Biomedical subjects

S Chungbin

Publications and source records attributed to S Chungbin.

3 recordsLinked to original sources

PubMed2001

The overshoot phenomenon in step-and-shoot IMRT delivery.

The control loop in the Varian DMLC system (V4.8) requires approximately 65 msec to monitor and halt the irradiation of a segment, causing an "overshoot" effect: the segment ends on a fractional monitor unit larger than that planned. As a result, the actual MU delivered may differ from that planned. In general, for step-and-shoot treatments, the first segment receives more, the last receives less, and intermediate segments vary. The overshoot for each segment (DeltaMU) is small, approximately 0.6 MU at 600 MU/min. Our IMRT planning system (Corvus) produces plans often having more than 20% of the segments with less than 1 MU/segment. Such segments may be skipped if the DeltaMU exceeds the segments' planned MU. Furthermore, QA filming often requires reducing the total MU by a factor of 4-6, increasing the potential for dosimetric error. This study measured DeltaMU over a range of MU/min and MU/segment. At >5 MU/segment, the DeltaMU was stable, corresponding to a delay of 62 msec. DeltaMU became larger and more variable at <1 MU/segment. The behavior was modeled in a computer program that predicted the change in delivered MU/segment and total change in delivered MU to each beamlet. Beams were analyzed for patients receiving 5 field prostate or 9 field head and neck treatments. At 400 MU/min, 28% and 16%, respectively, of the planned segments were skipped. For QA filming, up to 75% of the segments were skipped. The cumulative error averaged <0.1 MU/beamlet, but individual beamlets had errors exceeding 200%. The effect is most significant for low dose regions. Recommendations are given for deciding when to treat or do QA studies with lower MU/min. In general, treatments are not significantly affected, but QA films taken at reduced MU may be improved if irradiated at lowered MU/min.

Computer Simulation↗

PubMed1999

Development and clinical implementation of an enhanced display algorithm for use in networked electronic portal imaging.

PURPOSE: To introduce and clinically validate a preprocessing algorithm that allows clinical images from an electronic portal imaging device (EPID) to be displayed on any computer monitor, without loss of clinical usability. The introduction of such a system frees EPI systems from the constraints of fixed viewing workstations and increases mobility of the images in a department. METHODS AND MATERIALS: The preprocessing algorithm, together with its variable parameters is introduced. Clinically, the algorithm is tested using an observer study of 316 EPID images of the pelvic region in the framework of treatment of carcinoma of the cervix and endometrium. Both anterior-posterior (AP/PA) and latero-lateral (LAT) images were used. The images scored were taken from six different patients, five of whom were obese, female, and postmenopausal. The result is tentatively compared with results from other groups. The scoring system, based on the number of visible landmarks in the port, is proposed and validated. Validation was performed by having the observer panel score images with artificially induced noise levels. A comparative study was undertaken with a standard automatic window and leveling display technique. Finally, some case studies using different image sites and EPI detectors are presented. RESULTS: The image quality for all images in this study was deemed to be clinically useful (mean score >1). Most of the images received a score which was second highest (AP/PA landmarks > or =6 and LAT landmarks > or =5). Obesity, which has been an important factor determining the image quality, was not seen to be a factor here. Compared to standard techniques a highly significant improvement was determined with regard to clinical usefulness. The algorithm performs fast (less than 9 seconds) and needs no additional user interaction in most of the cases. The algorithm works well on both direct detection portal imagers and camera-based imagers whether analog or digital cameras. CONCLUSIONS: We have demonstrated that it is possible to preprocess EPIs in such a way that the clinically relevant landmarks are easily detected on a generic computer screen. The algorithm is system-independent and fast. This allows for the encoding of EPIs in more generalized commercial formats so that distribution of images is facilitated.

Algorithms↗

PubMed1998

Study of lung density corrections in a clinical trial (RTOG 88-08). Radiation Therapy Oncology Group.

PURPOSE: To investigate the effect of lung density corrections on the dose delivered to lung cancer radiotherapy patients in a multi-institutional clinical trial, and to determine whether commonly available density-correction algorithms are sufficient to improve the accuracy and precision of dose calculation in the clinical trials setting. METHODS AND MATERIALS: A benchmark problem was designed (and a corresponding phantom fabricated) to test density-correction algorithms under standard conditions for photon beams ranging from 60Co to 24 MV. Point doses and isodose distributions submitted for a Phase III trial in regionally advanced, unresectable non-small-cell lung cancer (Radiation Therapy Oncology Group 88-08) were calculated with and without density correction. Tumor doses were analyzed for 322 patients and 1236 separate fields. RESULTS: For the benchmark problem studied here, the overall correction factor for a four-field treatment varied significantly with energy, ranging from 1.14 (60Co) to 1.05 (24 MV) for measured doses, or 1.17 (60Co) to 1.05 (24 MV) for doses calculated by conventional density-correction algorithms. For the patient data, overall correction factors (calculated) ranged from 0.95 to 1.28, with a mean of 1.05 and distributional standard deviation of 0.05. The largest corrections were for lateral fields, with a mean correction factor of 1.11 and standard deviation of 0.08. CONCLUSIONS: Lung inhomogeneities can lead to significant variations in delivered dose between patients treated in a clinical trial. Existing density-correction algorithms are accurate enough to significantly reduce these variations.

Algorithms↗