Co-registration of intra-operative brain surface photographs and pre-operative MR images

Ultrasensitive Optical Detection and Elimination of Residual Microtumors with a Postoperative Implantable Hydrogel Sensor for Preventing Cancer Recurrence

In vivo optical imaging of trace biomarkers in residual microtumors holds significant promise for cancer prognosis but poses a formidable challenge. Here, a novel hydrogel sensor is designed for ultrasensitive and specific imaging of the elusive biomarker. This hydrogel sensor seamlessly integrates a molecular beacon nanoprobe with fibroblasts, offering both high tissue retention capability and an impressive signal-to-noise ratio for imaging. Signal amplification is accomplished through exonuclease I-mediated biomarker recycling. The resulting hydrogel sensor sensitively detects the biomarker carcinoembryonic antigen with a detection limit of 1.8 pg mL-1 in test tubes. Moreover, it successfully identifies residual cancer nodules with a median diameter of less than 2 mm in mice bearing partially removed primary triple-negative breast carcinomas (4T1). Notably, this hydrogel sensor is proven effective for the sensitive diagnosis of invasive tumors in post-surgical mice with infiltrating 4T1 cells, leveraging the role of fibroblasts in locally enriching tumor cells. Furthermore, the residual microtumor is rapidly photothermal ablation by polydopamine-based nanoprobe under the guidance of visualization, achieving ≈100% suppression of tumor recurrence and lung metastasis. This work offers a promising alternative strategy for visually detecting residual microtumors, potentially enhancing the prognosis of cancer patients following surgical interventions.

Image-to-Patient Registration in Computer-Assisted Surgery of Head and Neck: State-of-the-Art, Perspectives, and Challenges

Today, image-guided systems play a significant role in improving the outcome of diagnostic and therapeutic interventions. They provide crucial anatomical information during the procedure to decrease the size and the extent of the approach, to reduce intraoperative complications, and to increase accuracy, repeatability, and safety. Image-to-patient registration is the first step in image-guided procedures. It establishes a correspondence between the patient's preoperative imaging and the intraoperative data. When it comes to the head-and-neck region, the presence of many sensitive structures such as the central nervous system or the neurosensory organs requires a millimetric precision. This review allows evaluating the characteristics and the performances of different registration methods in the head-and-neck region used in the operation room from the perspectives of accuracy, invasiveness, and processing times. Our work led to the conclusion that invasive marker-based methods are still considered as the gold standard of image-to-patient registration. The surface-based methods are recommended for faster procedures and applied on the surface tissues especially around the eyes. In the near future, computer vision technology is expected to enhance these systems by reducing human errors and cognitive load in the operating room.

Development of a New Image-Guided Neuronavigation System: Mixed-Reality Projection Mapping Is Accurate and Feasible

BACKGROUND

Image-guided systems improve the safety, functional outcome, and overall survival of neurosurgery but require extensive equipment.

OBJECTIVE

To develop an image-guided surgery system that combines the brain surface photographic texture (BSP-T) captured during surgery with 3-dimensional computer graphics (3DCG) using projection mapping.

METHODS

Patients who underwent initial surgery with brain tumors were prospectively enrolled. The texture of the 3DCG (3DCG-T) was obtained from 3DCG under similar conditions as those when capturing the brain surface photographs. The position and orientation at the time of 3DCG-T acquisition were used as the reference. The correct position and orientation of the BSP-T were obtained by aligning the BSP-T with the 3DCG-T using normalized mutual information. The BSP-T was combined with and displayed on the 3DCG using projection mapping. This mixed-reality projection mapping (MRPM) was used prospectively in 15 patients (mean age 46.6 yr, 6 males). The difference between the centerlines of surface blood vessels on the BSP-T and 3DCG constituted the target registration error (TRE) and was measured in 16 fields of the craniotomy area. We also measured the time required for image processing.

RESULTS

The TRE was measured at 158 locations in the 15 patients, with an average of 1.19 ± 0.14 mm (mean ± standard error). The average image processing time was 16.58 min.

CONCLUSION

Our MRPM method does not require extensive equipment while presenting information of patients' anatomy together with medical images in the same coordinate system. It has the potential to improve patient safety.

Towards in-vivo label-free detection of brain tumor margins with epi-illumination tomographic quantitative phase imaging

Brain tumor surgery involves a delicate balance between maximizing the extent of tumor resection while minimizing damage to healthy brain tissue that is vital for neurological function. However, differentiating between tumor, particularly infiltrative disease, and healthy brain in-vivo remains a significant clinical challenge. Here we demonstrate that quantitative oblique back illumination microscopy (qOBM)-a novel label-free optical imaging technique that achieves tomographic quantitative phase imaging in thick scattering samples-clearly differentiates between healthy brain tissue and tumor, including infiltrative disease. Data from a bulk and infiltrative brain tumor animal model show that qOBM enables quantitative phase imaging of thick fresh brain tissues with remarkable cellular and subcellular detail that closely resembles histopathology using hematoxylin and eosin (H&E) stained fixed tissue sections, the gold standard for cancer detection. Quantitative biophysical features are also extracted from qOBM which yield robust surrogate biomarkers of disease that enable (1) automated tumor and margin detection with high sensitivity and specificity and (2) facile visualization of tumor regions. Finally, we develop a low-cost, flexible, fiber-based handheld qOBM device which brings this technology one step closer to in-vivo clinical use. This work has significant implications for guiding neurosurgery by paving the way for a tool that delivers real-time, label-free, in-vivo brain tumor margin detection.

Ultrabright gap-enhanced Raman tags for high-speed bioimaging

Surface-enhanced Raman spectroscopy (SERS) is advantageous over fluorescence for bioimaging due to ultra-narrow linewidth of the fingerprint spectrum and weak photo-bleaching effect. However, the existing SERS imaging speed lags far behind practical needs, mainly limited by Raman signals of SERS nanoprobes. In this work, we report ultrabright gap-enhanced Raman tags (GERTs) with strong electromagnetic hot spots from interior sub-nanometer gaps and external petal-like shell structures, larger immobilization surface area, and Raman cross section of reporter molecules. These GERTs reach a Raman enhancement factor beyond 5 × 10⁹ and a detection sensitivity down to a single-nanoparticle level. We use a 370 μW laser to realize high-resolution cell imaging within 6 s and high-contrast (a signal-to-background ratio of 80) wide-area (3.2 × 2.8 cm²) sentinel lymph node imaging within 52 s. These nanoprobes offer a potential solution to overcome the current bottleneck in the field of SERS-based bioimaging.

The speed of surface-enhanced Raman spectroscopy (SERS) imaging is generally limited due to low Raman signals. Here, the authors develop bright gap-enhanced Raman tags with external hot spots and demonstrate their use in fast near-infrared bioimaging.

Intraoperative Detection and Eradication of Residual Microtumors with Gap-Enhanced Raman Tags

The inability to intraoperatively diagnose and eliminate microscopic residual tumors represents a significant challenge in cancer surgery. These residual microtumors cause lethal recurrence and metastasis. Herein, we show a crucial example of Raman imaging with gap-enhanced Raman tags (GERTs) to serve as a robust platform for intraoperative detection and eradication of residual microscopic foci, which exist in surgical margins, tumor invasion, and multifocal tumor spread. The GERTs feature gap-enhanced gold core-shell nanostructures, with Raman reporters embedding inside the interior gap junction. This nanostructure elicits highly sensitive and photostable Raman signals for microtumor detection by applying a 785 nm, low-energy laser and produces hyperthermia effects for microtumor ablation upon switching a 808 nm, high-power laser. In the orthotopic prostate metastasis tumor model, systematic delivery of GERTs enabled precise imaging and real-time ablation of macroscopic malignant lesions around the surgical bed without damaging normal tissues. Consequently, the GERTs-based surgery prevented local recurrence and delivered 100% tumor-free survival. These results suggest the efficiency of theranostic GERTs for precise detection and removal of residual miroctumors, broadening the avenues to apply Raman-based imaging for theranostic precision medicine.

Framework for 2D-3D image fusion of infrared thermography with preoperative MRI

Multimodal medical image fusion combines information of one or more images in order to improve the diagnostic value. While previous applications mainly focus on merging images from computed tomography, magnetic resonance imaging (MRI), ultrasonic and single-photon emission computed tomography, we propose a novel approach for the registration and fusion of preoperative 3D MRI with intraoperative 2D infrared thermography. Image-guided neurosurgeries are based on neuronavigation systems, which further allow us track the position and orientation of arbitrary cameras. Hereby, we are able to relate the 2D coordinate system of the infrared camera with the 3D MRI coordinate system. The registered image data are now combined by calibration-based image fusion in order to map our intraoperative 2D thermographic images onto the respective brain surface recovered from preoperative MRI. In extensive accuracy measurements, we found that the proposed framework achieves a mean accuracy of 2.46 mm.

Mesh-to-raster region-of-interest-based nonrigid registration of multimodal images

Region of interest (RoI) alignment in medical images plays a crucial role in diagnostics, procedure planning, treatment, and follow-up. Frequently, a model is represented as triangulated mesh while the patient data is provided from computed axial tomography scanners as pixel or voxel data. Previously, we presented a 2-D method for curve-to-pixel registration. This paper contributes (i) a general mesh-to-raster framework to register RoIs in multimodal images; (ii) a 3-D surface-to-voxel application, and (iii) a comprehensive quantitative evaluation in 2-D using ground truth (GT) provided by the simultaneous truth and performance level estimation (STAPLE) method. The registration is formulated as a minimization problem, where the objective consists of a data term, which involves the signed distance function of the RoI from the reference image and a higher order elastic regularizer for the deformation. The evaluation is based on quantitative light-induced fluoroscopy (QLF) and digital photography (DP) of decalcified teeth. STAPLE is computed on 150 image pairs from 32 subjects, each showing one corresponding tooth in both modalities. The RoI in each image is manually marked by three experts (900 curves in total). In the QLF-DP setting, our approach significantly outperforms the mutual information-based registration algorithm implemented with the Insight Segmentation and Registration Toolkit and Elastix.

Sources of Variation Influencing Concordance between Functional MRI and Direct Cortical Stimulation in Brain Tumor Surgery

Object: Preoperative functional magnetic resonance imaging (fMRI) remains a promising method to aid in the surgical management of patients diagnosed with brain tumors. For patients that are candidates for awake craniotomies, surgical decisions can potentially be improved by fMRI but this depends on the level of concordance between preoperative brain maps and the maps provided by the gold standard intraoperative method, direct cortical stimulation (DCS). There have been numerous studies of the concordance between fMRI and DCS using sensitivity and specificity measures, however the results are variable across studies and the key factors influencing variability are not well understood. Thus, the present work addresses the influence of technical factors on fMRI and DCS concordance. Methods: Motor and language mapping data were collected for a group of glioma patients (n = 14) who underwent both preoperative fMRI and intraoperative DCS in an awake craniotomy procedure for tumor removal. Normative fMRI data were also acquired in a healthy control group (n = 12). The fMRI and DCS mapping data were co-registered; true positive (TP), true negative (TN), false positive (FP), and false negative (FN) occurrences were tabulated over the exposed brain surface. Sensitivity and specificity were measured for the total group, and for the motor and language sub-groups. The influence of grid placement, fMRI statistical thresholding, and task standardization were assessed. Correlations between proportions of agreement and error were also carefully scrutinized to evaluate concordance in more detail. Results: Concordance was significantly better for motor vs. language mapping. There was an inverse relationship between TP and TN with increasing statistical threshold, and FP dominated the total error. Sensitivity and specificity were reduced when tasks were not standardized across fMRI and DCS. Conclusions: Although the agreement between fMRI and DCS is good, variability is introduced by technical factors that can diminish the quality of patient data. Neurosurgeons should evaluate the usefulness of fMRI data while considering that (a) discordance arises primarily from FP fMRI results; (b) there is an inherent trade-off between sensitivity and specificity with fMRI statistical threshold; and

Superficial vessel reconstruction with a multiview camera system

We aim at reconstructing superficial vessels of the brain. Ultimately, they will serve to guide the deformation methods to compensate for the brain shift. A pipeline for three-dimensional (3-D) vessel reconstruction using three mono-complementary metal-oxide semiconductor cameras has been developed. Vessel centerlines are manually selected in the images. Using the properties of the Hessian matrix, the centerline points are assigned direction information. For correspondence matching, a combination of methods was used. The process starts with epipolar and spatial coherence constraints (geometrical constraints), followed by relaxation labeling and an iterative filtering where the 3-D points are compared to surfaces obtained using the thin-plate spline with decreasing relaxation parameter. Finally, the points are shifted to their local centroid position. Evaluation in virtual, phantom, and experimental images, including intraoperative data from patient experiments, shows that, with appropriate camera positions, the error estimates (root-mean square error and mean error) are [Formula: see text].

Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy

Differentiating tumor from normal brain is a major barrier to achieving optimal outcome in brain tumor surgery. New imaging techniques for visualizing tumor margins during surgery are needed to improve surgical results. We recently demonstrated the ability of stimulated Raman scattering (SRS) microscopy, a nondestructive, label-free optical method, to reveal glioma infiltration in animal models. We show that SRS reveals human brain tumor infiltration in fresh, unprocessed surgical specimens from 22 neurosurgical patients. SRS detects tumor infiltration in near-perfect agreement with standard hematoxylin and eosin light microscopy (κ = 0.86). The unique chemical contrast specific to SRS microscopy enables tumor detection by revealing quantifiable alterations in tissue cellularity, axonal density, and protein/lipid ratio in tumor-infiltrated tissues. To ensure that SRS microscopic data can be easily used in brain tumor surgery, without the need for expert interpretation, we created a classifier based on cellularity, axonal density, and protein/lipid ratio in SRS images capable of detecting tumor infiltration with 97.5% sensitivity and 98.5% specificity. Quantitative SRS microscopy detects the spread of tumor cells, even in brain tissue surrounding a tumor that appears grossly normal. By accurately revealing tumor infiltration, quantitative SRS microscopy holds potential for improving the accuracy of brain tumor surgery.

Smoothing of contact lines in spreading droplets by trisiloxane surfactants and its relevance for superspreading

Superspreading, the greatly enhanced spreading of aqueous solutions of trisiloxane surfactants on hydrophobic substrates, is of great interest in fundamental physics and technical applications. Despite numerous studies in the last 20 years, the superspreading mechanism is still not well understood, largely because the molecular scale cannot be resolved appropriately either experimentally or using continuum simulations. The absence of molecular-scale knowledge has led to a series of conflicting hypotheses based on different assumptions of surfactant behavior. We report a series of large-scale molecular dynamics simulations of aqueous solutions of superspreading and non-superspreading surfactants on different substrates. We find that the transition from the liquid-vapor to the solid-liquid interface is smooth for superspreading conditions, allowing direct adsorption through the contact line. This finding complements a study [Karapetsas et al., J. Fluid Mech., 2011, 670, 5-37], which predicts that superspreading can occur if this adsorption path is possible. Based on the observed mechanism, we provide plausible explanations for the influence of the substrate hydrophobicity, the surfactant chain length, and the surfactant concentration on the superspreading phenomenon. We also briefly address that the observed droplet shape is a mechanism to overcome the Huh-Scriven paradox of infinite viscous dissipation at the contact line.