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Radiobiological advantage of megavoltage grid therapy
Proceedings of the 43rd Annual ASTRO Meeting
Conclusions: (a) Dose-rate effects are relevant to differences between IMRT delivery methods, and conformal radiotherapy when automation is introduced to decrease delivery time. (b) “Fast” IMRT (total fraction delivered to each tissue volume in 1-2 mins.) may increase the biologically effective dose by ⬃10% compared to “slow” IMRT (total fraction delivered in about 10 minutes). (c) Late-responding normal tissues are theoretically expected to have an increased dose-rate effect compared to tumors, consistent with larger recovery between fractions, although this is yet to be clinically established. (d) Potentially, therefore, prolonged fractions could be used to increase local control at a constant rate of late-complications; or, at lower doses, similar local control could be achieved at reduced rates of late-complications. (e) Dose-rate effects would be expected to make cell survival probability more non-uniform over the planning target volume than the dose distribution would indicate, as different parts of the target in IMRT typically receive dose for a variable fraction of the total delivery time. (f) More data on the dose-rate effect, including in vitro cell survival experiments comparing faster and slower micro-fractionated sequences relevant to IMRT, are needed to draw more precise quantitative conclusions. Nevertheless, (g) IMRT planning algorithms should avoid, where possible, very rapid delivery of dose to dose-limiting normal structures. This is a reasonable principle, which could potentially be built into the optimization or delivery sequence algorithms, even though the level of sparing is not precisely known. Partially supported by NCI grant CA85181.
2333
Radiobiological Advantage of Megavoltage Grid Therapy
R.D. Zwicker, A. Meigooni, M. Mohiuddin Radiation Medicine Department, University of Kentucky, Lexington, KY Purpose: The advantages of grid use in large dose irradiation have been well known since the era of orthovoltage radiotherapy. It was found then that when small areas of the skin and underlying tissues were shielded, these protected areas served as centers for regrowth of normal tissues. More recently, megavoltage grid therapy has been used to deliver large single fractions of radiation to patients with bulky, deeply seated tumors who have already been treated to tolerance, or to debulk the tumor by reducing significantly the tumor cell population prior to the initiation of fractionated radiotherapy. In the present work we make use of standard linear quadratic modeling of cell kill to compare the effects of megavoltage grid therapy to those of uniform dose delivery on tumor and normal tissues at high single fraction dose levels. Materials and Methods: In the linear quadratic model the surviving fraction of cells following a radiation dose D is determined from the formula S⫽exp(-␣D - D2), where ␣ and  are characteristic of the tissue under irradiation. Widely used values of ␣/ are 10.0 Gy for tumors and 2.5 Gy for normal tissues. A typical 2.0-Gy surviving fraction SF2 is about 50%. Radioresistant tumors are expected to have a higher SF2. These values of ␣/ were used to compare the surviving fraction of cells in tumor and normal tissues subjected to grid irradiation at maximum dose levels of 10.0, 15.0, and 20.0 Gy, with half the irradiated volume shielded and receiving only 25% of the maximum dose. Dose change with depth was ignored in the present simple model. To assess the therapeutic effect of grid irradiation, equivalent uniform doses were determined which would yield the same average tumor cell survival in the irradiated volume, and the consequent surviving fractions were determined for adjacent normal tissues subjected to the same uniform dose. The ratio of the normal-tissue surviving fraction under grid irradiation to that obtained under equivalent (for tumor cells) uniform dose irradiation was taken as a measure of therapeutic gain. Results: The therapeutic ratio was examined for the maximum dose levels listed above, with the tumor cell SF2 varied between 0.3 and 0.7, representing a range of tumor types from sensitive to radioresistant. For the case of SF2 equaling 0.5 for both tumor and normal tissues, a therapeutic ratio ranging from 1.35 for 10.0 Gy to 1.65 for 20.0 Gy irradiation was found. With SF2 held at 0.5 for normal tissues and varied from 0.3 to 0.7 for tumor cells, the therapeutic ratio varied from a low of 0.88 for SF2 ⫽ 0.3 at the 10.0 Gy dose level to a high of 5.4 for SF2⫽0.7 at the 20.0 Gy level. Conclusion: The results found here indicate that with high single fraction doses, partial volume irradiation may be therapeutically advantageous over uniform dose irradiation for a wide range of cell types. This is particularly true of tumor cells which are considered radioresistant, as characterized by larger values of SF2, and for radiosensitive normal tissues, where a significant reduction in normal tissue cell kill was found to result from the use of a grid.
2334
Effect of Tissue Segmentation Variabilities on Treatment Outcome
E.L. Chaney, T.J. Cullip Radiation Oncology, University of North Carolina, Chapel Hill, NC,CNY Purpose: All 3D RTP systems require a model of the patient for localizing and displaying objects of interest, positioning the isocenter(s) of the treatment beams, shaping the radiation beams to conform to the outline of the target volume, incorporating tissue inhomogeneities into dose calculations, and computing volume-weighted metrics such as dose-volume histograms (DVHs), normal tissue complication probabilities (NTCPs), and tumor control probabilities (TCPs). The anatomical structures comprising the patient model must be defined by segmenting one or more volume images, usually CT and MR images. Most segmentation methods in routine use are user-guided and require decisions that are affected by factors such as display device and settings, lighting environment, the interactive user interface, user training and experience, the perceived importance of the object in the treatment plan, user fatigue, and time constraints. As a result of these and other factors, if the same object is defined repeatedly from the same image data using current clinical practices, both inter- and intra-user variabilities will be evident. The potential effects of these variabilities on treatment outcome have not been well studied. DVHs, NTCPs, and TCPs computed during treatment planning in general will not demonstrate significant differences for alternate segmentations. However these metrics are computed from treatment “snap shots” which do not account for treatment uncertainties that cause the planning target volume and organs at risk (OARs) to be in different positions relative to the treatment beam for each daily treatment. In
401
Conclusions: (a) Dose-rate effects are relevant to differences between IMRT delivery methods, and conformal radiotherapy when automation is introduced to decrease delivery time. (b) “Fast” IMRT (total fraction delivered to each tissue volume in 1-2 mins.) may increase the biologically effective dose by ⬃10% compared to “slow” IMRT (total fraction delivered in about 10 minutes). (c) Late-responding normal tissues are theoretically expected to have an increased dose-rate effect compared to tumors, consistent with larger recovery between fractions, although this is yet to be clinically established. (d) Potentially, therefore, prolonged fractions could be used to increase local control at a constant rate of late-complications; or, at lower doses, similar local control could be achieved at reduced rates of late-complications. (e) Dose-rate effects would be expected to make cell survival probability more non-uniform over the planning target volume than the dose distribution would indicate, as different parts of the target in IMRT typically receive dose for a variable fraction of the total delivery time. (f) More data on the dose-rate effect, including in vitro cell survival experiments comparing faster and slower micro-fractionated sequences relevant to IMRT, are needed to draw more precise quantitative conclusions. Nevertheless, (g) IMRT planning algorithms should avoid, where possible, very rapid delivery of dose to dose-limiting normal structures. This is a reasonable principle, which could potentially be built into the optimization or delivery sequence algorithms, even though the level of sparing is not precisely known. Partially supported by NCI grant CA85181.
2333
Radiobiological Advantage of Megavoltage Grid Therapy
R.D. Zwicker, A. Meigooni, M. Mohiuddin Radiation Medicine Department, University of Kentucky, Lexington, KY Purpose: The advantages of grid use in large dose irradiation have been well known since the era of orthovoltage radiotherapy. It was found then that when small areas of the skin and underlying tissues were shielded, these protected areas served as centers for regrowth of normal tissues. More recently, megavoltage grid therapy has been used to deliver large single fractions of radiation to patients with bulky, deeply seated tumors who have already been treated to tolerance, or to debulk the tumor by reducing significantly the tumor cell population prior to the initiation of fractionated radiotherapy. In the present work we make use of standard linear quadratic modeling of cell kill to compare the effects of megavoltage grid therapy to those of uniform dose delivery on tumor and normal tissues at high single fraction dose levels. Materials and Methods: In the linear quadratic model the surviving fraction of cells following a radiation dose D is determined from the formula S⫽exp(-␣D - D2), where ␣ and  are characteristic of the tissue under irradiation. Widely used values of ␣/ are 10.0 Gy for tumors and 2.5 Gy for normal tissues. A typical 2.0-Gy surviving fraction SF2 is about 50%. Radioresistant tumors are expected to have a higher SF2. These values of ␣/ were used to compare the surviving fraction of cells in tumor and normal tissues subjected to grid irradiation at maximum dose levels of 10.0, 15.0, and 20.0 Gy, with half the irradiated volume shielded and receiving only 25% of the maximum dose. Dose change with depth was ignored in the present simple model. To assess the therapeutic effect of grid irradiation, equivalent uniform doses were determined which would yield the same average tumor cell survival in the irradiated volume, and the consequent surviving fractions were determined for adjacent normal tissues subjected to the same uniform dose. The ratio of the normal-tissue surviving fraction under grid irradiation to that obtained under equivalent (for tumor cells) uniform dose irradiation was taken as a measure of therapeutic gain. Results: The therapeutic ratio was examined for the maximum dose levels listed above, with the tumor cell SF2 varied between 0.3 and 0.7, representing a range of tumor types from sensitive to radioresistant. For the case of SF2 equaling 0.5 for both tumor and normal tissues, a therapeutic ratio ranging from 1.35 for 10.0 Gy to 1.65 for 20.0 Gy irradiation was found. With SF2 held at 0.5 for normal tissues and varied from 0.3 to 0.7 for tumor cells, the therapeutic ratio varied from a low of 0.88 for SF2 ⫽ 0.3 at the 10.0 Gy dose level to a high of 5.4 for SF2⫽0.7 at the 20.0 Gy level. Conclusion: The results found here indicate that with high single fraction doses, partial volume irradiation may be therapeutically advantageous over uniform dose irradiation for a wide range of cell types. This is particularly true of tumor cells which are considered radioresistant, as characterized by larger values of SF2, and for radiosensitive normal tissues, where a significant reduction in normal tissue cell kill was found to result from the use of a grid.
2334
Effect of Tissue Segmentation Variabilities on Treatment Outcome
E.L. Chaney, T.J. Cullip Radiation Oncology, University of North Carolina, Chapel Hill, NC,CNY Purpose: All 3D RTP systems require a model of the patient for localizing and displaying objects of interest, positioning the isocenter(s) of the treatment beams, shaping the radiation beams to conform to the outline of the target volume, incorporating tissue inhomogeneities into dose calculations, and computing volume-weighted metrics such as dose-volume histograms (DVHs), normal tissue complication probabilities (NTCPs), and tumor control probabilities (TCPs). The anatomical structures comprising the patient model must be defined by segmenting one or more volume images, usually CT and MR images. Most segmentation methods in routine use are user-guided and require decisions that are affected by factors such as display device and settings, lighting environment, the interactive user interface, user training and experience, the perceived importance of the object in the treatment plan, user fatigue, and time constraints. As a result of these and other factors, if the same object is defined repeatedly from the same image data using current clinical practices, both inter- and intra-user variabilities will be evident. The potential effects of these variabilities on treatment outcome have not been well studied. DVHs, NTCPs, and TCPs computed during treatment planning in general will not demonstrate significant differences for alternate segmentations. However these metrics are computed from treatment “snap shots” which do not account for treatment uncertainties that cause the planning target volume and organs at risk (OARs) to be in different positions relative to the treatment beam for each daily treatment. In
401