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In vivo fluorescence/luminescence imaging in the near-infrared-IIb (NIR-IIb, 1,500 to 1,700 nm) window under <1,000 nm excitation can afford subcentimeter imaging depth without any tissue autofluorescence, promising high-precision intraoperative navigation in the clinic. Here, we developed a compact imager for concurrent visible photographic and NIR-II (1,000 to 3,000 nm) fluorescence imaging for preclinical image-guided surgery. Biocompatible erbium-based rare-earth nanoparticles (ErNPs) with bright down-conversion luminescence in the NIR-IIb window were conjugated to TRC105 antibody for molecular imaging of CD105 angiogenesis markers in 4T1 murine breast tumors. Under a ∼940 ± 38 nm light-emitting diode (LED) excitation, NIR-IIb imaging of 1,500- to 1,700-nm emission afforded noninvasive tumor–to–normal tissue (T/NT) signal ratios of ∼40 before surgery and an ultrahigh intraoperative tumor-to-muscle (T/M) ratio of ∼300, resolving tumor margin unambiguously without interfering background signal from surrounding healthy tissues. High-resolution imaging resolved small numbers of residual cancer cells during surgery, allowing thorough and nonexcessive tumor removal at the few-cell level. NIR-IIb molecular imaging afforded 10-times-higher and 100-times-higher T/NT and T/M ratios, respectively, than imaging with IRDye800CW-TRC105 in the ∼900- to 1,300-nm range. The vastly improved resolution of tumor margin and diminished background open a paradigm of molecular imaging-guided surgery.

A hybrid fluorescence molecular tomography–X ray computed tomography system is applied for in vivo imaging of multiple mouse models, and its performance is validated on post-mortem cryosection data. The development of hybrid optical tomography methods to improve imaging performance has been suggested over a decade ago and has been experimentally demonstrated in animals and humans. Here we examined in vivo performance of a camera-based hybrid fluorescence molecular tomography (FMT) system for 360° imaging combined with X-ray computed tomography (XCT). Offering an accurately co-registered, information-rich hybrid data set, FMT-XCT has new imaging possibilities compared to stand-alone FMT and XCT. We applied FMT-XCT to a subcutaneous 4T1 tumor mouse model, an Aga2 osteogenesis imperfecta model and a Kras lung cancer mouse model, using XCT information during FMT inversion. We validated in vivo imaging results against post-mortem planar fluorescence images of cryoslices and histology data. Besides offering concurrent anatomical and functional information, FMT-XCT resulted in the most accurate FMT performance to date. These findings indicate that addition of FMT optics into the XCT gantry may be a potent upgrade for small-animal XCT systems.

Mammary tumors similar to those observed in women can be induced in rats by intraperitoneal administration of N-methyl-N-nitrosourea. Determining tumor volume is a useful and quantitative way to monitor tumor progression. In this study, the authors measured dimensions of rat mammary tumors using a caliper and using real-time compound B-mode ultrasonography. They then used different formulas to calculate tumor volume from these tumor measurements and compared the calculated tumor volumes with the real tumor volume to identify the formulas that gave the most accurate volume calculations. They found that caliper and ultrasonography measurements were significantly correlated but that tumor volumes calculated using different formulas varied substantially. Mammary tumors seemed to take on an oblate spheroid geometry. The most accurate volume calculations were obtained using the formula V = (W 2 × L)/2 for caliper measurements and the formula V = (4/3) × π × (L/2) × (L/2) × (D/2) for ultrasonography measurements, where V is tumor volume, W is tumor width, L is tumor length and D is tumor depth.

Advances in genetic engineering have enabled the use of bacterial outer membrane vesicles (OMVs) to deliver vaccines, drugs and immunotherapy agents, as a strategy to circumvent biocompatibility and large-scale production issues associated with synthetic nanomaterials. We investigate bioengineered OMVs for contrast enhancement in optoacoustic (photoacoustic) imaging. We produce OMVs encapsulating biopolymer-melanin (OMV Mel ) using a bacterial strain expressing a tyrosinase transgene. Our results show that upon near-infrared light irradiation, OMV Mel generates strong optoacoustic signals appropriate for imaging applications. In addition, we show that OMV Mel builds up intense heat from the absorbed laser energy and mediates photothermal effects both in vitro and in vivo. Using multispectral optoacoustic tomography, we noninvasively monitor the spatio-temporal, tumour-associated OMV Mel distribution in vivo. This work points to the use of bioengineered vesicles as potent alternatives to synthetic particles more commonly employed for optoacoustic imaging, with the potential to enable both image enhancement and photothermal applications. Bacterial outer membrane vesicles (OMVs) are increasingly used as carriers for drug delivery. Here the authors encapsulate biopolymer melanin into OMVs, extending their use to optoacoustic imaging both in vitro and in vivo, and demonstrate the potential of this tool for photothermal therapy applications.

Cryo-imaging sections and images a whole mouse and provides ~ 120-GBytes of microscopic 3D color anatomy and fluorescence images, making fully manual analysis of metastases an onerous task. A convolutional neural network (CNN)-based metastases segmentation algorithm included three steps: candidate segmentation, candidate classification, and semi-automatic correction of the classification result. The candidate segmentation generated > 5000 candidates in each of the breast cancer-bearing mice. Random forest classifier with multi-scale CNN features and hand-crafted intensity and morphology features achieved 0.8645 ± 0.0858, 0.9738 ± 0.0074, and 0.9709 ± 0.0182 sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC), with fourfold cross validation. Classification results guided manual correction by an expert with our in-house MATLAB software. Finally, 225, 148, 165, and 344 metastases were identified in the four cancer mice. With CNN-based segmentation, the human intervention time was reduced from > 12 to ~ 2 h. We demonstrated that 4T1 breast cancer metastases spread to the lung, liver, bone, and brain. Assessing the size and distribution of metastases proves the usefulness and robustness of cryo-imaging and our software for evaluating new cancer imaging and therapeutics technologies. Application of the method with only minor modification to a pancreatic metastatic cancer model demonstrated generalizability to other tumor models.

Light propagating in tissue attains a spectrum that varies with location due to wavelength-dependent fluence attenuation, an effect that causes spectral corruption. Spectral corruption has limited the quantification accuracy of optical and optoacoustic spectroscopic methods, and impeded the goal of imaging blood oxygen saturation (sO 2 ) deep in tissues; a critical goal for the assessment of oxygenation in physiological processes and disease. Here we describe light fluence in the spectral domain and introduce eigenspectra multispectral optoacoustic tomography (eMSOT) to account for wavelength-dependent light attenuation, and estimate blood sO 2 within deep tissue. We validate eMSOT in simulations, phantoms and animal measurements and spatially resolve sO 2 in muscle and tumours, validating our measurements with histology data. eMSOT shows substantial sO 2 accuracy enhancement over previous optoacoustic methods, potentially serving as a valuable tool for imaging tissue pathophysiology. Spectral corruption impedes imaging of blood oxygen saturation. Here Tzoumas et al. describe light fluence in the spectral domain and introduce eigenspectra Multispectral Optoacoustic Tomography to account for wavelength-dependent light attenuation and estimate blood oxygen saturation within deep tissue.

The application of nanoparticle drug formulations, such as nanoliposomal doxorubicin (Doxil), is increasingly integrated in clinical cancer care. Despite nanomedicine’s remarkable potential and growth over the last three decades, its clinical benefits for cancer patients vary. Here we report a non-invasive quantitative positron emission tomography (PET) nanoreporter technology that is predictive of therapeutic outcome in individual subjects. In a breast cancer mouse model, we demonstrate that co-injecting Doxil and a Zirconium-89 nanoreporter ( 89 Zr-NRep) allows precise doxorubicin (DOX) quantification. Importantly, 89 Zr-NRep uptake also correlates with other types of nanoparticles’ tumour accumulation. 89 Zr-NRep PET imaging reveals remarkable accumulation heterogeneity independent of tumour size. We subsequently demonstrate that mice with >25 mg kg −1 DOX accumulation in tumours had significantly better growth inhibition and enhanced survival. This non-invasive imaging tool may be developed into a robust inclusion criterion for patients amenable to nanotherapy. Nanoparticle drug formulations are currently used as cancer treatment but the response in patients is highly variable. Here, the authors developed a Zirconium-89 nanoreporter able to predict using PET, therapeutic accumulation and efficacy of anti-cancer nanoparticle drug formulations when co-injected in a murine breast cancer model.

Mitochondrial membrane potential (Δ Ψ m ) is a universal selective indicator of mitochondrial function and is known to play a central role in many human pathologies, such as diabetes mellitus, cancer and Alzheimer’s and Parkinson’s diseases. Here, we report the design, synthesis and several applications of mitochondria-activatable luciferin (MAL), a bioluminescent probe sensitive to Δ Ψ m , and partially to plasma membrane potential (Δ Ψ p ), for non-invasive, longitudinal monitoring of Δ Ψ m in vitro and in vivo. We applied this new technology to evaluate the aging-related change of Δ Ψ m in mice and showed that nicotinamide riboside (NR) reverts aging-related mitochondrial depolarization, revealing another important aspect of the mechanism of action of this potent biomolecule. In addition, we demonstrated application of the MAL probe for studies of brown adipose tissue (BAT) activation and non-invasive in vivo assessment of Δ Ψ m in animal cancer models, opening exciting opportunities for understanding the underlying mechanisms and for discovery of effective treatments for many human pathologies. A mitochondria-activatable bioluminescent probe was designed enabling sensitive, non-invasive and longitudinal monitoring of mitochondrial membrane potential in vitro and in vivo.

In the current study, a breast tumor xenograft was established in athymic nude mice by subcutaneous injection of the MCF-7 cell line and assessed the tumor progression by photoacoustic spectroscopy combined with machine learning tools. The advancement of breast tumors in nude mice was validated by tumor volume kinetics and histopathology and corresponding image analysis by TissueQuant software compared to controls. The ex vivo tumors in progressive conditions belonging to time points, day 5th, 10th, 15th & 20th, were excited with 281 nm pulsed laser light and recorded the corresponding photoacoustic spectra in time domain. The spectra were then pre-processed, augmented for a 10-fold increase in the data strength, and subjected to wavelet packet transformation for feature extraction and selection using MATLAB software. In the present study, the top 10 features from all the time point groups under study were selected based on their prediction ranking values using the mRMR algorithm. The chosen features of all the time-point groups were then subjected to multi-class Support Vector Machine (SVM) algorithms for learning and classifying into respective time point groups under study. The analysis demonstrated accuracy values of 95.2%, 99.5%, and 80.3% with SVM- Radial Basis Function (SVM-RBF), SVM-Polynomial & SVM-Linear, respectively. The serum metabolomic levels during tumor progression complemented photoacoustic patterns of tumor progression, depicting breast cancer pathophysiology. The current study reports the assessment of tumor progression in athymic nude mice by Photoacoustic spectroscopy-based machine learning tools. The progressive tumors were classified using multi-class Support Vector Machine (SVM) algorithms with 99.5% accuracy. The serum metabolomic levels during tumor progression complemented photoacoustic spectral features, depicting breast cancer pathophysiology.

Fatty acids play essential roles in the growth and metastasis of cancer cells. To facilitate their avid growth and proliferation, cancer cells not only alter the fatty acid synthesis and metabolism intracellularly and extracellularly, but also in the macroenvironment via direct or indirect pathways. We report here, using Raman micro-spectroscopy, that an increase in the production of polyunsaturated fatty acids (PUFAs) was identified in both cancerous and normal appearing breast tissue obtained from breast cancer patients and tumor-bearing rats. By minimizing confounding effects from mixed chemicals and optimizing the signal-to-noise ratio of Raman spectra, we observed a large-scale transition from monounsaturated fatty acids to PUFAs in the tumor while only a small subset of fatty acids transitioned to PUFAs in the tumor micro- and macroenvironment. These data have important implications for further clarifying the macroenvironmental effect of cancer progression and provide new potential approaches for characterizing the tumor micro- and macroenvironment of breast cancer in both pre-clinical animal studies and clinical applications.