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SUMMARY:Constraining CP Invariance in Ortho-Positronium Decays at 7 T with
  NeuroSphere MR-Compatible PET Modules
DTSTART;VALUE=DATE-TIME:20260911T091000Z
DTEND;VALUE=DATE-TIME:20260911T095000Z
DTSTAMP;VALUE=DATE-TIME:20260922T173908Z
UID:indico-contribution-424-2061@events.ncbj.gov.pl
DESCRIPTION:Speakers: Magdelena S. Allen (MGH Athinoula A. Martinos Center
  for Biomedical Imaging)\nPositron Emission Tomography (PET) systems can m
 easure the decay properties of ortho-positronium (oPs)\, an intermediate b
 ound state often formed during positron-electron annihilation that decays 
 to photons after a short lifetime. The lifetime and decay kinematics of oP
 s can be used to probe material properties\, have potential to serve as a 
 novel biomarker in disease\, and can be used test the Standard Model. Addi
 tional sources of charge conjugation-parity (CP) symmetry violation are re
 quired to explain the observed matter-antimatter imbalance in the Universe
 \, and CP violation can be constrained by measuring decays under the rever
 sal of an applied magnetic field. A dedicated physics measurement platform
  was constructed from the architecture of the NeuroSphere brain PET insert
  for 7-T MRI\, including a PET detector array\, positronium target with li
 fetime trigger\, and motorized gantry for control of the system orientatio
 n inside the 7-T environment. GATE simulations were used to inform the dev
 elopment of a custom data analysis pipeline for oPs event selection and mu
 lti-coincidence processing. Systematics were mitigated by combining runs w
 ith various target and detector positions (to average out artificial asymm
 etries caused by assembly or detector efficiency) and by applying a baseli
 ne correction from events in a kinematic region with vanishing analyzing p
 ower (to account for drift and complex field- and material-related effects
 ).  decays in polyvinyltoluene (PVT) were measured at 7 T\, finding a long
  lifetime component near 100 ns and CP violation consistent with zero. Thi
 s work demonstrates the unique opportunity provided by PET/MR instrumentat
 ion to perform high-field physics measurements and proof-of-concept for me
 asuring positronium decays with the full NeuroSphere system.\n\nhttps://ev
 ents.ncbj.gov.pl/event/468/contributions/2061/
LOCATION:
URL:https://events.ncbj.gov.pl/event/468/contributions/2061/
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BEGIN:VEVENT
SUMMARY:AI and Monte Carlo Particle Transport in Medical Imaging and Radio
 therapy
DTSTART;VALUE=DATE-TIME:20260911T083000Z
DTEND;VALUE=DATE-TIME:20260911T091000Z
DTSTAMP;VALUE=DATE-TIME:20260922T173908Z
UID:indico-contribution-424-2060@events.ncbj.gov.pl
DESCRIPTION:Speakers: Nils Krah (INSA Lyon)\nMonte Carlo particle transpor
 t is a cornerstone of simulation in medical imaging and radiotherapy\, but
  its computational cost can limit its use. Artificial intelligence offers 
 several routes to accelerate these simulations\, from denoising low-statis
 tics results and predicting dose distributions to learning detector respon
 ses and generating particle phase spaces.\n\nThis talk surveys these appro
 aches through medical applications\, including nuclear imaging\, radiother
 apy dose calculation\, and optical photon transport in radiation detectors
 . It examines what each model learns\, which parts of the simulation it re
 places\, and how its output can be validated. Particular attention is give
 n to the distinction between reproducing an average response and preservin
 g the probability distributions and correlations needed for reliable simul
 ation.\n\nThe discussion also extends to AI-assisted radiotherapy planning
 \, where a predicted dose distribution must be converted into a physically
  deliverable treatment plan. Together\, these examples highlight the oppor
 tunities for combining AI with Monte Carlo methods and the importance of e
 valuating the complete workflow\, beyond prediction accuracy or computatio
 nal speed alone.\n\nhttps://events.ncbj.gov.pl/event/468/contributions/206
 0/
LOCATION:
URL:https://events.ncbj.gov.pl/event/468/contributions/2060/
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BEGIN:VEVENT
SUMMARY:Multi‑Start Likelihood Reconstruction with Bayesian Penalisation
  for Low‑Statistic Positronium Lifetime Imaging
DTSTART;VALUE=DATE-TIME:20260911T095000Z
DTEND;VALUE=DATE-TIME:20260911T102000Z
DTSTAMP;VALUE=DATE-TIME:20260922T173908Z
UID:indico-contribution-424-2039@events.ncbj.gov.pl
DESCRIPTION:Speakers: Roman Shopa (National Centre for Nuclear Research)\n
 We explore the adaptive algorithm in Positronium Lifetime Imaging (PLI)\, 
 a new technique that analyses the local behaviour of positronium (Ps) – 
 a quasi-stable electron-positron ($e^−e^+$) compound [1]. Voxel-dependen
 t Ps lifetime spectra can be acquired using Positron Emission Tomography (
 PET) with specific $\\beta^+\\gamma$ sources that emit an additional promp
 t gamma photon. But mostly due to a need for 3-photon coincidence data\, t
 he sensitivity is much lower than in standard PET [2].\n\nBased on the pre
 vious development of PLI algorithms based on non-linear fitting of noisy v
 oxel-dependent Ps lifetime spectra [3]\, we further address the challenge 
 of low-count data. A multi-variable Bayesian penalisation factor is added 
 to the negative log‑likelihood minimisation\, using prior information fr
 om the approximate low-resolution image. There is a major issue that the m
 ulti-channel Ps decay model tends to overfit and converge to local minima.
  A proposed solution is a multi-start optimisation with random initial gue
 sses\, split into two stages – each with different variables fixed or pe
 nalised from priors.\n\nWe also conduct an inferential analysis of the ini
 tial guess distributions and their adjustment to the regions that converge
  best. That allows for a decrease in their minimal number for successful m
 inimisation and for a performance boost of the PLI algorithm.\n\n[1] Deuts
 ch M. Phys.Rev. 82 455 (1951)\n[2] Huang B et al. Comm.Phys. 8 1 (2025)\n[
 3] Shopa RY\, Dulski K. BAMS 19 54 (2023)\n\nhttps://events.ncbj.gov.pl/ev
 ent/468/contributions/2039/
LOCATION:
URL:https://events.ncbj.gov.pl/event/468/contributions/2039/
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