Quality assurance of gating response times for surface guided motion management treatment delivery using an electronic portal imaging detector.

Gating response times of monitoring system/LINAC combinations for gated radiotherapy treatments are notoriously difficult to measure. This difficulty may reflect why the incorporation of gating response times is not thoroughly considered when creating treatment margins for gated radiotherapy treatments, however ignoring the effect of gating response time could lead to significant treatment inaccuracies. This study shows a methodology which measured gating response times for AlignRT/Varian Truebeam combination which appears to be applicable to any surface guided monitoring/Linac combination as well as those combinations which incorporate extended lag times (>200 ms). Beam on lag time appears to be measurably greater than beam off lag time. Although these gating response times are slower than other gating systems on the market, the advantages surface guided radiotherapy (SGRT) could potentially provide for treatment accuracy is discussed as well as demonstrating the lack of guidance regarding SGRT with respect to gated treatments.

Discrimination between parkinsonian syndrome and essential tremor using artificial neural network classification of quantified DaTSCAN data.

BACKGROUND: In the semi-quantitative assessment of DaTSCAN images, it has been suggested that the ratio of tracer accumulation in the putamen to that in the caudate nucleus may be helpful and could allow parkinsonian syndromes progression to be assessed. Separation of ratio values has been reported when early Parkinson's disease is compared with essential tremor. The separation is lost, however, when the Parkinson's disease is not early stage. OBJECTIVES: To evaluate whether a two-stage analysis can differentiate between parkinsonian syndromes, of various stages, and essential tremor, and whether such a two-stage analysis can be undertaken in a single step using artificial neural networks (ANNs). METHODS: Data from 18 patients were analysed. Quantification was undertaken by manually drawing irregular regions of interest (ROIs): over each caudate nucleus and putamen and over an occipital cortex area near the posterior edge of the brain. A two-stage analysis was undertaken and was repeated, in a single step, using an ANN. RESULTS: The first stage, of the two-stage analysis, identified 12 patients with non-early parkinsonian syndromes. The remaining six patients were then successfully classified into early parkinsonian syndromes and essential tremor. The ANN analysis successfully discriminated parkinsonian syndromes from essential tremor, in all patients, in a single step. CONCLUSIONS: The two-stage process provides a method for classifying early disease without being compromised by the noise from non-early disease. The results of the single stage ANN analysis were very definite and it may be considered to have potential in the quantification of DaTSCAN images for clinical use.