Renal Dosimetry

July 5, 2017 | Autor: Marta Cremonesi | Categoria: Humans, Kidney, Radiometry, Theoretical Models, Pamphlets, Predictive value of tests
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CANCER BIOTHERAPY AND RADIOPHARMACEUTICALS Volume 25, Number 5, 2010 ª Mary Ann Liebert, Inc. DOI: 10.1089/cbr.2010.0867

Renal Dosimetry Barry W. Wessels,1 Roger G. Dale,2 Marta Cremonesi,3 Ruby F. Meredith,4 Alan J. Green,5 Bertrand Brill,6 Wesley E. Bolch,7 George Sgouros,8 and Stephen R. Thomas9

Dear Editors: This letter is in response to the letter to the Editor by Siegel, Stabin, and Sharkey regarding renal dosimetry, and their corresponding article, which appears in this current issue of Cancer Biotherapy and Radiopharmaceuticals. Because of publication deadlines associated with this issue of the journal, and the unusual nature of the exchange (authors writing a letter to the editor in response to their own article), we did not have sufficient time to address all issues and criticisms that Siegel et al. highlighted in their letter. Accordingly, this letter only responds to the major items of discussion raised in the article and letter by Siegel et al., and is signed only by MIRD Pamphlet 20 authors that had an opportunity to review this response. The major issues include: 1. The MIRD Committee and the Pamphlet 20 Task Group observed from reports in the literature that a number of patients who had undergone peptide radionuclide receptor therapy (PRRT), Ho-166 therapy, and other radionuclide therapies in which the kidney was an organ at risk (OAR), experienced severe renal toxicity and, in several cases, renal failure and death.1 Furthermore, it was clear, from a total-dose analysis to the OAR of the early radionuclide therapy clinical trials, that the direct application of Emami et al.2 or QUANTEC4 external beam limits would not ensure patient safety. MIRD Pamphlet 201 demonstrated that the application of common organ toxicity limits based on 2-Gy fractions from external beam experience could lead to unanticipated toxicity when applied to radiopharmaceutical therapy with low molecular-weight, rapidly clearing agents. Primarily, dose rate must be brought into the picture as a first order correction. Figure 2 of reference 1

(not shown here) shows that, if 15 Gy is delivered to the kidney in 6 hours from I-131 radionuclide therapy, kidney failure is predicted. Using these kinetics, if this same total absorbed-dose radiation is delivered in 24 hours, kidney tolerance is likely. With this insight,4 fractionation and clearing agents were introduced as part of the clinical protocol for these agents, and the kidney toxicity was significantly reduced. MIRD Pamphlet 201 provides the best method currently available to perform these radiobiological calculations so that future clinical trials will benefit from the critical evaluation offered by these predictive models and assist in their refinement. Like all predictive models, the model described in this pamphlet will have its limitations and acquisition of new data will provide further enlightenment and the opportunity to refine the time–dose algorithms used in our kidney-response model. Notably, MIRD Pamphlet 201 and MIRD Pamphlet 195 also provide insight on how one might account for nonuniformity in tissue uptake and clearance, type of radiation emitted by the radionuclide, and organ-specific tissue radiosensitivity parameters. We anticipate introducing these variables into the model as more information becomes available. As it stands, the model described in MIRD Pamphlet 201 is an extremely useful tool for predicting dose-limiting kidney toxicity encountered in therapeutic applications of radiolabeled peptides. 2. We address the issue of patient-specific dosimetry brought up by the letter by Siegel et al. Without question, we support patient-specific and tissue-specific techniques to the extent that they can be reasonably achievable. However, one should not be misled by Segel et al.’s assertion that we cannot move forward

1 Department of Radiation Oncology, Case Western Reserve University School of Medicine, and University Hospitals Case Medical Center, Cleveland, Ohio. 2 Radiation Physics and Radiobiology, Imperial Healthcare NHS Trust, London, United Kingdom. 3 Medical Physics Division, European Institute of Oncology, Milan, Italy. 4 University of Alabama at Birmingham, Birmingham, Alabama. 5 CRC Targeting and Imaging Group, Dept. of Oncology, Royal Free and University College Medical School, University College London, London, United Kingdom. 6 Department of Radiology, Vanderbilt University, Nashville, Tennessee. 7 Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, Florida. 8 Department of Radiology and Radiological Sciences, School of Medicine, The Johns Hopkins University, Baltimore, Maryland. 9 Department of Radiology, University of Cincinnati, Cincinnati, Ohio.

Address correspondence to: Barry W. Wessels; Department of Radiation Oncology, University Hospitals Case Medical Center; B-181 Lerner Tower, 11100 Euclid Avenue, Cleveland, Ohio 44106 E-mail: [email protected]

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598 unless we absolutely know everything about the patient’s ‘‘specifics.’’ Not all specifics are known, and having all patient parameters is neither necessary nor required to practice ‘‘good and safe’’ clinical physics and dosimetry. For example, patient-specific tissue radiosensentivity factors are acquired in conjunction with external beam therapy, but have not come into general clinical use.6 Why not? Significance, cost, and relevance to clinical outcome all play a part in this answer. However, to not provide a solid basis for specifying critical treatment parameters including total doseto–target volume, dose per fraction, and whole or partial organ tolerance dose to OARs in external beam therapy, would not be acceptable. We currently have patients ‘‘on the table,’’ both for external beam therapy and radionuclide therapy. These patients demand ‘‘safe’’ approaches for addressing critical treatment issues, and it is our responsibility to provide treatment solutions based on our current state of knowledge. We cannot return to ‘‘an ivory tower’’ approach and wait to gather all patient-specific information before we act. It is unlikely that all patient-specific information can ever be known, and, therefore, the ‘‘ivory tower’’ approach is likely to harm more patients than are helped. The good physicist/dosimetrist will help our medical colleagues sort out relevant safety and efficacy issues based on the best information available and recommend treatment or no treatment based on their findings. 3. We next review the use of radiobiological models for external beam and radionuclide therapy. The use of the time–dose fractionation (TDF) model in this application by Siegel et al. represents a phenomenological reach into the past. At one point they claim nonendorsement of TDF, but later indicate that TDF is marginally better than the linear-quadratic (LQ) model in limited circumstances. To several of us many years ago, the TDF model provided useful tables to compare one external beam therapy fractionation scheme to another. However, that concept was removed from a prominent radiobiology textbook, 7 because the concept lacked any theoretical basis other than ‘‘curve fitting.’’ LQ has a biophysical basis, which, with caveats, allows it to be adapted to different patterns of radiation delivery. The original TDF model was derived from the Ellis formula (applicable to external beam radiation, [XRT] only) and therefore inherited the limitations of the latter. Siegel et al., in fact, switched this notion 180 degrees in the last statement of the manuscript abstract. The extension of TDF to cover therapy with variable dose rate was purely a mathematical manipulation of the original version and was not radiobiologically based. The main objections to TDF are a lack of tissue-specific factors, lack of any coherent view of repair or repopulation kinetics, and lack of a clear meaning for "tolerance"—early or late effects. Moreover, TDF would suffer from exactly the same criticisms as are being purported by Siegel et al. against the LQ model, in stating that, despite earlier attempts to extend its applicability, it may go awry when partial irradiation is compared with uniform irradiation.3 In MIRD Pamphlet 20,1 we made no claim that LQ was the only model that could arrive at the basic dose rate observations associated with radiation therapy. LQ happens to be the model

LETTER TO THE EDITOR that is currently most accepted.8,9 So what is the significance of the science presented in the Siegel et al. article? Was it to show that a model recognized to be outdated— and with no theoretical underpinning—can empirically describe the first order dose-rate phenomena in the radiobiology of radiopharmaceuticals? If this was the objective, the authors have succeeded—but to what end? Perhaps XRT does translate to radionuclide therapy, at least in terms of conversions of dose rate patterns of the first order for many of the basic and historical dose conversion models. But why use historical models going forward, especially, when it will be more difficult to adapt them to patient-specific approaches? Furthermore, is there any novelty in Siegel et al.’s finding that TDF and LQ can yield similar results when applied to radionuclide therapy? Comments 1–4 by Siegel et al. regarding grouping of patients, relative effectiveness (RE) used for external-beam data conversion to biologically effective dose (BED) values, binning of data when small sample size was encountered, and restating asymptotic behavior of both the BED and TDF models at protracted irradiation times (Fig 1B in MIRD Pamphlet 201; not shown here) are secondary in nature. In all cases, model limits and assumptions used in MIRD Pamphlet 201 were stated explicitly. For example, regarding the compilation of the Barone and Bodei data sets, MIRD Pamphlet 201 clearly states that ‘‘compilation of data from nearly a dozen sources over the past 30 years’’ contributes to the ‘‘PRRT data uncertainty from 10 [to] 25 %,’’ knowing that their data collection and analysis methods differ. As stated in MIRD Pamphlet 20,1 Table 2 (not shown here), BED values were generated from the external beam data using an RE of 1.6. The most recent compilation of kidney data given by the QUANTEC effort3 suggests this value may be 1.4. These detailed comments do provide an improvement in our, ‘‘closer than ever’’ patient-specific modeling approaches described in MIRD Pamphlet 195 and MIRD Pamphlet 20.1 It was known to authors of MIRD Pamphlet 201 that selection of specific data parameters in our examples 1–4 would not elucidate all extremes of model behavior. Accordingly, the MIRD Committee has begun development of a web-based software tool that implements the kidney dose–response model using MIRD Pamphlet 201 expressions as a starting point. If the user wishes to change input data and constant values used in the model (dose, radionuclide, T rep, T eff, a/b ratio), it can be accomplished online. In summary, in their analysis of Pamphlets 195 and 20,1 Siegel et al. missed an important opportunity to clarify the scientific and technical issues for your readers. Akin to missing the forest for the trees, these researchers focused on minor aspects of these two publications to criticize, and also, regrettably, to promote a phenomenological model (TDF) that was abandoned by the radiobiology community in the early 1980s.10 This approach does little to advance science or help the medical community. It is not apparent how such an effort contributes to refinement of the models that currently deserve the most widespread use. References 1. Wessels BW, Konijnenberg MW, Dale RG, et al. MIRD Pamphlet No. 20: The effect of model assumptions on kidney

LETTER TO THE EDITOR

2. 3.

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dosimetry and response—implications for radionuclide therapy. J Nucl Med 2008;49:1884. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21:109. Dawson LA, Kavanagh BD, Paulino AC, et al. Radiationassociated kidney injury. Int J Radiat Oncol Biol Phys 2010;76:S108. Cremonesi M, Ferrari M, Bodei L, et al. Dosimetry in peptide radionuclide receptor therapy: A review. J Nucl Med 2006;47:1467. Bouchet LG, Bolch WE, Blanco HP, et al. MIRD Pamphlet No 19: Absorbed fractions and radionuclide S values for six age-dependent multiregion models of the kidney. J Nucl Med 2003;44:1113.

599 6. Geara FB, Peters LJ, Ang KK, et al. Prospective comparison of in vitro normal cell radiosensitivity and normal tissue reactions in radiotherapy patients. Int J Radiat Oncol Biol Phys 1993;27:1173. 7. Hall EJ. Radiobiology for the Radiologist, 2nd ed. Philadelphia: Harper & Row, 1978. 8. Fowler JF. 21 years of biologically effective dose. Br J Radiol 2010;83:554. 9. Brenner DJ, Hlatky LR, Hahnfeldt PJ, et al. The linearquadratic model and most other common radiobiological models result in similar predictions of time–dose relationships. Radiat Res 1998;150:83. 10. Thames HD and Hendry JH. Fractionation in Radiotherapy. London: Taylor & Francis, 1987.

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