A method has been devised for the electro- MATERIALS AND METHODS Immunogens and Immunization Procedures. Escherichia coli ribosomal proteins L7 and L12 were extracted (10) from 50S subunits and purified as described (11) by ion-exchange chromatography on carboxymethyl-and DEAE-cellulose. Antibodies were raised in a goat by injecting 250 jig of protein emulsified with complete Freund's adjuvant intracutaneously distributed over several sites. Bacillus pertussis vaccine (1.5 ml of Bordet-Gengou vaccine, Schweizerisches Serum-und Impfinstitut, Bern, Switzerland) was given subcutaneously with every antigen injection. Booster injections of the same formulation were given on days 38, 79, and 110. The animal was bled on day 117.Subunits from chicken liver ribosomes (12) were combined in equimolar amounts, and 200-iAg aliquots were emulsified with 125 Al of complete Freund's adjuvant injected at one intraperitoneal and four subcutaneous sites into BALB/c mice. Booster injections of 400 ,ig of ribosomes in saline were given intraperitoneally on days 33, 57, 58, and 59. The animals were bled on day 71. Electrophoretic Blotting Procedures. Proteins were first subjected to electrophoresis in the presence of urea either in two dimensions (12) or in one-dimensional slab gels corresponding to the second dimension of the same two-dimensional system. The proteins were then transferred to nitrocellulose sheets as follows. The physical assembly used is shown diagrammatically in Fig. 1. A sheet of nitrocellulose (0.45 ,im pore size in roll form, Millipore) was briefly wetted with water and laid on a scouring pad (Scotch-Brite) which was supported by a stiff plastic grid (disposable micropipette tray, Medical Laboratory Automation, Inc., New York). The gel to be blotted was put on the nitrocellulose sheet and care was taken to remove all air bubbles. A second pad and plastic grid were added and rubber bands were strung around all layers. The gel was thus firmly and evenly pressed against the nitrocellulose sheet. The assembly was put into an electrophoretic destaining chamber with the nitrocellulose sheet facing the cathode. The chamber contained 0.7% acetic acid. A voltage gradient of 6 V/cm was applied for 1 hr.For polyacrylamide electrophoresis in the presence of sodium dodecyl sulfate (13) instead of urea, the procedure was as det To whom reprint requests should be addressed. 4350The publication costs of this article were defrayed in part by page charge payment. This article must therefore be hereby marked "advertisement" in accordance with 18 U. S. C. §1734 solely to indicate this fact.

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It was previously shown that the poliovirus-

This work ͑i͒ proposes a probabilistic treatment planning framework, termed coverage optimized planning ͑COP͒, based on dose coverage histogram ͑DCH͒ criteria; ͑ii͒ describes a concrete proofof-concept implementation of COP within the PINNACLE treatment planning system; and ͑iii͒ for a set of 28 prostate anatomies, compares COP plans generated with this implementation to traditional PTV-based plans generated with planning criteria approximating those in the high dose arm of the Radiation Therapy Oncology Group 0126 protocol. Let D v denote the dose delivered to fractional volume v of a structure. In conventional intensity modulated radiation therapy planning, D v has a unique value derived from the static ͑planned͒ dose distribution. In the presence of geometric uncertainties ͑e.g., setup errors͒ D v assumes a range of values. The DCH is the complementary cumulative distribution function of D v . DCHs are similar to dose volume histograms ͑DVHs͒. Whereas a DVH plots volume v versus dose D, a DCH plots coverage probability Q versus D. For a given patient, Q is the probability ͑i.e., percentage of geometric uncertainties͒ for which the realized value of D v exceeds D. PTV-based treatment plans can be converted to COP plans by replacing DVH optimization criteria with corresponding DCH criteria. In this approach, PTVs and planning organ at risk volumes are discarded, and DCH criteria are instead applied directly to clinical target volumes ͑CTVs͒ or organs at risk ͑OARs͒. Plans are optimized using a similar strategy as for DVH criteria. The specific implementation is described. COP was found to produce better plans than standard PTV-based plans, in the following sense. While target OAR dose tradeoff curves were equivalent to those for PTV-based plans, COP plans were able to exploit slack in OAR doses, i.e., cases where OAR doses were below their optimization limits, to increase target coverage. Specifically, because COP plans were not constrained by a predefined PTV, they were able to provide wider dosimetric margins around the CTV, by pushing OAR doses up to, but not beyond, their optimization limits. COP plans demonstrated improved target coverage when averaged over all 28 prostate anatomies, indicating that the COP approach can provide benefits for many patients. However, the degree to which slack OAR doses can be exploited to increase target coverage will vary according to the individual patient anatomy. The proof-of-concept COP implementation investigated here utilized a probabilistic DCH criteria only for the CTV minimum dose criterion. All other optimization criteria were conventional DVH criteria. In a mature COP implementation, all optimization criteria will be DCH criteria, enabling direct planning control over probabilistic dose distributions. Further research is necessary to determine the benefits of COP planning, in terms of tumor control probability and/or normal tissue complication probabilities.