A review on the clinical implementation of respiratory-gated radiation therapy

Respiratory-gated treatment techniques have been introduced into the radiation oncology practice to manage target or organ motions. This paper will review the implementation of this type of gated treatment technique where the respiratory cycle is determined using an external marker. The external marker device is placed on the abdominal region between the xyphoid process and the umbilicus of the patient. An infrared camera tracks the motion of the marker to generate a surrogate for the respiratory cycle. The relationship, if any, between the respiratory cycle and the movement of the target can be complex. The four-dimensional computed tomography (4DCT) scanner is used to identify this motion for those patients that meet three requirements for the successful implementation of respiratory-gated treatment technique for radiation therapy. These requirements are (a) the respiratory cycle must be periodic and maintained during treatment, (b) the movement of the target must be related to the respiratory cycle, and (c) the gating window can be set sufficiently large to minimise the overall treatment time or increase the duty cycle and yet small enough to be within the gate. If the respiratory-gated treatment technique is employed, the end-expiration image set is typically used for treatment planning purposes because this image set represents the phase of the respiratory cycle where the anatomical movement is often the least for the longest time. Contouring should account for tumour residual motion, setup uncertainty, and also allow for deviation from the expected respiratory cycle during treatment. Respiratory-gated intensity-modulated radiation therapy (IMRT) treatment plans must also be validated prior to treatment. Quality assurance should be performed to check for positional changes and the output in association with the motion-gated technique. To avoid potential treatment errors, radiation therapist (radiographer) should be regularly in-serviced and made aware of the need to invoke the gating feature when prescribed for selected patients

A method for incorporating organ motion due to breathing into 3D dose calculations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134856/1/mp8577.pd

BASS: Bayesian Analyzer of Event Sequences

. We describe the BASS system, a Bayesian analyzer of event sequences. BASS uses Markov chain Monte Carlo methods, especially Metropolis-Hastings algorithm, for exploring posterior distributions. The system allows the user to specify an intensity model in a high-level definition language, and then runs the Metropolis-Hastings algorithm on it. Keywords. Bayesian analysis, event sequences, Metropolis-Hastings algorithm 1 Introduction Statistical data are often expressed in the form of a sequences of events in time. Such data arise in a variety of applied areas, for instance, in telecommunications, quality control, as well as in infectious disease epidemiology and other areas of biostatistics. Intensity functions (see, e.g., Cox et al., 1984, and Arjas, 1989) are nowadays extensively used as a methodical tool in applications of this kind, to describe the instantaneous risk of observing the event of interest over time. Frequently, it would be useful to obtain the posterior distribution..

Classification of findings in mammography screening--a method to minimise recall anxiety?

STUDY OBJECTIVE--The aim was to find out if it is possible, by classifying screening mammograms according to the likelihood of malignancy, to divide the recalled women to a group in which there is high suspicion of malignancy, most having breast cancers, and a group with more obscure findings. DESIGN--Screening mammograms of recalled women were classified according to the likelihood of malignancy. 0 = technically insufficient, 1 = normal, 2 = benign tumour, 3 = malignancy cannot be excluded, 4 = strongly suspicious for malignancy, 5 = malignant. SETTING--This study was a population based survey of mammography screening in Helsinki and surroundings in Finland. PATIENTS--21,417 women (aged 50-59 years) were invited to be screened, 18,012 (84.10%) participated. Of these 579 (3.21% of those screened) were recalled for further studies; 124 of these were referred for surgical biopsy and 82 had breast cancer. MEASUREMENTS AND MAIN RESULTS--All cases classified as 5, 60% of the cases classified as 4, 6.5% of the cases classified as 3, 0% of the cases classified as 2 or 1, and 1.2% of the cases classified as 0 proved to have breast cancers. However classification 5 represented 5.9% of all recalled women and 41.5% of all screening detected breast cancers; classification 4, 6.0% of all recalled women and 25.6% of all screening detected breast cancers; classification 3, 68.9% of all recalled women and 31.7% of all screening detected breast cancers; classification 2, 11.7% and classification 1, 2.9% of all recalled women. No breast cancers were detected with these classifications. Classification 0 represented 4.5% of all recalled women and 1.2% of all screening detected breast cancers. Classifications 5 and 4 represented only 11.9% of all recalled women but 67.1% of all screening detected breast cancers. CONCLUSIONS--By classifying screening mammograms according to the likelihood of malignancy, recalled women can be divided into two groups: (1) a quite small subgroup in which everyone or almost everyone will be shown to have breast cancer; and (2) a much larger subgroup in which only a few will be proven to have breast cancer. The invitation procedure for the further studies should be improved on this basis of minimising anxiety among recalled women