Super-Resolution Ultrasound Imaging for Monitoring the Therapeutic Efficacy of a Vascular Disrupting Agent in an Animal Model of Breast Cancer.

OBJECTIVE: Evaluate the use of super-resolution ultrasound (SRUS) imaging for the early detection of tumor response to treatment using a vascular-disrupting agent (VDA). METHODS: A population of 28 female nude athymic mice (Charles River Laboratories) were implanted with human breast cancer cells (MDA-MB-231, ATCC) in the mammary fat pad and allowed to grow. Ultrasound imaging was performed using a Vevo 3100 scanner (FUJIFILM VisualSonics Inc) equipped with the MX250 linear array transducer immediately before and after receiving bolus injections of a microbubble (MB) contrast agent (Definity, Lantheus Medical Imaging) via the tail vein. Following baseline ultrasound imaging, VDA drug (combretastatin A4 phosphate, CA4P, Sigma Aldrich) or control saline was injected via the placed catheter. After 4 or 24 hours, repeat ultrasound imaging along the same tumor cross-section occurred. Direct intratumoral pressure measurements were obtained using a calibrated sensor. All raw ultrasound data were saved for offline processing and SRUS image reconstruction using custom MATLAB software (MathWorks Inc). From a region encompassing the tumor space and the entire postprocessed ultrasound image sequence, time MB count (TMC) curves were generated in addition to traditional SRUS maps reflecting MB enumeration at each pixel location. Peak enhancement (PE) and wash-in rate (WIR) were extracted from these TMC curves. At termination, intratumoral microvessel density (MVD) was quantified using tomato lectin labeling of patent blood vessels. RESULTS: SRUS images exhibited a clear difference between control and treated tumors. While there was no difference in any group parameters at baseline (0 hour, P > .09), both SRUS-derived PE and WIR measurements in tumors treated with VDA exhibited significant decreases by 4 (P = .03 and P = .05, respectively) and 24 hours (P = .02 and P = .01, respectively), but not in control group tumors (P > .22). Similarly, SRUS derived microvascular maps were not different at baseline (P = .81), but measures of vessel density were lower in treated tumors at both 4 and 24 hours (P < .04). An inverse relationship between intratumoral pressure and both PE and WIR parameters were found in control tumors (R2 > .09, P < .03). CONCLUSION: SRUS imaging is a new modality for assessing tumor response to treatment using a VDA.

Critical Advances for Democratizing Ultrasound Diagnostics in Human and Veterinary Medicine.

The democratization of ultrasound imaging refers to the process of making ultrasound technology more accessible. Traditionally, ultrasound imaging has been predominately used in specialized medical facilities by trained professionals. Advancements in technology and changes in the health-care landscape have inspired efforts to broaden the availability of ultrasound imaging to various settings such as remote and resource-limited areas. In this review, we highlight several key factors that have contributed to the ongoing democratization of ultrasound imaging, including portable and handheld devices, recent advancements in technology, and training and education. Examples of diagnostic point-of-care ultrasound (POCUS) imaging used in emergency and critical care, gastroenterology, musculoskeletal applications, and other practices are provided for both human and veterinary medicine. Open challenges and the future of POCUS imaging are presented, including the emerging role of artificial intelligence in technology development. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 26 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Multiparametric ultrasound imaging for early-stage steatosis: Comparison with magnetic resonance imaging-based proton density fat fraction.

BACKGROUND: The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR. PURPOSE: This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging-based proton density fat fraction (MRI-PDFF) for hepatic steatosis assessment. METHODS: We investigated early-stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI-PDFF; histology fat percentages. Seven individual US parameters were extracted using B-mode measurement, Burr distribution estimation, attenuation estimation, H-scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease-specific imaging (DSI). RESULTS: The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p-value < 0.05) and outperforms the correlation between MRI-PDFF and histology (R = 0.89, p-value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI-PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color-highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p-value < 0.05). CONCLUSIONS: We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI-PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans.

A single photodynamic priming protocol augments delivery of ⍺-PD-L1 mAbs and induces immunogenic cell death in head and neck tumors.

Photodynamic priming (PDP) leverages the photobiological effects of subtherapeutic photodynamic therapy (PDT) regimens to modulate the tumor vasculature and stroma. PDP also sensitizes tumors to secondary therapies, such as immunotherapy by inducing a cascade of molecular events, including immunogenic cell death (ICD). We and others have shown that PDP improves the delivery of antibodies, among other theranostic agents. However, it is not known whether a single PDP protocol is capable of both inducing ICD in vivo and augmenting the delivery of immune checkpoint inhibitors. In this rapid communication, we show for the first time that a single PDP protocol using liposomal benzoporphyrin derivative (Lipo-BPD, 0.25 mg/kg) with 690 nm light (75 J/cm2 , 100 mW/cm2 ) simultaneously doubles the delivery of ⍺-PD-L1 antibodies in murine AT-84 head and neck tumors and induces ICD in vivo. ICD was observed as a 3-11 fold increase in tumor cell exposure of damage-associated molecular patterns (Calreticulin, HMGB1, and HSP70). These findings suggest that this single, highly translatable PDP protocol using clinically relevant Lipo-BPD holds potential for improving immunotherapy outcomes in head and neck cancer. It can do so by simultaneously overcoming physical barriers to the delivery of immune checkpoint inhibitors, and biochemical barriers that contribute to immunosuppression.

Endothelial ERα promotes glucose tolerance by enhancing endothelial insulin transport to skeletal muscle.

The estrogen receptor (ER) designated ERα has actions in many cell and tissue types that impact glucose homeostasis. It is unknown if these include mechanisms in endothelial cells, which have the potential to influence relative obesity, and processes in adipose tissue and skeletal muscle that impact glucose control. Here we show that independent of impact on events in adipose tissue, endothelial ERα promotes glucose tolerance by enhancing endothelial insulin transport to skeletal muscle. Endothelial ERα-deficient male mice are glucose intolerant and insulin resistant, and in females the antidiabetogenic actions of estradiol (E2) are absent. The glucose dysregulation is due to impaired skeletal muscle glucose disposal that results from attenuated muscle insulin delivery. Endothelial ERα activation stimulates insulin transcytosis by skeletal muscle microvascular endothelial cells. Mechanistically this involves nuclear ERα-dependent upregulation of vesicular trafficking regulator sorting nexin 5 (SNX5) expression, and PI3 kinase activation that drives plasma membrane recruitment of SNX5. Thus, coupled nuclear and non-nuclear actions of ERα promote endothelial insulin transport to skeletal muscle to foster normal glucose homeostasis.

Optical blood-brain-tumor barrier modulation expands therapeutic options for glioblastoma treatment.

The treatment of glioblastoma has limited clinical progress over the past decade, partly due to the lack of effective drug delivery strategies across the blood-brain-tumor barrier. Moreover, discrepancies between preclinical and clinical outcomes demand a reliable translational platform that can precisely recapitulate the characteristics of human glioblastoma. Here we analyze the intratumoral blood-brain-tumor barrier heterogeneity in human glioblastoma and characterize two genetically engineered models in female mice that recapitulate two important glioma phenotypes, including the diffusely infiltrative tumor margin and angiogenic core. We show that pulsed laser excitation of vascular-targeted gold nanoparticles non-invasively and reversibly modulates the blood-brain-tumor barrier permeability (optoBBTB) and enhances the delivery of paclitaxel in these two models. The treatment reduces the tumor volume by 6 and 2.4-fold and prolongs the survival by 50% and 33%, respectively. Since paclitaxel does not penetrate the blood-brain-tumor barrier and is abandoned for glioblastoma treatment following its failure in early-phase clinical trials, our results raise the possibility of reevaluating a number of potent anticancer drugs by combining them with strategies to increase blood-brain-tumor barrier permeability. Our study reveals that optoBBTB significantly improves therapeutic delivery and has the potential to facilitate future drug evaluation for cancers in the central nervous system.

Simultaneous imaging of ultrasonic relative backscatter and attenuation coefficients for quantitative liver steatosis assessment.

Prevalence of liver disease is continuously increasing and nonalcoholic fatty liver disease (NAFLD) is the most common etiology. We present an approach to detect the progression of liver steatosis based on quantitative ultrasound (QUS) imaging. This study was performed on a group of 55 rats that were subjected to a control or methionine and choline deficient (MCD) diet known to induce NAFLD. Ultrasound (US) measurements were performed at 2 and 6 weeks. Thereafter, animals were humanely euthanized and livers excised for histological analysis. Relative backscatter and attenuation coefficients were simultaneously estimated from the US data and envelope signal-to-noise ratio was calculated to train a regression model for: (1) fat fraction percentage estimation and (2) performing classification according to Brunt's criteria in grades (0 <5%; 1, 5-33%; 2, >33-66%; 3, >66%) of liver steatosis. The trained regression model achieved an [Formula: see text] of 0.97 (p-value < 0.01) and a RMSE of 3.64. Moreover, the classification task reached an accuracy of 94.55%. Our results suggest that in vivo QUS is a promising noninvasive imaging modality for the early assessment of NAFLD.

Image-guided focused ultrasound-mediated molecular delivery to breast cancer in an animal model.

Tumors become inoperable due to their size or location, making neoadjuvant chemotherapy the primary treatment. However, target tissue accumulation of anticancer agents is limited by the physical barriers of the tumor microenvironment. Low-intensity focused ultrasound (FUS) in combination with microbubble (MB) contrast agents can increase microvascular permeability and improve drug delivery to the target tissue after systemic administration. The goal of this research was to investigate image-guided FUS-mediated molecular delivery in volume space. Three-dimensional (3-D) FUS therapy functionality was implemented on a programmable ultrasound scanner (Vantage 256, Verasonics Inc.) equipped with a linear array for image guidance and a 128-element therapy transducer (HIFUPlex-06, Sonic Concepts). FUS treatment was performed on breast cancer-bearing female mice (N= 25). Animals were randomly divided into three groups, namely, 3-D FUS therapy, two-dimensional (2-D) FUS therapy, or sham (control) therapy. Immediately prior to the application of FUS therapy, animals received a slow bolus injection of MBs (Definity, Lantheus Medical Imaging Inc.) and near-infrared dye (IR-780, surrogate drug) for optical reporting and quantification of molecular delivery. Dye accumulation was monitored viain vivooptical imaging at 0, 1, 24, and 48 h (Pearl Trilogy, LI-COR). Following the 48 h time point, animals were humanely euthanized and tumors excised forex vivoanalyzes. Optical imaging results revealed that 3-D FUS therapy improved delivery of the IR-780 dye by 66.4% and 168.1% at 48 h compared to 2-D FUS (p= 0.18) and sham (p= 0.047) therapeutic strategies, respectively.Ex vivoanalysis revealed similar trends. Overall, 3-D FUS therapy can improve accumulation of a surrogate drug throughout the entire target tumor burden after systemic administration.

Assessment of Transarterial Chemoembolization Using Super-resolution Ultrasound Imaging and a Rat Model of Hepatocellular Carcinoma.

OBJECTIVE: Hepatocellular carcinoma (HCC) is a highly prevalent form of liver cancer diagnosed annually in 600,000 people worldwide. A common treatment is transarterial chemoembolization (TACE), which interrupts the blood supply of oxygen and nutrients to the tumor mass. The need for repeat TACE treatments may be assessed in the weeks after therapy with contrast-enhanced ultrasound (CEUS) imaging. Although the spatial resolution of traditional CEUS has been restricted by the diffraction limit of ultrasound (US), this physical barrier has been overcome by a recent innovation known as super-resolution US (SRUS) imaging. In short, SRUS enhances the visible details of smaller microvascular structures on the 10 to 100 µm scale, which unlocks a host of new clinical opportunities for US. METHODS: In this study, a rat model of orthotopic HCC is introduced and TACE treatment response (to a doxorubicin-lipiodol emulsion) is assessed using longitudinal SRUS and magnetic resonance imaging (MRI) performed at 0, 7 and 14 d. Animals were euthanized at 14 d for histological analysis of excised tumor tissue and determination of TACE response, that is, control, partial response or complete response. CEUS imaging was performed using a pre-clinical US system (Vevo 3100, FUJIFILM VisualSonics Inc.) equipped with an MX201 linear array transducer. After administration of a microbubble contrast agent (Definity, Lantheus Medical Imaging), a series of CEUS images were collected at each tissue cross-section as the transducer was mechanically stepped at 100 µm increments. SRUS images were formed at each spatial position, and a microvascular density metric was calculated. Microscale computed tomography (microCT, OI/CT, MILabs) was used to confirm TACE procedure success, and tumor size was monitored using a small animal MRI system (BioSpec 3T, Bruker Corp.). RESULTS: Although there were no differences at baseline (p > 0.15), both microvascular density levels and tumor size measures from the complete responder cases at 14 d were considerably lower and smaller, respectively, than those in the partial responder or control group animals. Histological analysis revealed tumor-to-necrosis levels of 8.4%, 51.1% and 100%, for the control, partial responder and complete responder groups, respectively (p < 0.005). CONCLUSION: SRUS imaging is a promising modality for assessing early changes in microvascular networks in response to tissue perfusion-altering interventions such as TACE treatment of HCC.

High-Resolution Ultrasound Characterization of Local Scattering in Cancer Tissue.

Ultrasound (US) has afforded an approach to tissue characterization for more than a decade. The challenge is to reveal hidden patterns in the US data that describe tissue function and pathology that cannot be seen in conventional US images. Our group has developed a high-resolution analysis technique for tissue characterization termed H-scan US, an imaging method used to interpret the relative size of acoustic scatterers. In the present study, the objective was to compare local H-scan US image intensity with registered histologic measurements made directly at the cellular level. Human breast cancer cells (MDA-MB 231, American Type Culture Collection, Manassas, VA, USA) were orthotopically implanted into female mice (N = 5). Tumors were allowed to grow for approximately 4 wk before the study started. In vivo imaging of tumor tissue was performed using a US system (Vantage 256, Verasonics Inc., Kirkland, WA, USA) equipped with a broadband capacitive micromachined ultrasonic linear array transducer (Kolo Medical, San Jose, CA, USA). A 15-MHz center frequency was used for plane wave imaging with five angles for spatial compounding. H-scan US image reconstruction involved use of parallel convolution filters to measure the relative strength of backscattered US signals. Color codes were applied to filter outputs to form the final H-scan US image display. For histologic processing, US imaging cross-sections were carefully marked on the tumor surface, and tumors were excised and sliced along the same plane. By use of optical microscopy, whole tumor tissue sections were scanned and digitized after nuclear staining. US images were interpolated to have the same number of pixels as the histology images and then spatially aligned. Each nucleus from the histologic sections was automatically segmented using custom MATLAB software (The MathWorks Inc., Natick, MA, USA). Nuclear size and spacing from the histology images were then compared with local H-scan US image features. Overall, local H-scan US image intensity exhibited a significant correlation with both cancer cell nuclear size (R2 > 0.27, p < 0.001) and the inverse relationship with nuclear spacing (R2 > 0.17, p < 0.001).

Generalized mathematical framework for contrast-enhanced ultrasound imaging with pulse inversion spectral deconvolution.

A generalized mathematical framework for performing contrast-enhanced ultrasound (CEUS) imaging is introduced. Termed pulse inversion spectral deconvolution (PISD), this CEUS approach is founded on Gaussian derivative functions (GDFs). PISD pulses are used to form two inverted pulse sequences, which are then used to filter backscattered ultrasound (US) data for isolation of the nonlinear (NL) microbubble (MB) signal component. An US scanner equipped with a linear array transducer was used for data acquisition. With a vascular flow phantom perfused with MBs, data was collected using PISD and NL-based CEUS imaging. The role of wide-beam transmit aperture size (32 or 64 elements) was also evaluated using an US pulse frequency of 6.25 MHz. Image enhancement was quantified by a contrast-to-noise ratio (CNR). Preliminary in vivo data was collected in the hindlimb and kidney of healthy rats. Overall, in vitro wide-beam CEUS imaging using an aperture size of 64 elements yielded improved CNR values. Specifically, PISD-based CEUS imaging produced CNR values of 37.3 dB. For comparison, CNR values obtained using B-mode US or NL approaches were 2.1 and 12.1 dB, respectively. In vivo results demonstrated that PISD-based CEUS imaging improved vascular visualization compared to the NL imaging strategy.

H-Scan Ultrasound Monitoring of Breast Cancer Response to Chemotherapy and Validation With Diffusion-Weighted Magnetic Resonance Imaging.

OBJECTIVES: H-scan ultrasound (US) imaging is a novel tissue characterization technique to detect apoptosis-induced changes in cancer cells after the initiation of effective drug treatment. The objective of the proposed research was to assess the sensitivity of 3-dimensional (3D) H-scan US technique for monitoring the response of breast cancer-bearing animals to neoadjuvant chemotherapy and correlate results to diffusion-weighted magnetic resonance imaging (DW-MRI) measurements of programmed cancer cell death. METHODS: Experimental studies used female mice (N = 18) implanted with human breast cancer cells. Animals underwent H-scan US and DW-MRI imaging on days 0, 1, 3, 7, and 10. After imaging at day 0, breast tumor-bearing nude mice were treated biweekly with an apoptosis-inducing drug. Texture analysis of H-scan US images explored spatial relationships between local US scattering. At day 10, H-scan measurements were compared with DW-MRI-derived apparent diffusion coefficient (ADC) values and histological findings. RESULTS: H-scan US imaging of low and high dose cisplatin-treated cancer-bearing animals revealed changes in image intensity suggesting a progressive decrease in aggregate US scatterer size that was not observed in control animals. Longitudinal trends discovered in H-scan US result matched with texture analysis and DW-MRI (P < .01). Further, analysis of the H-scan US image intensity and corresponding DW-MRI-derived ADC values revealed a strong linear correlation (R2  = .93, P < .001). These changes were due to cancer cell apoptotic activity and consider as early detectable biomarker during treatment. CONCLUSIONS: The 3D H-scan technique holds promise for assisting clinicians in monitoring the early response of breast cancer tumor to neoadjuvant chemotherapy and adding value to traditional diagnostic ultrasound examinations.

3-D H-scan ultrasound imaging of relative scatterer size using a matrix array transducer and sparse random aperture compounding.

H-scan ultrasound (US) is a high-resolution imaging technique for soft tissue characterization. By acquiring data in volume space, H-scan US can provide insight into subtle tissue changes or heterogenous patterns that might be missed using traditional cross-sectional US imaging approaches. In this study, we introduce a 3-dimensional (3-D) H-scan US imaging technology for voxel-level tissue characterization in simulation and experimentation. Using a matrix array transducer, H-scan US imaging was developed to evaluate the relative size of US scattering aggregates in volume space. Experimental data was acquired using a programmable US system (Vantage 256, Verasonics Inc, Kirkland, WA) equipped with a 1024-element (32 × 32) matrix array transducer (Vermon Inc, Tours, France). Imaging was performed using the full array in transmission. Radiofrequency (RF) data sequences were collected using a sparse random aperture compounding technique with 6 different data compounding approaches. Plane wave imaging at five angles was performed at a center frequency of 8 MHz. Scan conversion and attenuation correction were applied. To generate the 3-D H-scan US images, a convolution filter bank (N = 256) was then used to process the RF data sequences and measure the spectral content of the backscattered US signals before volume reconstruction. Preliminary experimental studies were conducted using homogeneous phantom materials embedded with spherical US scatterers of varying diameter, i.e., 27 to 45, 63 to 75, or 106-126 µm. Both simulated and experimental results revealed that 3-D H-scan US images have a low spatial variance when tested with homogeneous phantom materials. Furthermore, H-scan US is considerably more sensitive than traditional B-mode US imaging for differentiating US scatterers of varying size (p = 0.001 and p = 0.93, respectively). Overall, this study demonstrates the feasibility of 3-D H-scan US imaging using a matrix array transducer for tissue characterization in volume space.

Towards Photodynamic Image-Guided Surgery of Head and Neck Tumors: Photodynamic Priming Improves Delivery and Diagnostic Accuracy of Cetuximab-IRDye800CW.

Fluorescence image-guided surgery (IGS) using antibody conjugates of the fluorophore IRDye800CW have revolutionized the surgical debulking of tumors. Cetuximab, an anti-epidermal growth factor receptor (EGFR) monoclonal antibody, conjugated to IRDye800CW (Cet-IRDye800) is the first molecular targeted antibody probe to be used for IGS in head and neck cancer patients. In addition to surgical debulking, Cetuximab-targeted photodynamic therapy (photoimmunotherapy; PIT) is emerging in the clinic as a powerful modality for head and neck tumor photodestruction. A plethora of other photoactivable agents are also in clinical trials for photodynamic-based therapies of head and neck cancer. Considering the vascular and stromal modulating effects of sub-therapeutic photodynamic therapy, namely photodynamic priming (PDP), this study explores the potential synergy between PDP and IGS for a novel photodynamic image-guided surgery (P-IGS) strategy. To the best of our knowledge, this is the first demonstration that PDP of the tumor microenvironment can augment the tumor delivery of full-length antibodies, namely Cet-IRDye800. In this study, we demonstrate a proof-of-concept that PDP primes orthotopic FaDu human head and neck tumors in mice for P-IGS by increasing the delivery of Cet-IRDye800 by up to 138.6%, by expediting its interstitial accumulation by 10.5-fold, and by increasing its fractional tumor coverage by 49.5% at 1 h following Cet-IRDye800 administration. Importantly, PDP improves the diagnostic accuracy of tumor detection by up to 264.2% with respect to vicinal salivary glands at 1 h. As such, PDP provides a time-to-surgery benefit by reducing the time to plateau 10-fold from 25.7 h to 2.5 h. We therefore propose that a pre-operative PDP regimen can expedite and augment the accuracy of IGS-mediated surgical debulking of head and neck tumors and reduce the time-to-IGS. Furthermore, this P-IGS regimen, can also enable a forward-looking post-operative protocol for the photodestruction of unresectable microscopic disease in the surgical bed. Beyond this scope, the role of PDP in the homogenous delivery of diagnostic, theranostic and therapeutic antibodies in solid tumors is of considerable significance to the wider community.

Photoacoustic graphic equalization and application in characterization of red blood cell aggregates.

A photoacoustic (PA) graphic equalization (PAGE) algorithm was developed to characterize the relative size of optical absorbing aggregates. This technique divides the PA signal into frequency bands related to different-sized optical absorbers. Simulations of a material containing optical absorbing microparticles of varying size were used to assess PAGE performance. Experiments were performed on phantom materials containing microspheres of varying size and concentration. Additional experiments were performed using tubes with fresh clotting blood. PA data was obtained using a Vevo LAZR-X system (FUJIFILM VisualSonics Inc). PAGE imaging of phantoms with varying-sized optical absorbers found a 1.5-fold difference in mean image intensity (p < 0.001). Conversely, PA images from these same materials exhibited no intensity changes (p = 0.68). PAGE imaging results from clotting blood exhibited differences for clot sizes in the range 0.30-0.64 mm (p < 0.001). In summary, PAGE imaging can distinguish optical absorbing aggregates of varying size.

Deep-Tissue Activation of Photonanomedicines: An Update and Clinical Perspectives.

With the continued development of nanomaterials over the past two decades, specialized photonanomedicines (light-activable nanomedicines, PNMs) have evolved to become excitable by alternative energy sources that typically penetrate tissue deeper than visible light. These sources include electromagnetic radiation lying outside the visible near-infrared spectrum, high energy particles, and acoustic waves, amongst others. Various direct activation mechanisms have leveraged unique facets of specialized nanomaterials, such as upconversion, scintillation, and radiosensitization, as well as several others, in order to activate PNMs. Other indirect activation mechanisms have leveraged the effect of the interaction of deeply penetrating energy sources with tissue in order to activate proximal PNMs. These indirect mechanisms include sonoluminescence and Cerenkov radiation. Such direct and indirect deep-tissue activation has been explored extensively in the preclinical setting to facilitate deep-tissue anticancer photodynamic therapy (PDT); however, clinical translation of these approaches is yet to be explored. This review provides a summary of the state of the art in deep-tissue excitation of PNMs and explores the translatability of such excitation mechanisms towards their clinical adoption. A special emphasis is placed on how current clinical instrumentation can be repurposed to achieve deep-tissue PDT with the mechanisms discussed in this review, thereby further expediting the translation of these highly promising strategies.

Three-Dimensional H-Scan Ultrasound Imaging of Early Breast Cancer Response to Neoadjuvant Therapy in a Murine Model.

OBJECTIVES: Three-dimensional (3D) H-scan is a new ultrasound (US) technique that images the relative size of acoustic scatterers. The goal of this research was to evaluate use of 3D H-scan US imaging for monitoring early breast cancer response to neoadjuvant therapy using a preclinical murine model of breast cancer. MATERIALS AND METHODS: Preclinical studies were conducted using luciferase-positive breast cancer-bearing mice (n = 40). Anesthetized animals underwent US imaging at baseline before administration with an apoptosis-inducing drug or a saline control. Image data were acquired using a US scanner equipped with a volumetric transducer following either a shorter- or longer-term protocol. The later included bioluminescent imaging to quantify tumor cell viability. At termination, tumors were excised for ex vivo analysis. RESULTS: In vivo results showed that 3D H-scan US imaging is considerably more sensitive to tumor changes after apoptosis-inducing drug therapy as compared with traditional B-scan US. Although there was no difference at baseline (P > 0.99), H-scan US results from treated tumors exhibited progressive decreases in image intensity (up to 62.2% by day 3) that had a significant linear correlation with cancer cell nuclear size (R2 > 0.51, P < 0.001). Results were validated by histological data and a secondary longitudinal study with survival as the primary end point. DISCUSSION: Experimental results demonstrate that noninvasive 3D H-scan US imaging can detect an early breast tumor response to apoptosis-inducing drug therapy. Local in vivo H-scan US image intensity correlated with cancer cell nuclear size, which is one of the first observable changes of a cancer cell undergoing apoptosis and confirmed using histological techniques. Early imaging results seem to provide prognostic insight on longer-term tumor response. Overall, 3D H-scan US imaging is a promising technique that visualizes the entire tumor and detects breast cancer response at an early stage of therapy.

Disease-Specific Imaging Utilizing Support Vector Machine Classification of H-Scan Parameters: Assessment of Steatosis in a Rat Model.

In medical imaging, quantitative measurements have shown promise in identifying diseases by classifying normal versus pathological parameters from tissues. The support vector machine (SVM) has shown promise as a supervised classification algorithm and has been widely used. However, the classification results typically identify a category of abnormal tissues but do not necessarily differentiate progressive stages of a disease. Moreover, the classification result is typically provided independently as a supplement to medical images, which contributes to an overload of information sources in the clinic. Hence, we propose a new imaging method utilizing the SVM to integrate classification results into medical images. This framework is called disease-specific imaging (DSI) that produces a color overlaid highlight on B-mode ultrasound images indicating the type, location, and severity of pathology from different conditions. In this article, the SVM training was performed to construct hyperplanes that can differentiate normal, fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastases in livers based on ultrasound echoes. Also, cluster centroids for specific diseases define unique disease axes, and the inner product between measured features and any disease axis selected by the SVM quantifies the disease progression. The features were measured from 2794 ultrasound frames using the H-scan analysis, attenuation estimation, and B-mode image analysis. The performance of our proposed DSI method was evaluated for a preclinical model of steatosis ( n = 400 frames). The contribution of each feature was assessed, and the results were compared with ground truth from histology. Moreover, the images generated by our DSI were compared with earlier imaging methods of B-mode, H-scan, and histology. The comparisons demonstrate that DSI images yield higher sensitivity to monitor progressive steatosis than B-mode and H-scan and provide a comparable performance with the histology. For the parameter comparison, DSI and H-scan resulted in similar correlation with histology ( rs = 0.83 ) but higher than attenuation ( rs = 0.73 ) and B-mode ( rs = 0.47 ). Therefore, we conclude that DSI utilizing the SVM applied to steatosis can visually represent the classification results with color highlighting, which can simplify the interpretation of classification compared to the traditional SVM result. We expect that the proposed DSI can be used for any medical imaging modality that can estimate multiple quantitative parameters at high resolution.

Faster super-resolution ultrasound imaging with a deep learning model for tissue decluttering and contrast agent localization.

Super-resolution ultrasound (SR-US) imaging allows visualization of microvascular structures as small as tens of micrometers in diameter. However, use in the clinical setting has been impeded in part by ultrasound (US) acquisition times exceeding a breath-hold and by the need for extensive offline computation. Deep learning techniques have been shown to be effective in modeling the two more computationally intensive steps of microbubble (MB) contrast agent detection and localization. Performance gains by deep networks over conventional methods are more than two orders of magnitude and in addition the networks can localize overlapping MBs. The ability to separate overlapping MBs allows use of higher contrast agent concentrations and reduces US image acquisition time. Herein we propose a fully convolutional neural network (CNN) architecture to perform the operations of MB detection as well as localization in a single model. Termed SRUSnet, the network is based on the MobileNetV3 architecture modified for 3-D input data, minimal convergence time, and high-resolution data output using a flexible regression head. Also, we propose to combine linear B-mode US imaging and nonlinear contrast pulse sequencing (CPS) which has been shown to increase MB detection and further reduce the US image acquisition time. The network was trained within silicodata and tested onin vitrodata from a tissue-mimicking flow phantom, and onin vivodata from the rat hind limb (N = 3). Images were collected with a programmable US system (Vantage 256, Verasonics Inc., Kirkland, WA) using an L11-4v linear array transducer. The network exceeded 99.9% detection accuracy onin silicodata. The average localization accuracy was smaller than the resolution of a pixel (i.e.λ/8). The average processing time on a Nvidia GeForce 2080Ti GPU was 64.5 ms for a 128 × 128-pixel image.

Multiscale computational modeling of cancer growth using features derived from microCT images.

Advances in medical imaging technologies now allow noninvasive image acquisition from individual patients at high spatiotemporal resolutions. A relatively new effort of predictive oncology is to develop a paradigm for forecasting the future status of an individual tumor given initial conditions and an appropriate mathematical model. The objective of this study was to introduce a comprehensive multiscale computational method to predict cancer and microvascular network growth patterns. A rectangular lattice-based model was designed so different evolutionary scenarios could be simulated and for predicting the impact of diffusible factors on tumor morphology and size. Further, the model allows prediction-based simulation of cell and microvascular behavior. Like a single cell, each agent is fully realized within the model and interactions are governed in part by machine learning methods. This multiscale computational model was developed and incorporated input information from in vivo microscale computed tomography (microCT) images acquired from breast cancer-bearing mice. It was found that as the difference between expansion of the cancer cell population and microvascular network increases, cells undergo proliferation and migration with a greater probability compared to other phenotypes. Overall, multiscale computational model agreed with both theoretical expectations and experimental findings (microCT images) not used during model training.