Background and Purpose-Vascular pathology and Alzheimer disease (AD) pathology have been shown to coexist in the brains of dementia patients. We investigated how cognitive impairment could be exacerbated in a rat model of combined injury through the interaction of chronic cerebral hypoperfusion and amyloid beta (A␤) toxicity. Methods-In Wistar rats, chronic cerebral hypoperfusion was modeled by permanent occlusion of bilateral common carotid arteries (BCCAo). Further, AD pathology was modeled by bilateral intracerebroventricular A␤ (A␤ toxicity) using a nonphysiological A␤ peptide (A␤ 25 to 35). The experimental animals were divided into 4 groups, including sham, single injury (A␤ toxicity or BCCAo), and combined injury (BCCAo-A␤ toxicity) groups (nϭ7 per group) . Cerebral blood flow and metabolism were measured using small animal positron emission tomography. A Morris water maze task, novel object location and recognition tests, and histological investigation, including neuronal cell death, apoptosis, neuroinflammation, and AD-related pathology, were performed. Results-Spatial memory impairment was synergistically exacerbated in the BCCAo-A␤ toxicity group as compared to the BCCAo or A␤ toxicity groups (PϽ0.05). Compared to the sham group, neuroinflammation with microglial or astroglial activation was increased both in multiple white matter lesions and the hippocampus in other experimental groups. AD-related pathology was enhanced in the BCCAo-A␤ toxicity group compared to the A␤ toxicity group. Conclusion-Our experimental results support a clinical hypothesis of the deleterious interaction between chronic cerebralhypoperfusion and A␤ toxicity. Chronic cerebral hypoperfusion-induced perturbation in the equilibrium of AD-related pathology may exacerbate cognitive impairment in a rat model of combined injury. (Stroke. 2011;42:2595-2604.)Key Words: Alzheimer disease Ⅲ amyloid beta Ⅲ chronic cerebral hypoperfusion Ⅲ Morris water maze Ⅲ vascular dementia A lzheimer disease (AD) and vascular dementia are the most common causes of cognitive decline in the aging population. 1 Accumulation of insoluble amyloid beta (A␤) in the brain has been identified as the major culprit for the cognitive impairment observed in AD patients. 2 Because senile plaques composed of the A␤ peptide have been found in the brains of AD patients, 2 extensive research has focused on the amyloid hypothesis to explain AD pathology.A hypothesis emphasizing the interaction between AD and vascular pathologies has recently emerged. [3][4][5] The Nun study and other clinico-pathological studies 6 -8 have revealed that patients with AD exhibit concomitant vascular lesions in the brain. Further, epidemiological studies have shown that the major risk factors for AD mostly coincide with those for vascular dementia. 4 The Rotterdam study, 9 a large population-based prospective study, reported an increased prevalence of atherosclerosis in patients either with AD or Received March 11, 2011; accepted March 31, 2011 A converging hypothesis involving chronic ...

The purpose of this study was to develop Cu-labeled trastuzumab with improved pharmacokinetics for human epidermal growth factor receptor 2. Trastuzumab was conjugated with SCN-Bn-NOTA and radiolabeled with Cu. Serum stability and immunoreactivity ofCu-NOTA-trastuzumab were tested. Small animal PET imaging and biodistribution study were performed in HER2-positive breast cancer xenograft model (BT-474). Internal dosimetry of experimental animals was performed using the image-based approach with the Monte Carlo N-Particle Code. Cu-NOTA-trastuzumab was prepared with high radiolabel yield and radiochemical purity (>98%) and showed high stability in serum and good immunoreactivity. Uptake of Cu-NOTA-trastuzumab was highest at 48 h after injection determined by PET imaging and biodistribution results in BT-474 tumors. The blood radioactivity concentrations ofCu-NOTA-trastuzumab decreased bi-exponentially with time in both mice with and without BT-474 tumor xenografts. The calculated absorbed dose of Cu-NOTA-trastuzumab was 0.048 mGy/MBq for the heart, 0.079 for the liver and 0.047 for the spleen.Cu-NOTA-trastuzumab was effectively targeted to the HER2-expressing tumor and, and it exhibited relatively low absorbed dose due to short residence time. Therefore, Cu-NOTA-trastuzumab could be applied to select the right patients/right timing for HER2 therapy, to monitor the treatment response after HER2-targeted therapy, and to detect distal or metastatic spread.

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Radiolabeled lipophilic cationic compounds, such as 18 F-labeled phosphonium salt, accumulate in the mitochondria through a negative inner transmembrane potential. The purpose of this study was to develop and evaluate ( 18 F-fluoropentyl)triphenylphosphonium salt ( 18 F-FPTP) as a myocardial PET agent. Methods: A reference compound of 18 F-FPTP was synthesized via 3-step nucleophilic substitution reactions and was radiolabeled via 2-step nucleophilic substitution reactions of no-carrier-added 18 F-fluoride. Accumulations of 18 F-FPTP, 3 H-tetraphenylphosphonium, and 99m Tc-sestamibi were compared in a cultured embryonic cardiomyoblast cell line (H9c2). The biodistribution of 18 F-FPTP was assessed using BALB/c mice. The 18 F-FPTP small-animal PET study was performed in Sprague-Dawley rats with or without left coronary artery (LCA) ligation. Results: 18 F-FPTP was synthesized with a radiochemical yield of 15%-20% and radiochemical purity of greater than 98%. Specific activity was greater than 6.3 TBq/mmol. Cell uptake of 18 F-FPTP was more than 15-fold higher in H9c2 than in normal fibroblasts (human normal foreskin fibroblasts). Selective collapse of mitochondrial membrane potential substantially decreased cellular uptake for 18 F-FPTP and 3 H-tetraphenylphosphonium, compared with that for 99m Tc-sestamibi. The biodistribution data in mice (n 5 24) showed rapid blood clearance and high accumulation in the heart. Heart-to-blood ratios at 10 and 30 min were 54 and 133, respectively. Heart-to-lung and heart-to-liver ratios at 10, 30, and 60 min were 4, 4, and 7 and 4, 5, and 7, respectively. Dynamic small-animal PET for 60 min after injection of 18 F-FPTP showed an initial spike of radioactivity, followed by retention in the myocardium and rapid clearance from the background. 18 F-FPTP small-animal PET images in LCA-occluded rats demonstrated sharply defined myocardial defects in the corresponding area of the myocardium. The myocardial defect size measured by 18 F-FPTP small-animal PET correlated closely with the hypoperfused area measured by quantitative 2,3,5-triphenyltetrazolium chloride staining (r 2 5 0.92, P , 0.001). Conclusion: The excellent pharmacokinetics of 18 F-FPTP and its correlation with 2,3,5-triphenyltetrazolium chloride staining in normal and LCAoccluded rats suggest that this molecular probe may have a high potential as a mitochondrial voltage sensor for PET. This probe may also allow high throughput, with multiple daily studies and a wide distribution of PET myocardial imaging in the clinic.

Although epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI) produce an initially dramatic response in lung cancer patients harboring a mutation in the EGFR gene, development of acquired resistance is almost inevitable. A secondary mutation of threonine 790 (T790M) is associated with approximately half of the cases of acquired resistance. This study investigated whether the addition of silibinin to therapy with gefitinib or erlotinib could overcome T790M-mediated drug resistance considering that silibinin has various antitumor effects, including EGFR modulation. Silibinin selectively reduced the activity of the EGFR family (EGFR, ErbB2, and ErbB3) through the inhibition of receptor dimerization in lung cancer cells with EGFR mutations, but not in those harboring the wild type. In primary and acquired resistant cells with T790M, addition of silibinin enhanced the ability of EGFR-TKIs to downregulate EGFR signals and to inhibit cell growth. Similarly, the combination of silibinin and erlotinib effectively suppressed tumor growth in erlotinib resistance-bearing PC-9 xenografts. The results indicate that the addition of silibinin to EGFR-TKIs is a promising strategy to overcome T790M-mediated drug resistance. Mol Cancer Ther; 9(12); 3233-43. Ó2010 AACR.

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This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The breast PET/MRI image deep learning model was introduced and compared with the conventional methods. PET/CT and MRI parameters were evaluated before and after the first NAC cycle in patients with advanced breast cancer [n = 56; all women; median age, 49 (range 26–66) years]. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained with the corresponding baseline values (SUV0, MTV0, and TLG0, respectively) and interim PET images (SUV1, MTV1, and TLG1, respectively). Mean apparent diffusion coefficients were obtained from baseline and interim diffusion MR images (ADC0 and ADC1, respectively). The differences between the baseline and interim parameters were measured (ΔSUV, ΔMTV, ΔTLG, and ΔADC). Subgroup analysis was performed for the HER2-negative and triple-negative groups. Datasets for convolutional neural network (CNN), assigned as training (80%) and test datasets (20%), were cropped from the baseline (PET0, MRI0) and interim (PET1, MRI1) images. Histopathologic responses were assessed using the Miller and Payne system, after three cycles of chemotherapy. Receiver operating characteristic curve analysis was used to assess the performance of the differentiating responders and non-responders. There were six responders (11%) and 50 non-responders (89%). The area under the curve (AUC) was the highest for ΔSUV at 0.805 (95% CI 0.677–0.899). The AUC was the highest for ΔSUV at 0.879 (95% CI 0.722–0.965) for the HER2-negative subtype. AUC improved following CNN application (SUV0:PET0 = 0.652:0.886, SUV1:PET1 = 0.687:0.980, and ADC1:MRI1 = 0.537:0.701), except for ADC0 (ADC0:MRI0 = 0.703:0.602). PET/MRI image deep learning model can predict pathological responses to NAC in patients with advanced breast cancer.

BackgroundOsteosarcoma (OS) is the most common primary bone tumor affecting humans and it has extreme heterogeneity. Despite modern therapy, it recurs in approximately 30–40% of patients initially diagnosed with no metastatic disease, with the long-term survival rates of patients with recurrent OS being generally 20%. Thus, early prediction of metastases in OS management plans is crucial for better-adapted treatments and survival rates. In this study, a radiomics model for metastasis risk prediction in OS was developed and evaluated using metabolic imaging phenotypes.Methods and findingsThe subjects were eighty-three patients with OS, and all were treated with surgery and chemotherapy for local control. All patients underwent a pretreatment 18F-FDG-PET scan. Forty-five features were extracted from the tumor region. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved cross validation in the following four steps leading to final prediction model construction: (1) feature set reduction and selection; (2) model coefficients computation through train and validation processing; and (3) prediction performance estimation. The multivariable logistic regression model was developed using two radiomics features, SUVmax and GLZLM-SZLGE. The trained and validated multivariable logistic model based on probability of endpoint (P) = 1/ (1+exp (-Z)) was Z = -1.23 + 1.53*SUVmax + 1.68*GLZLM-SZLGE with significant p-values (SUVmax: 0.0462 and GLZLM_SZLGE: 0.0154). The final multivariable logistic model achieved an area under the curve (AUC) receiver operating characteristics (ROC) curve of 0.80, a sensitivity of 0.66, and a specificity of 0.88 in cross validation.ConclusionsThe SUVmax and GLZLM-SZLGE from metabolic imaging phenotypes are independent predictors of metastasis risk assessment. They show the association between 18F-FDG-PET and metastatic colonization knowledge. The multivariable model developed using them could improve patient outcomes by allowing aggressive treatment in patients with high metastasis risk.