Fast, Automated, Knowledge-Based Treatment Planning for Selecting Patients for Proton Therapy Based on Normal Tissue Complication Probabilities.

Purpose: Selecting patients who will benefit from proton therapy is laborious and subjective. We demonstrate a novel automated solution for creating high-quality knowledge-based plans (KBPs) using proton and photon beams to identify patients for proton treatment based on their normal tissue complication probabilities (NTCP).

Methods And Materials: Two previously validated RapidPlan PT models for locally advanced head and neck cancer were used in combination with scripting to automatically create proton and photon KBPs for 72 patients with recent oropharynx cancer.

Coherent active-sterile neutrino flavor transformation in the early universe.

We solve the problem of coherent Mikheyev-Smirnov-Wolfenstein resonant active-to-sterile neutrino flavor conversion driven by an initial lepton number in the early Universe. We find incomplete destruction of the lepton number in this process and a sterile neutrino energy distribution with a distinctive cusp and high energy tail. These features imply alteration of the nonzero lepton number primordial nucleosynthesis paradigm when there exist sterile neutrinos with rest masses m(s) approximately 1 eV.