging (MRI) have been carried out nearly simultaneously in three lower extremity bone infection cases to investigate the relationship between these two imaging modalities for assessing bone blood perfusion during open orthopedic surgeries. Time-intensity curves in the corresponding regions of interest of two modalities were derived for comparison. The results demonstrated that ICG-based DCE-FI has higher sensitivity to perfusion changes while DCE-MRI provides superior and supplemental depth-related perfusion information. Research applying the depth-related perfusion information derived from MRI to improve the overall analytic modeling of intraoperative DCE-FI is ongoing.

Supplemental Figures and Table

In this study, a radiomics approach was extended to optical fluorescence molecular imaging data for tissue classification, termed 'optomics'. Fluorescence molecular imaging is emerging for precise surgical guidance during head and neck squamous cell carcinoma (HNSCC) resection. However, the tumor-to-normal tissue contrast is confounded by intrinsic physiological limitations of heterogeneous expression of the target molecule, epidermal growth factor receptor (EGFR). Optomics seek to improve tumor identification by probing textural pattern differences in EGFR expression conveyed by fluorescence. A total of 1,472 standardized optomic features were extracted from fluorescence image samples. A supervised machine learning pipeline involving a support vector machine classifier was trained with 25 top-ranked features selected by minimum redundancy maximum relevance criterion. Model predictive performance was compared to fluorescence intensity thresholding method by classifying testing set image patches of resected tissue with histologically confirmed malignancy status. The optomics approach provided consistent improvement in prediction accuracy on all test set samples, irrespective of dose, compared to fluorescence intensity thresholding method (mean accuracies of 89% vs. 81%; P = 0.0072). The improved performance demonstrates that extending the radiomics approach to fluorescence molecular imaging data offers a promising image analysis technique for cancer detection in fluorescence-guided surgery., Comment: 21 pages, 8 figures, 1 table, submitted as a manuscript at Frontiers in Medical Technology

Objective: In this study, a fast imaging technique was developed for the first in vivo Cherenkov emission imaging from an ultra-high dose rate (UHDR) electron beam source at single pulse (360 Hz) submillimeter resolution. Approach: A CMOS camera, gated to the UHDR LINAC, imaged the Cherenkov emission profiles pulse by pulse passively during the irradiation of mice on their limbs and intestinal region. The utility of an intensifier was investigated for its effect on image quality including signal to noise and spatial resolution. Pulse by pulse variability in Cherenkov emission profile were quantified spatially and temporally. Main results: An intensifier improved the emission profile signal to noise ratio from 15 to 280, with reduced spatial resolution. The profile extended beyond of the treatment field due to the lateral scattering of the electrons in tissue and its optical properties. The CMOS camera with an intensifier detected the changes in Cherenkov emission profile during expiration and inspiration of the respiration cycle for the mice to be about 3 mm. Significance: This fast imaging technique can be utilized for in vivo intrafraction monitoring of FLASH patient treatments at single pulse resolution. It can display delivery differences during respiration, and variability in the delivered treatment's surface profile, which may perturb from the intended UHDR treatment more for pencil beam scanning systems. The technique may leverage Cherenkov emission surface profile to gate the treatment delivery via respiratory gating systems under FLASH conditions., Comment: 16 pages, 3 figures

Fluorescence imaging is an emerging imaging technique that has shown many benefits for clinical care. Currently, the field is in rapid clinical translation, and an unprecedented number of clinical trials are performed. Clinicians are inundated with numerous opportunities and combinations of different imaging modalities. To streamline this process, a multidisciplinary approach is needed with drug discovery, software and systems engineering, and translational medicine. Here, we discuss the main constituents of a uniform fluorescence imaging protocol to match the clinical need and ensure consistent study designs and reliable data collection in clinical trials. In an era in which the potential of fluorescence imaging has become evident, consistent conduct of studies, data analysis, and data interpretation are essential for implementation into standard of care.

ICG fluorescence maps at each condition of 11th tibia.

The following work presents how autoencoding all the possible hidden activations of a network for a given problem can provide insight about its structure, behavior, and vulnerabilities. The method, termed self-introspection, can show that a trained model showcases similar activation patterns (albeit randomly distributed due to initialization) when shown data belonging to the same category, and classification errors occur in fringe areas where the activations are not as clearly defined, suggesting some form of random, slowly varying, implicit encoding occurring within deep networks, that can be observed with this representation. Additionally, obtaining a low-dimensional representation of all the activations allows for (1) real-time model evaluation in the context of a multiclass classification problem, (2) the rearrangement of all hidden layers by their relevance in obtaining a specific output, and (3) the obtainment of a framework where studying possible counter-measures to noise and adversarial attacks is possible. Self-introspection can show how damaged input data can modify the hidden activations, producing an erroneous response. A few illustrative are implemented for feedforward and convolutional models and the MNIST and CIFAR-10 datasets, showcasing its capabilities as a model evaluation framework., Comment: 16 pages, 7 figures

Considerable advances in cancer-specific optical imaging have improved the precision of tumor resection. In comparison to traditional imaging modalities, this technology is unique in its ability to provide real-time feedback to the operating surgeon. Given the significant clinical implications of optical imaging, there is an urgent need to standardize surgical navigation tools and contrast agents to facilitate swift regulatory approval. Because fluorescence-enhanced surgery requires a combination of both device and drug, each may be developed in conjunction, or separately, which are important considerations in the approval process. This report is the result of a one-day meeting held on May 4, 2016 with officials from the National Cancer Institute, the FDA, members of the American Society of Image-Guided Surgery, and members of the World Molecular Imaging Society, which discussed consensus methods for FDA-directed human testing and approval of investigational optical imaging devices as well as contrast agents for surgical applications. The goal of this workshop was to discuss FDA approval requirements and the expectations for approval of these novel drugs and devices, packaged separately or in combination, within the context of optical surgical navigation. In addition, the workshop acted to provide clarity to the research community on data collection and trial design. Reported here are the specific discussion items and recommendations from this critical and timely meeting. Cancer Res; 77(9); 2197-206. ©2017 AACR.

Complete MRI and optical data from 24 patients analyzed. Data in the DCE and T2 + DWI columns are the results of radiologist interpretation, where “1” and “0” indicate malignant and benign diagnoses, respectively. Data in DCE-NIRST and T2-NIRST columns are the contrast ratio of HbT in the abnormal ROI relative to the rest of the breast. (PDF 32 kb)

Nanoscale drug delivery vehicles can facilitate multimodal therapies of cancer by promoting tumour-selective drug release. However, few are effective because cancer cells develop ways to resist and evade treatment. Here, we introduce a photoactivable multi-inhibitor nanoliposome (PMIL) that imparts light-induced cytotoxicity in synchrony with a photoinitiated and sustained release of inhibitors that suppress tumour regrowth and treatment escape signalling pathways. The PMIL consists of a nanoliposome doped with a photoactivable chromophore (benzoporphyrin derivative, BPD) in the lipid bilayer, and a nanoparticle containing cabozantinib (XL184)--a multikinase inhibitor--encapsulated inside. Near-infrared tumour irradiation, following intravenous PMIL administration, triggers photodynamic damage of tumour cells and microvessels, and simultaneously initiates release of XL184 inside the tumour. A single PMIL treatment achieves prolonged tumour reduction in two mouse models and suppresses metastatic escape in an orthotopic pancreatic tumour model. The PMIL offers new prospects for cancer therapy by enabling spatiotemporal control of drug release while reducing systemic drug exposure and associated toxicities.

Multi-spectral scatter visualization of tissue ultrastructure in situ can provide a unique tool for guiding surgical tumor resection. The variations in scattering parameters, i.e. scattering power, scattering amplitude and average scattered intensity, across different tissue types has been analyzed. Since scatter changes are subtle, tissue sub-type identification requires multiparametric analysis of optical data to help in tumor delineation. The proposed methodology has been validated on tissue types observed across pancreatic tumor samples that were pathologically classified under three major groups (epithelium, fibrosis and necrosis) with their corresponding subtypes. This methodology combines a statistical pre-processing of the scattering parameters and an ensemble segmentation method. The latter merges the predictions of k-nearest neighbors (kNN) and Artificial Neural Network (ANN) algorithms for tissue type classification. The classification accuracy inside some predefined regions of interest was determined. Results show a strong correlation between the automated and expert-based classifications.

A lack of accepted standards and standardized phantoms suitable for the technical validation of biophotonic instrumentation hinders the reliability and reproducibility of its experimental outputs. In this Perspective, we discuss general criteria for the design of tissue-mimicking biophotonic phantoms, and use these criteria and state-of-the-art developments to critically review the literature on phantom materials and on the fabrication of phantoms. By focusing on representative examples of standardization in diffuse optical imaging and spectroscopy, fluorescence-guided surgery and photoacoustic imaging, we identify unmet needs in the development of phantoms and a set of criteria (leveraging characterization, collaboration, communication and commitment) for the standardization of biophotonic instrumentation.