An anthropomorphic 1H MRS head phantom has been developed which mimics the in vivo structure, metabolite concentrations, and relaxation times (for both water and metabolites) of human brain tissue. Different brain regions and two tumor types, fluid-containing ventricles, and air-filled sinus, and subcutaneous fat are all simulated. The main tissue-mimicking materials are gelatin/agar mixtures with metabolites and several other ingredients added. Their composition and method of production are thoroughly described. T1's and T2's of water in the phantom are very close to in vivo values, and metabolite T1's and T2's are considerably more realistic than those in aqueous solutions. Spectra and relaxation times for the pig brain were also acquired and compare well with those of the phantom. The realistic properties of this phantom should be useful for testing spectral quantitation and localization.

An editable rounded leaf offset (RLO) table is provided in the Pinnacle3 treatment planning software. Default tables are provided for major linear accelerator manufacturers, but it is not clear how the default table values should be adjusted by the user to optimize agreement between the calculated leaf tip value and the actual measured value. Since we wish for the calculated MLC‐defined field edge to closely match the actual delivered field edge, optimal RLO table values are crucial. This is especially true for IMRT fields containing a large number of segments, since any errors would add together. A method based on the calculated MLC‐defined field edge was developed for optimizing and modifying the default RLO table values. Modified RLO tables were developed and evaluated for both dosimetric and light field‐based MLC leaf calibrations. It was shown, using a Picket Fence type test, that the optimized RLO table better modeled the calculated leaf tip than the Pinnacle3 default table. This was demonstrated for both an Elekta Synergy 80‐leaf and a Varian 120‐leaf MLC.PACS numbers: 87.55.D‐, 87.55.de, 87.55.Qr

Seven adults with painful effusions of the knee were examined for occult fractures using pluridirectional tomography in the coronal and lateral planes. Six patients (ages 50-82 years) were osteopenic and gave histories ranging from none to mild trauma; one 26-year-old man was not osteopenic and had severe trauma. In all cases, routine radiographs were interpreted as negative, but tomography demonstrated a fracture. Five fractures were subchondral. Bone scans in 2 patients were positive. The authors conclude that osteopenic patients with a painful effusion of the knee should be considered to have an occult fracture. While bone scans may be helpful, tomography is recommended as the procedure of choice to define the location and extent of the fracture.

Purpose: Manufacturer recommended rounded leaf offsets for the Philips Pinnacle treatment planning system are inaccurate for leaves away from the central axis, and for varying energies. The need for an in‐house MLC rounded leaf offset correction is established, as well as a method for determining the offsets for individual MLC leaves. Materials and Methods: A standard picket‐fence test is developed with 2 cm separations across a 25×25 field. Dose distributions are calculated for the test, with 20th leaf offset values for the X = 0.0 position ranging from −2.0 to +2.0 mm from the nominal leaf position, using the manufacturer recommended offset curve for leaves 1–40. Dose profiles are collected along the cross‐plane of the 20th leaf. The picket‐fence test plan is delivered to a film, in phantom at 90cm SSD and 10 cm depth, for 6 and 10 MV energies. Dose profiles are measured through the central axis and superimposed on the calculated profiles produced by the TPS. The profiles are compared for agreement. Results: It was found that the measured dose profiles do not match manufacturer recommended offsets for leaves away from the central axis. If the calibrated leaf (20th) is matched to the tabular data, there is deviation in the picket‐fence test at distances >5.0 cm from the central axis, resulting is dose discrepancies. Manufacturer‐recommended offsets were also observed to be inaccurate for the 10 MV beam, exhibiting an energy‐dependence of the required offset values. Conclusions: It is found that manufacturer recommended rounded leaf offsets are inaccurate and in‐house measurements are required to determine appropriate offsets for groups of leaves near and away from the beam's central axis. It was also found that there is an energy dependence for these offsets. A method for making in‐house corrections is established by using measured and calculated dose distributions.

Purpose: A tumor control probability (TCP) model incorporating a generalized linear‐quadratic (gLQ) model was investigated to predict clinical outcome after radiation therapy for patients. The clinical utility of the model incorporating the following individually measured radiobiology parameters: intrinsic radiosensitivity, proliferation and number of clonogenic cells, was evaluated. The hypothesis in the study was that the incorporation of individually measured tumor parameters into the TCP model would increase its reliability in predicting treatment outcome compared with the use of average population derived data. Methods: 46 patients with head and neck tumors were included and most of them received both external beam radiotherapy and brachytherapy (as published in Acta Oncologica, 2009; 48:584–590). Primary tumor size was drawn from case records and pre‐treatment CT scans or MRI using two or three dimensional measurements to calculate tumor volume. Surviving fraction after 2 Gy (SF2), reflecting intrinsic radiosensitivity, was estimated by a soft‐agar clonogenic assay (as published in Int J Radiat Oncol Bio Phys, 2000; 46:13–19). Eighteen patients receiving external beam treatment alone were used to perform statistical analyses. Local control was determined by follow‐up records. Results: SF2 correlated significantly with tumor response (p=0.04, Mann‐Whitney test), but initial tumor volume did not (p=0.6). Eight of the 18 patients had a >95% calculated tumor control probability and none developed a local recurrence, yielding a negative predictive value of 100%, compared with 67% for population‐derived data. There was a statistically significant difference in local control levels between the patient group with >95% vs. <5% predicted probability of local control (p<0.001). Conclusion: The results suggest that incorporation of measured biological data within a TCP radiobiological model would improve its ability to predict radiation therapy outcome.