Penaolesen4852

tients with T0-FLR < 30%.

NTL-Dmean and NTL exposed to ≥ 30 Gy (NTL-V30) were most significantly associated with increase in FLR (particularly among patients with T0-FLR less then 30%). When half of NTL received ≥ 30 Gy, FLR increased to ≥ 40%, with higher accuracy among patients with T0-FLR less then 30%.Normal brain aging is commonly associated with neural activity alteration, β-amyloid (Aβ) deposition, and tau aggregation, driving a progressive cognitive decline in normal elderly individuals. Positron emission tomography (PET) with radiotracers targeting these age-related changes has been increasingly employed to clarify the sequence of their occurrence and the evolution of clinically cognitive deficits. Herein, we reviewed recent literature on PET-based imaging of normal human brain aging in terms of neural activity, Aβ, and tau. Neural hypoactivity reflected by decreased glucose utilization with PET imaging has been predominately reported in the frontal, cingulate, and temporal lobes of the normal aging brain. Aβ PET imaging uncovers the pathophysiological association of Aβ deposition with cognitive aging, as well as the potential mechanisms. Tau-associated cognitive changes in normal aging are likely independent of but facilitated by Aβ as indicated by tau and Aβ PET imaging. Future longitudinal studies using multi-radiotracer PET imaging combined with other neuroimaging modalities, such as magnetic resonance imaging (MRI) morphometry, functional MRI, and magnetoencephalography, are essential to elucidate the neuropathological underpinnings and interactions in normal brain aging.

Manual quantification of the metabolic tumor volume (MTV) from whole-body

F-FDG PET/CT is time consuming and therefore usually not applied in clinical routine. It has been shown that neural networks might assist nuclear medicine physicians in such quantification tasks. learn more However, little is known if such neural networks have to be designed for a specific type of cancer or whether they can be applied to various cancers. Therefore, the aim of this study was to evaluate the accuracy of a neural network in a cancer that was not used for its training.

Fifty consecutive breast cancer patients that underwent

F-FDG PET/CT were included in this retrospective analysis. The PET-Assisted Reporting System (PARS) prototype that uses a neural network trained on lymphoma and lung cancer

F-FDG PET/CT data had to detect pathological foci and determine their anatomical location. Consensus reads of two nuclear medicine physicians together with follow-up data served as diagnostic reference standard; 1072

F-FDG avid foci ymphoma and lung cancer, PARS showed good accuracy in the detection of PERCIST measurable lesions. Therefore, the neural network seems not prone to the clever Hans effect. However, the network has poor accuracy if all manually segmented lesions were used as reference standard. Both the whole body and organ-wise MTV were significant prognosticators of overall survival in advanced breast cancer.

Although trained on lymphoma and lung cancer, PARS showed good accuracy in the detection of PERCIST measurable lesions. Therefore, the neural network seems not prone to the clever Hans effect. However, the network has poor accuracy if all manually segmented lesions were used as reference standard. Both the whole body and organ-wise MTV were significant prognosticators of overall survival in advanced breast cancer.Three- and four-dimensional US techniques in antenatal screening are commonplace, but they are not routinely used for perinatal postmortem US. In this technical innovation, we performed both two-dimensional (2-D) and three-dimensional (3-D) postmortem US on 11 foetuses (mean gestation 23 weeks; range 15-32 weeks) to determine whether there was any benefit in 3-D over conventional 2-D methods. In one case of osteogenesis imperfecta, both 2-D and 3-D US images were non-diagnostic because of small foetal size. Of the remaining 10 foetuses, 7 were normal at imaging and autopsy, and 3 had abnormalities detected on both 2-D and 3-D US. There were no false-positive diagnoses by 2-D or 3-D US. Whilst 3-D postmortem US was a feasible technique, it did not provide additional information over 2-D US. Routine 3-D postmortem US cannot therefore be routinely recommended based on our findings.

Prognostic markers for meningioma recurrence are needed to guide patient management. Apart from rare hereditary syndromes, the impact of a previous unrelated tumor disease on meningioma recurrence has not been described before.

We retrospectively searched our database for patients with meningioma WHO grade I and complete resection provided between 2002 and 2016. Demographical, clinical, pathological, and outcome data were recorded. The following covariates were included in the statistical model age, sex, clinical history of unrelated tumor disease, and localization (skull base vs. convexity). Particular interest was paid to the patients' past medical history. The study endpoint was date of tumor recurrence on imaging. Prognostic factors were obtained from multivariate proportional hazards models.

Out of 976 meningioma patients diagnosed with a meningioma WHO grade I, 416 patients fulfilled our inclusion criteria. We encountered 305 women and 111 men with a median age of 57 years (range 21-89 years). Forty-six patients suffered from a tumor other than meningioma, and no TERT mutation was detected in these patients. There were no differences between patients with and without a positive oncological history in terms of age, tumor localization, or mitotic cell count. Clinical history of prior tumors other than meningioma showed the strongest association with meningioma recurrence (p = 0.004, HR = 3.113, CI = 1.431-6.771) both on uni- and multivariate analysis.

Past medical history of tumors other than meningioma might be associated with an increased risk of meningioma recurrence. A detailed pre-surgical history might help to identify patients at risk for early recurrence.

Past medical history of tumors other than meningioma might be associated with an increased risk of meningioma recurrence. A detailed pre-surgical history might help to identify patients at risk for early recurrence.