Formation and progression of atherosclerotic plaque is a dynamic and complex process involving various pathophysiologic steps including inflammation and calcification. The purpose of this study was to compare macrophage activity as determined by 18 F-FDG PET and ongoing mineral deposition as measured by 18 F-sodium fluoride PET in atherosclerotic plaque and to correlate these findings with calcified plaque burden as assessed by CT. Methods: Forty-five patients were examined by whole-body 18 F-FDG PET, 18 F-sodium fluoride PET, and CT. Tracer uptake in various arterial segments was analyzed both qualitatively and semiquantitatively by measuring the blood-pool-corrected standardized uptake value (target-to-background ratio [TBR]). The pattern of tracer uptake in atherosclerotic lesions was compared after color-coded multistudy image fusion of PET and CT studies. The Fisher exact test and the Spearman correlation coefficient r s were used for statistical analysis of image-based results and cardiovascular risk factors. Intra-and interrater reproducibility were evaluated using the Cohen k. Results: 18 F-sodium fluoride uptake was observed at 105 sites in 27 (60%) of the 45 study patients, and mean TBR was 2.3 6 0.7. 18 F-FDG uptake was seen at 124 sites in 34 (75.6%) patients, and mean TBR was 1.5 6 0.3. Calcified atherosclerotic lesions were observed at 503 sites in 34 (75.6%) patients. Eighty-one (77.1%) of the 105 lesions with marked 18 F-sodium fluoride uptake and only 18 (14.5%) of the 124 lesions with 18 F-FDG accumulation were colocalized with arterial calcification. Coincident uptake of both 18 F-sodium fluoride and 18 F-FDG was observed in only 14 (6.5%) of the 215 arterial lesions with radiotracer accumulation. Conclusion: PET/ CT with 18 F-FDG and 18 F-sodium fluoride may allow evaluation of distinct pathophysiologic processes in atherosclerotic lesions and might provide information on the complex interactions involved in formation and progression of atherosclerotic plaque.

18 F-FDG PET/CT is effective in the assessment of therapy response. Changes in glucose uptake or tumor size are used as a measure. Tumor heterogeneity was found to be a promising predictive and prognostic factor. We investigated textural parameters for their predictive and prognostic capability in patients with rectal cancer using histopathology as the gold standard. In addition, a comparison to clinical outcome was performed. Methods: Twenty-seven patients with rectal cancer underwent 18 F-FDG PET/CT before, 2 wk after the start, and 4 wk after the completion of neoadjuvant chemoradiotherapy. In all PET/CT scans, conventional parameters (tumor volume, diameter, maximum and mean standardized uptake values, and total lesion glycolysis [TLG]) and textural parameters (coefficient of variation [COV], skewness, and kurtosis) were determined to assess tumor heterogeneity. Values on pretherapeutic PET/CT as well as changes early in the course of therapy and after therapy were compared with histopathologic response. In addition, the prognostic value was assessed by correlation with time to progression and survival time. Results: The COV showed a statistically significant capability to assess histopathologic response early in therapy (sensitivity, 68%; specificity, 88%) and after therapy (79% and 88%, respectively). Thereby, the COV had a higher area under the curve in receiver-operating-characteristic analysis than did any analyzed conventional parameter for early and late response assessment. The COV showed a statistically significant capability to evaluate disease progression and to predict survival, although the latter was not statistically significant. Conclusion: Tumor heterogeneity assessed by the COV, being superior to the investigated conventional parameters, is an important predictive factor in patients with rectal cancer. Furthermore, it can provide prognostic information. Therefore, its application is an important step for personalized treatment of rectal cancer.

BackgroundTextural features in FDG-PET have been shown to provide prognostic information in a variety of tumor entities. Here we evaluate their predictive value for recurrence and prognosis in NSCLC patients receiving primary stereotactic radiation therapy (SBRT).Methods45 patients with early stage NSCLC (T1 or T2 tumor, no lymph node or distant metastases) were included in this retrospective study and followed over a median of 21.4 months (range 3.1–71.1). All patients were considered non-operable due to concomitant disease and referred to SBRT as the primary treatment modality. Pre-treatment FDG-PET/CT scans were obtained from all patients. SUV and volume-based analysis as well as extraction of textural features based on neighborhood gray-tone difference matrices (NGTDM) and gray-level co-occurence matrices (GLCM) were performed using InterView Fusion™ (Mediso Inc., Budapest). The ability to predict local recurrence (LR), lymph node (LN) and distant metastases (DM) was measured using the receiver operating characteristic (ROC). Univariate and multivariate analysis of overall and disease-specific survival were executed.Results7 out of 45 patients (16%) experienced LR, 11 (24%) LN and 11 (24%) DM. ROC revealed a significant correlation of several textural parameters with LR with an AUC value for entropy of 0.872. While there was also a significant correlation of LR with tumor size in the overall cohort, only texture was predictive when examining T1 (tumor diameter < = 3 cm) and T2 (>3 cm) subgroups. No correlation of the examined PET parameters with LN or DM was shown.In univariate survival analysis, both heterogeneity and tumor size were predictive for disease-specific survival, but only texture determined by entropy was determined as an independent factor in multivariate analysis (hazard ratio 7.48, p = .016). Overall survival was not significantly correlated to any examined parameter, most likely due to the high comorbidity in our cohort.ConclusionsOur study adds to the growing evidence that tumor heterogeneity as described by FDG-PET texture is associated with response to radiation therapy in NSCLC. The results may be helpful into identifying patients who might profit from an intensified treatment regime, but need to be verified in a prospective patient cohort before being incorporated into routine clinical practice.

Gliomas are the most common type of tumor in the brain. Although the definite diagnosis is routinely made ex vivo by histopathologic and molecular examination, diagnostic work-up of patients with suspected glioma is mainly done using MRI. Nevertheless, l--methyl-C-methionine (C-MET) PET holds great potential in the characterization of gliomas. The aim of this study was to establish machine-learning-driven survival models for glioma built on in vivo C-MET PET characteristics, ex vivo characteristics, and patient characteristics. The study included 70 patients with a treatment-naïve glioma that was C-MET-positive and had histopathology-derived ex vivo feature extraction, such as World Health Organization 2007 tumor grade, histology, and isocitrate dehydrogenase 1 R132H mutational status. TheC-MET-positive primary tumors were delineated semiautomatically on PET images, followed by the extraction of tumor-to-background-based general and higher-order textural features by applying 5 different binning approaches. In vivo and ex vivo features, as well as patient characteristics (age, weight, height, body mass index, Karnofsky score), were merged to characterize the tumors. Machine-learning approaches were used to identify relevant in vivo, ex vivo, and patient features and their relative weights for predicting 36-mo survival. The resulting feature weights were used to establish 3 predictive models per binning configuration: one model based on a combination of in vivo, ex vivo, and clinical patient information (M36); another based on in vivo and patient information only (M36); and a third based on in vivo information only (M36). In addition, a binning-independent model based on ex vivo and patient information only (M36) was created. The established models were validated in a Monte Carlo cross-validation scheme. The most prominent machine-learning-selected and -weighted features were patient-based and ex vivo-based, followed by in vivo-based. The highest areas under the curve for our models as revealed by the Monte Carlo cross-validation were 0.9 for M36, 0.87 for M36, 0.77 for M36, and 0.72 for M36 Prediction of survival in amino acid PET-positive glioma patients was highly accurate using computer-supported predictive models based on in vivo, ex vivo, and patient features.

Clinical observations of Babesia canis infection in 63 dogs during a 1-year period are summarised, demonstrating the pathogenicity of the Babesia strain endemic in Hungary. Most patients had babesiosis in the spring and autumn, correlating with the seasonal activity of ticks. Male animals appeared in higher numbers, probably due to an overrepresentation of outdoor dogs. Uncomplicated babesiosis was diagnosed in 32 cases. The disease affected dogs of any age in this study. Symptoms were similar to those published from other parts of the world: lethargy, fever, splenomegaly, pallor, icterus, haemoglobinuria and presence of ticks were the most common observations. Thrombocytopenia, lymphopenia and neutropenia were frequent haemogram changes. Imidocarb appeared to be highly effective in eliminating the Babesia infection. Thirty-one animals demonstrated babesiosis with complications. Most Rottweilers (7/9) developed complicated disease. Old age was a risk factor for multiple complications. Multiple organ manifestations had poor prognosis. Hepatopathy (44%), pancreatitis (33%), acute renal failure (ARF; 31%) and disseminated intravascular coagulation (DIC; 24%) were frequent complications, while immune-mediated haemolytic anaemia (IMHA; 10%), acute respiratory distress syndrome (ARDS; 6%) and cerebral babesiosis (3%) were rarely observed. There was a significant difference between the mean age of dogs having uncomplicated disease, babesiosis with a single complication and babesiosis with multiple complications (3.4, 4.8 and 8.6 years, respectively, p < 0.001). The recovery rate (78, 68 and 25%, respectively, p = 0.005) and mortality rate (3, 21 and 67%, respectively, p < 0.001) also tended to differ significantly in these groups. Systemic inflammatory response syndrome (SIRS) and