EP-1957 An MR-based simulation procedure for individual assessment of tumor motion in MR-guided lung SABR

The paper proposes the model of a person seismic signal with noise for the investigation of passive seismic location system characteristics. The known models based on Gabor and Berlage pulses have been analyzed. These models are not able wholly to consider statistical properties of seismic signals. The proposed model is based on almost cyclic character of seismic signals, Gauss character of fluctuations inside a pulse, random amplitude change from pulse to pulse and relatively small fluctuation of separate pulses positions. The simulation procedure consists of passing the white noise through a linear generating filter with characteristics formed by real steps of a person, and the primary pulse sequence modulation by Gauss functions. The model permits to control the signal-to-noise ratio after its reduction to unity and to vary pulse shifts with respect to person steps irregularity. It has been shown that the model of a person seismic signal with noise agrees with experimental data.

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Comprehensive survey among statistical members of medical ethics committees in Germany on their personal impression of completeness and correctness of biostatistical aspects of submitted study protocols

BMJ Open ◽

10.1136/bmjopen-2019-032864 ◽

2020 ◽

Vol 10 (2) ◽

pp. e032864

Author(s):

Geraldine Rauch ◽

Lorena Hafermann ◽

Ulrich Mansmann ◽

Iris Pigeot

Keyword(s):

Medical Ethics ◽

Missing Values ◽

Sample Size Calculation ◽

Ethics Committees ◽

Secondary Outcome ◽

Study Protocols ◽

Individual Assessment ◽

Statistical Problems ◽

Multiple Comparison Procedures

ObjectivesTo assess biostatistical quality of study protocols submitted to German medical ethics committees according to personal appraisal of their statistical members.DesignWe conducted a web-based survey among biostatisticians who have been active as members in German medical ethics committees during the past 3 years.SettingThe study population was identified by a comprehensive web search on websites of German medical ethics committees.ParticipantsThe final list comprised 86 eligible persons. In total, 57 (66%) completed the survey.QuestionnaireThe first item checked whether the inclusion criterion was met. The last item assessed satisfaction with the survey. Four items aimed to characterise the medical ethics committee in terms of type and location, one item asked for the urgency of biostatistical training addressed to the medical investigators. The main 2×12 items reported an individual assessment of the quality of biostatistical aspects in the submitted study protocols, while distinguishing studies according to the German Medicines Act (AMG)/German Act on Medical Devices (MPG) and studies non-regulated by these laws.Primary and secondary outcome measuresThe individual assessment of the quality of biostatistical aspects corresponds to the primary objective. Thus, participants were asked to complete the sentence ‘In x% of the submitted study protocols, the following problem occurs’, where 12 different statistical problems were formulated. All other items assess secondary endpoints.ResultsFor all biostatistical aspects, 45 of 49 (91.8%) participants judged the quality of AMG/MPG study protocols much better than that of ‘non-regulated’ studies. The latter are in median affected 20%–60% more often by statistical problems. The highest need for training was reported for sample size calculation, missing values and multiple comparison procedures.ConclusionsBiostatisticians being active in German medical ethics committees classify the biostatistical quality of study protocols as low for ‘non-regulated’ studies, whereas quality is much better for AMG/MPG studies.

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Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm

Radiation Oncology ◽

10.1186/s13014-019-1401-2 ◽

2019 ◽

Vol 14 (1) ◽

Cited By ~ 3

Author(s):

Wu-zhou Li ◽

Zhi-wen Liang ◽

Yi Cao ◽

Ting-ting Cao ◽

Hong Quan ◽

...

Keyword(s):

Stereotactic Radiotherapy ◽

Imaging System ◽

Liver Tumors ◽

Three Dimensional ◽

Rigid Motion ◽

Iterative Closest Point ◽

Tumor Motion ◽

Tracking Accuracy ◽

Icp Algorithm ◽

Anterior Posterior

Abstract Background Tumor motion may compromise the accuracy of liver stereotactic radiotherapy. In order to carry out a precise planning, estimating liver tumor motion during radiotherapy has received a lot of attention. Previous approach may have difficult to deal with image data corrupted by noise. The iterative closest point (ICP) algorithm is widely used for estimating the rigid registration of three-dimensional point sets when these data were dense or corrupted. In the light of this, our study estimated the three-dimensional (3D) rigid motion of liver tumors during stereotactic liver radiotherapy using reconstructed 3D coordinates of fiducials based on the ICP algorithm. Methods Four hundred ninety-five pairs of orthogonal kilovoltage (KV) images from the CyberKnife stereo imaging system for 12 patients were used in this study. For each pair of images, the 3D coordinates of fiducial markers inside the liver were calculated via geometric derivations. The 3D coordinates were used to calculate the real-time translational and rotational motion of liver tumors around three axes via an ICP algorithm. The residual error was also investigated both with and without rotational correction. Results The translational shifts of liver tumors in left-right (LR), anterior-posterior (AP),and superior-inferior (SI) directions were 2.92 ± 1.98 mm, 5.54 ± 3.12 mm, and 16.22 ± 5.86 mm, respectively; the rotational angles in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions were 3.95° ± 3.08°, 4.93° ± 2.90°, and 4.09° ± 1.99°, respectively. Rotational correction decreased 3D fiducial displacement from 1.19 ± 0.35 mm to 0.65 ± 0.24 mm (P<0.001). Conclusions The maximum translational movement occurred in the SI direction. Rotational correction decreased fiducial displacements and increased tumor tracking accuracy.

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