Mitigating Illumination-, Leaf-, and View-Angle Dependencies in Hyperspectral Imaging Using Polarimetry.

Automation of plant phenotyping using data from high-dimensional imaging sensors is on the forefront of agricultural research for its potential to improve seasonal yield by monitoring crop health and accelerating breeding programs. A common challenge when capturing images in the field relates to the spectral reflection of sunlight (glare) from crop leaves that, at certain solar incidences and sensor viewing angles, presents unwanted signals. The research presented here involves the convergence of 2 parallel projects to develop a facile algorithm that can use polarization data to decouple light reflected from the surface of the leaves and light scattered from the leaf's tissue. The first project is a mast-mounted hyperspectral imaging polarimeter (HIP) that can image a maize field across multiple diurnal cycles throughout a growing season. The second project is a multistatic fiber-based Mueller matrix bidirectional reflectance distribution function (mmBRDF) instrument which measures the polarized light-scattering behavior of individual maize leaves. The mmBRDF data was fitted to an existing model, which outputs parameters that were used to run simulations. The simulated data were then used to train a shallow neural network which works by comparing unpolarized 2-band vegetation index (VI) with linearly polarized data from the low-reflectivity bands of the VI. Using GNDVI and red-edge reflection ratio we saw an improvement of an order of magnitude or more in the mean error (ϵ) and a reduction spanning 1.5 to 2.7 in their standard deviation (ϵσ) after applying the correction network on the HIP sensor data.

Development of [225Ac]Ac-DOTA-C595 as radioimmunotherapy of pancreatic cancer: in vitro evaluation, dosimetric assessment and detector calibration.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy which may benefit from radioimmunotherapy. Previously, [177Lu]Lu-DOTA-C595 has been developed as a beta-emitting radioimmunoconjugate to target cancer-specific mucin 1 epitopes (MUC1-CE) overexpressed on PDAC. However, the therapeutic effect may be enhanced by using an alpha-emitting radionuclide such as Actinium-225 (Ac-225). The short range and high linear energy transfer of alpha particles provides dense cellular damage and can overcome typical barriers related to PDAC treatment such as hypoxia. Despite the added cytotoxicity of alpha-emitters, their clinical implementation can be complicated by their complex decay chains, recoil energy and short-range impeding radiation detection. In this study, we developed and evaluated [225Ac]Ac-DOTA-C595 as an alpha-emitting radioimmunotherapy against PDAC using a series of in vitro experiments and conducted a preliminary dosimetric assessment and cross-calibration of detectors for the clinical implementation of Ac-225. RESULTS: Cell binding and internalisation of [225Ac]Ac-DOTA-C595 was rapid and greatest in cells with strong MUC1-CE expression. Over 99% of PDAC cells had positive yH2AX expression within 1 h of [225Ac]Ac-DOTA-C595 exposure, suggesting a high level of DNA damage. Clonogenic assays further illustrated the cytotoxicity of [225Ac]Ac-DOTA-C595 in a concentration-dependent manner. At low concentrations of [225Ac]Ac-DOTA-C595, cells with strong MUC1-CE expression had lower cell survival than cells with weak MUC1-CE expression, yet survival was similar between cell lines at high concentrations irrespective of MUC1-CE expression. A dosimetric assessment was performed to estimate the dose-rate of 1 kBq of [225Ac]Ac-DOTA-C595 with consideration to alpha particles. Total absorption of 1 kBq of Ac-225 was estimated to provide a dose rate of 17.5 mGy/h, confirmed via both detector measurements and calculations. CONCLUSION: [225Ac]Ac-DOTA-C595 was shown to target and induce a therapeutic effect in MUC1-CE expressing PDAC cells.

In vitro characterisation of [177Lu]Lu-DOTA-C595 as a novel radioimmunotherapy for MUC1-CE positive pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) continues to be a malignancy with an unmet clinical demand. Development of radioimmunoconjugates which target cancer-specific receptors provides an opportunity for radioimmunotherapy of both metastatic and primary PDAC. In this study, we characterised the in vitro behaviour of a novel beta-emitting radioimmunoconjugate [177Lu]Lu-DOTA-C595 as a therapeutic agent against PDAC. [177Lu]Lu-DOTA-C595 is designed to target cancer-specific mucin 1 epitopes (MUC1-CE) overexpressed on most epithelial cancers, including PDAC. RESULTS: A series of in vitro experiments were performed on PDAC cell lines (PANC-1, CAPAN-1, BxPC-3 and AsPC-1) exhibiting strong to weak MUC1-CE expression. [177Lu]Lu-DOTA-C595 bound to all cell lines relative to their expression of MUC1-CE. [177Lu]Lu-DOTA-C595 was also rapidly internalised across all cell lines, with a maximum of 75.4% of activity internalised within the PANC-1 cell line at 48 h. The expression of γH2AX foci and clonogenic survival of PANC-1 and AsPC-1 cell lines after exposure to [177Lu]Lu-DOTA-C595 were used to quantify the in vitro cytotoxicity of [177Lu]Lu-DOTA-C595. At 1 h post treatment, the expression of γH2AX foci exceeded 97% in both cell lines. The expression of γH2AX foci continued to increase in PANC-1 cells at 24 h, although expression reduced in AsPC-1. Clonogenic assays showed a high level of cell kill induced by [177Lu]Lu-DOTA-C595. CONCLUSION: [177Lu]Lu-DOTA-C595 has favourable in vitro characteristics to target and treat MUC1-CE positive PDAC. Further investigations to characterise the in vivo effects and potential value of [177Lu]Lu-DOTA-C595 in other MUC1-CE expressing malignancies such as lung, ovarian and colorectal adenocarcinoma are warranted.

Preliminary Development and Testing of C595 Radioimmunoconjugates for Targeting MUC1 Cancer Epitopes in Pancreatic Ductal Adenocarcinoma.

Mucin 1 is a transmembrane glycoprotein which overexpresses cancer-specific epitopes (MUC1-CE) on pancreatic ductal adenocarcinoma (PDAC) cells. As PDAC is a low survival and highly aggressive malignancy, developing radioimmunoconjugates capable of targeting MUC1-CE could lead to improvements in PDAC outcomes. The aim of this study was to develop and perform preliminary testing of diagnostic and therapeutic radioimmunoconjugates for PDAC using an anti-MUC1 antibody, C595. Firstly, p-SCN-Bn-DOTA was conjugated to the C595 antibody to form a DOTA-C595 immunoconjugate. The stability and binding affinity of the DOTA-C595 conjugate was evaluated using mass spectrometry and ELISA. DOTA-C595 was radiolabelled to Copper-64, Lutetium-177, Gallium-68 and Technetium-99m to form novel radioimmunoconjugates. Cell binding assays were performed in PANC-1 (strong MUC1-CE expression) and AsPC-1 (weak MUC1-CE expression) cell lines using 64Cu-DOTA-C595 and 177Lu-DOTA-C595. An optimal molar ratio of 4:1 DOTA groups per C595 molecule was obtained from the conjugation process. DOTA-C595 labelled to Copper-64, Lutetium-177, and Technetium-99m with high efficiency, although the Gallium-68 labelling was low. 177Lu-DOTA-C595 demonstrated high cellular binding to the PANC-1 cell lines which was significantly greater than AsPC-1 binding at concentrations exceeding 100 nM (p < 0.05). 64Cu-DOTA-C595 showed similar binding to the PANC-1 and AsPC-1 cells with no significant differences observed between cell lines (p > 0.05). The high cellular binding of 177Lu-DOTA-C595 to MUC1-CE positive cell lines suggests promise as a therapeutic radioimmunoconjugate against PDAC while further work is required to harness the potential of 64Cu-DOTA-C595 as a diagnostic radioimmunoconjugate.

Combined chemotherapy and endoscopic ultrasound-guided intratumoral 32P implantation for locally advanced pancreatic adenocarcinoma: a pilot study.

BACKGROUND: This study evaluated clinical outcomes of combined chemotherapy and endoscopic ultrasound (EUS)-guided intratumoral radioactive phosphorus-32 (32P) implantation in locally advanced pancreatic adenocarcinoma (LAPC). METHODS: Consecutive patients with newly diagnosed LAPC were recruited over 20 months. Baseline computed tomography and 18F-2-fluoro-2-deoxy-D-glucose (18FDG) positron emission tomography-computed tomography were performed and repeated after 12 weeks to assess treatment response. Following two cycles of conventional chemotherapy, patients underwent EUS-guided 32P implantation followed by six chemotherapy cycles. RESULTS: 12 patients with LAPC (median age 69 years [interquartile range 61.5-73.3]; 8 male) completed treatment. Technical success was 100 % with no procedural complications. At 12 weeks, median reduction in tumor volume was 8.2 cm3 (95 % confidence interval 4.95-10.85; P = 0.003), with minimal or no 18FDG uptake in nine patients (75 %). Tumor downstaging was achieved in six patients (50 %), leading to successful resection in five (42 %), including four R0 resections (80 %). CONCLUSIONS: EUS-guided 32P implantation was feasible, well tolerated, and resulted in a 42 % surgical resection rate. Further evaluation in a larger randomized multicenter trial is warranted.

The Expression Profile and Textural Characteristics of C595-Reactive MUC1 in Pancreatic Ductal Adenocarcinoma for Targeted Radionuclide Therapy.

Improvements in the prognosis of pancreatic ductal adenocarcinoma (PDAC) rely on the development of effective treatments to target advanced disease. Mucin 1 (MUC1) is a transmembrane glycoprotein which is involved in the metastatic progression of PDAC and is a receptor-of-interest for targeted radionuclide therapy. The aim of this study was to determine the feasibility of MUC1-based targeted radionuclide therapy for PDAC, by evaluating the expression profile of MUC1 in different pancreatic cells and tissues using the C595 antibody. MUC1 expression was evaluated in four PDAC cell lines (PANC-1, BxPC-3, CAPAN-1 and AsPC-1) using flow cytometry and immunocytochemistry. Immunohistochemistry was performed on primary and metastatic PDAC, pancreatitis, pancreatic intra-epithelial neoplasia and normal pancreatic tissue samples to identify potential changes in C595-reactive MUC1 expression across different disease groups. C595-reactive MUC1 expression was found to varying degrees in the cell lines (11.5-93.1%). A pixel analysis of the immunohistochemical staining demonstrated highest MUC1 expression in primary PDAC tissue (mean pixel value of 205.4), followed by other pancreatic cancer types (204.9), pancreatic intra-epithelial neoplasia (203.8), metastatic PDAC (201.5), chronic pancreatitis (198.1) and normal pancreatic tissue (191.4). The increased expression in malignant tissues and reduced expression in benign tissues indicate that C595-reactive MUC1 is a potential target for targeted radionuclide therapy of PDAC.

Radioimmunotherapy of Pancreatic Ductal Adenocarcinoma: A Review of the Current Status of Literature.

Pancreatic ductal adenocarcinoma (PDAC) has long been associated with low survival rates. A lack of accurate diagnostic tests and limited treatment options contribute to the poor prognosis of PDAC. Radioimmunotherapy using α- or ß-emitting radionuclides has been identified as a potential treatment for PDAC. By harnessing the cytotoxicity of α or ß particles, radioimmunotherapy may overcome the anatomic and physiological factors which traditionally make PDAC resistant to most conventional treatments. Appropriate selection of target receptors and the development of selective and cytotoxic radioimmunoconjugates are needed to achieve the desired results of radioimmunotherapy. The aim of this review is to examine the growing preclinical and clinical trial evidence regarding the application of α and ß radioimmunotherapy for the treatment of PDAC. A systematic search of MEDLINE® and Scopus databases was performed to identify 34 relevant studies conducted on α or ß radioimmunotherapy of PDAC. Preclinical results demonstrated α and ß radioimmunotherapy provided effective tumour control. Clinical studies were limited to investigating ß radioimmunotherapy only. Phase I and II trials observed disease control rates of 11.2%-57.9%, with synergistic effects noted for combination therapies. Further developments and optimisation of treatment regimens are needed to improve the clinical relevance of α and ß radioimmunotherapy in PDAC.

Preparation of 68 Ga-Mg-Ca-phytate colloid and its evaluation as a liver imaging agent.

The objective of this study was to investigate the radiosynthesis of 68 Ga-Mg-Ca-phytate colloid and then characterise the formulation for radiochemical purity (RCP), radioactive particle size distribution, and biodistribution in normal rats. This radiocolloid was prepared by mixing an aqueous solution of phytic acid, 68 Ga3+ ions, a dispersant, Mg2+ and Ca2+ ions, and then heating the contents at 100°C for 5 minutes. After cooling the vial to 5°C, the solution was basified to pH 5 and stored in the cold. The resulting product contained 92±3% RCP 68 Ga-colloidal particles and a low level (8±3%) of soluble 68 Ga-Mg-Ca-phytate. Particle size experiments defined the radioactive particle population was 6±4% <20 nm, 90±6% 20 to 200 nm, and 4% were >200 nm in diameter. Intravenous injection of the 68 Ga-colloid dispersion to rats resulted in 93% uptake by the liver plus spleen, 1% lungs, 1% total blood, and 6% in the carcass after 20 minutes. This optimal formulation remained stable at 5°C for 1½ hours in vitro, and it resulted in the same biodistribution as the formulation prepared at t = 0 hours. The preclinical data so far indicate that 68 Ga-Mg-Ca-colloid has excellent potential as a liver imaging agent.

68 Ga-Ca-phytate particles: A potential lung perfusion agent of synthetic origin prepared in a cold kit format.

The objective of this study was to investigate the radiosynthesis of 68 Ga-Ca-phytate particles and then characterize the formulation for radiochemical purity, radioactive particle size distribution, and biodistribution in normal rats. This radiotracer was prepared using a commercial phytate cold kit after reconstitution with saline, 68 Ga-chloride generator eluent, calcium chloride, and air, then heating at 100°C for 30 minutes to achieve 99% radiochemical purity of 68 Ga-particles that were 21% 3-5 µm, 8% 5-15 µm, and 71% >15 µm in diameter. This optimal formulation was stable for 2 hours at room temperature. Intravenous administration of 68 Ga-particles in rats resulted in an uptake of 93% in the lungs, 4% in the liver plus spleen, and 3% in the carcass after 20 minutes. Two-thirds of the carcass activity was radioactive blood, likely to be 68 Ga-transferrin. The positron emission tomography image was superior than the 99m Tc-MAA image because it displayed high lung uptake against a low background. Low uptake by the liver, spleen did not interfere with the diagnostic quality, and faint activity in the submandibular (salivary) glands was due to 68 Ga-transferrin. The preclinical data so far indicate that 68 Ga-Ca-phytate particles have good potential as a lung perfusion imaging agent.

An improved assay for (68)Ga-hydroxide in (68)Ga-DOTATATE formulations intended for neuroendocrine tumour imaging.

The objective of this study was to identify a more rapid assay for (68)Ga(OH)3 impurity in (68)Ga-DOTATATE formulations. Three methods were used to prepare (68)Ga(OH)3 reference material (pharmacopoeial, bench titration and automated radiosynthesis), and four quality control methods for its assessment (thin layer chromatography, membrane filtration, HPLC and solid phase extraction). The optimal method of preparing (68)Ga(OH)3 was by titrating (68)Ga(3+) with buffered sodium hydroxide solutions to pH 5.6 ± 0.2. The precipitate was quantitatively isolated by membrane filtration (0.02 µm)/hydrochloric acid (HCl; pH 5.6) solvent, and also it remained 100% at the origin on instant thin layer chromatography with silica gel paper/HCl (pH 5.6) solvent. For (68)Ga-DOTATATE samples, the thin layer chromatography technique was used with a single paper strip developed separately on two occasions, once in HCl (pH 5.6) and next in methanol solvent. This so-called double-developed (DD) method separated (68)Ga(OH)3 impurity located at the origin, from (68)Ga-DOTATATE plus (68)Ga(3+) at ~Rf 0.4, and it was superior to the other methods. It assayed for the impurity similarly to the pharmacopoeial method. The advantages of the DD method were that it required inexpensive test materials and it reproducibly determined % (68)Ga(OH)3 in (68)Ga-DOTATATE in 12 min, 13 min earlier than the pharmacopoeial method. This time efficiency resulted in a surplus of 12% (68)Ga-DOTATATE counts in the product vial, and this provided a contingency of radioactivity or time for the injection/imaging processes in the Nuclear Medicine Department.

Nonlinear principal component analysis of noisy data.

With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem in NLPCA, a new information criterion (IC) is proposed for selecting the best model among multiple models with different complexity and regularization (i.e. weight penalty). This IC gauges the inconsistency I between the nonlinear principal components (u and u) for every data point x and its nearest neighbour x, with I=1 - correlation (u, u), where I tends to increase with overfitted solutions. Tests were performed using autoassociative neural networks for NLPCA on synthetic and real climate data (tropical Pacific sea surface temperatures and equatorial stratospheric winds), with the IC performing well in model selection and in deciding between an open curve or a closed curve solution.

Neural network forecasts of the tropical Pacific sea surface temperatures.

A nonlinear forecast system for the sea surface temperature (SST) anomalies over the whole tropical Pacific has been developed using a multi-layer perceptron neural network approach, where sea level pressure and SST anomalies were used as predictors to predict the five leading SST principal components at lead times from 3 to 15 months. Relative to the linear regression (LR) models, the nonlinear (NL) models showed higher correlation skills and lower root mean square errors over most areas of the domain, especially over the far western Pacific (west of 155 degrees E) and the eastern equatorial Pacific off Peru at lead times longer than 3 months, with correlation skills enhanced by 0.10-0.14. Seasonal and decadal changes in the prediction skills in the NL and LR models were also studied.

Complex-valued neural networks for nonlinear complex principal component analysis.

Principal component analysis (PCA) has been generalized to complex principal component analysis (CPCA), which has been widely applied to complex-valued data, two-dimensional vector fields, and complexified real data through the Hilbert transform. Nonlinear PCA (NLPCA) can also be performed using auto-associative feed-forward neural network (NN) models, which allows the extraction of nonlinear features in the data set. This paper introduces a nonlinear complex PCA (NLCPCA) method, which allows nonlinear feature extraction and dimension reduction in complex-valued data sets. The NLCPCA uses the architecture of the NLPCA network, but with complex variables (including complex weight and bias parameters). The application of NLCPCA on test problems confirms its ability to extract nonlinear features missed by the CPCA. For similar number of model parameters, the NLCPCA captures more variance of a data set than the alternative real approach (i.e. replacing each complex variable by two real variables and applying NLPCA). The NLCPCA is also used to perform nonlinear Hilbert PCA (NLHPCA) on complexified real data. The NLHPCA applied to the tropical Pacific sea surface temperatures extracts the El Niño-Southern Oscillation signal better than the linear Hilbert PCA.