Using gamma–gamma coincidence measurements to validate Monte Carlo generated detector response functions

Neutron Response Function of Bonner Sphere Spectrometer With 6LiI(Eu) Detector. The detector response function was needed to measure the neutron fluence based on the count rates from Bonner Sphere Spectrometer (BSS). The determination of response function of a BSS with 6LiI(Eu) detector has been performed using Monte Carlo MCNPX code. This calculation was performed for BSS using scintillation detector of 4 mm × 4 mm 6LiI(Eu) which is placed at the center of a set of polyethylene spheres i.e bare, 2", 3", 5", 8", 10", and 12" diameters. The BSS response functions were obtained for neutron energy of 1x10-9 MeV - 1x102 MeV in 111 energy bins and each value has an uncertainty less or equal to 2 %. The response function were compared with two response functions reported in the literature i.e IAEA document in Technical Reports Series 403 (TRS-403) and the calculation from Vega-Carrillo, et al. Also validated with measurement 252Cf neutron spectra, that shown the simulated BSS spectra were quite close to the experimental measured with a differrence of 3%.

Download Full-text

Monte Carlo calculation of NaI(Tl) detector response functions for low energy gamma rays

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ◽

10.1016/0168-9002(84)90063-9 ◽

1984 ◽

Vol 226 (2-3) ◽

pp. 449-454 ◽

Cited By ~ 15

Author(s):

Kimiaki Saito ◽

Shigeru Moriuchi

Keyword(s):

Monte Carlo ◽

Gamma Rays ◽

Monte Carlo Calculation ◽

Low Energy ◽

Detector Response ◽

Response Functions ◽

Energy Gamma

Download Full-text

A new Monte Carlo assisted approach to detector response functions

Nuclear Instruments and Methods in Physics Research Section B Beam Interactions with Materials and Atoms ◽

10.1016/s0168-583x(03)01540-4 ◽

2004 ◽

Vol 213 ◽

pp. 100-104 ◽

Cited By ~ 38

Author(s):

Avneet Sood ◽

Robin P. Gardner

Keyword(s):

Monte Carlo ◽

Detector Response ◽

Response Functions

Download Full-text

A Monte Carlo simulation approach for generating NaI detector response functions (DRFs) that accounts for non-linearity and variable flat continua

Nuclear Instruments and Methods in Physics Research Section B Beam Interactions with Materials and Atoms ◽

10.1016/s0168-583x(03)01539-8 ◽

2004 ◽

Vol 213 ◽

pp. 87-99 ◽

Cited By ~ 32

Author(s):

Robin P. Gardner ◽

Avneet Sood

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Detector Response ◽

Response Functions ◽

Simulation Approach

Download Full-text

More realistic Monte Carlo calculations of photon detector response functions

Nuclear Instruments and Methods in Physics Research ◽

10.1016/0167-5087(82)90155-7 ◽

1982 ◽

Vol 199 (3) ◽

pp. 531-548 ◽

Cited By ~ 70

Author(s):

D.W.O. Rogers

Keyword(s):

Monte Carlo ◽

Detector Response ◽

Response Functions ◽

Photon Detector ◽

Monte Carlo Calculations

Download Full-text

Numerical integration of detector response functions via Monte Carlo simulations

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ◽

10.1016/j.nima.2017.05.048 ◽

2017 ◽

Vol 866 ◽

pp. 182-189 ◽

Cited By ~ 8

Author(s):

K.J. Kelly ◽

J.M. O’Donnell ◽

J.A. Gomez ◽

T.N. Taddeucci ◽

M. Devlin ◽

...

Keyword(s):

Monte Carlo ◽

Monte Carlo Simulations ◽

Numerical Integration ◽

Detector Response ◽

Response Functions

Download Full-text

An investigation of the possible interaction mechanisms for Si(Li) and Ge detector response functions by Monte Carlo simulation

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ◽

10.1016/0168-9002(86)90437-7 ◽

1986 ◽

Vol 242 (3) ◽

pp. 399-405 ◽

Cited By ~ 51

Author(s):

R.P. Gardner ◽

A.M. Yacout ◽

J. Zhang ◽

K. Verghese

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Detector Response ◽

Response Functions ◽

Interaction Mechanisms ◽

Ge Detector

Download Full-text

A detailed study of the interaction mechanisms for Si(Li) detector response functions by the direct Monte Carlo approach

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ◽

10.1016/0168-9002(88)90768-1 ◽

1988 ◽

Vol 272 (3) ◽

pp. 847-854 ◽

Cited By ~ 17

Author(s):

Hong-jian He ◽

Tao-wei Zhang ◽

Ren-cheng Shang ◽

Si-da Xu

Keyword(s):

Monte Carlo ◽

Detector Response ◽

Response Functions ◽

Monte Carlo Approach ◽

Interaction Mechanisms

Download Full-text

The effect of calibration factors and recovery coefficients on 177Lu SPECT activity quantification accuracy: a Monte Carlo study

EJNMMI Physics ◽

10.1186/s40658-021-00365-8 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Keamogetswe Ramonaheng ◽

Johannes A. van Staden ◽

Hanlie du Raan

Keyword(s):

Monte Carlo ◽

Monte Carlo Study ◽

Partial Volume Correction ◽

Detector Response ◽

Physical Size ◽

Partial Volume ◽

Volume Correction ◽

Radioactive Water ◽

Quantification Accuracy ◽

Cylindrical Volume

Abstract Background Different gamma camera calibration factor (CF) geometries have been proposed to convert SPECT data into units of activity concentration. However, no consensus has been reached on a standardised geometry. The CF is dependent on the selected geometry and is further affected by partial volume effects. This study investigated the effect of two CF geometries and their corresponding recovery coefficients (RCs) on the quantification accuracy of 177Lu SPECT images using Monte Carlo simulations. Methods The CF geometries investigated were (i) a radioactive-sphere surrounded by non-radioactive water (sphere-CF) and (ii) a cylindrical phantom uniformly filled with radioactive water (cylinder-CF). Recovery coefficients were obtained using the sphere-CF and cylinder-CF, yielding the sphere-RC and cylinder-RC values, respectively, for partial volume correction (PVC). The quantification accuracy was evaluated using four different-sized spheres (15.6–65.4 ml) and a kidney model with known activity concentrations inside a cylindrical, torso and patient phantom. Images were reconstructed with the 3D OS-EM algorithm incorporating attenuation, scatter and detector-response corrections. Segmentation was performed using the physical size and a small cylindrical volume inside the cylinder for the sphere-CF and cylinder-CF, respectively. Results The sphere quantification error (without PVC) was better for the sphere-CF (≤ − 5.54%) compared to the cylinder-CF (≤ − 20.90%), attributed to the similar geometry of the quantified and CF spheres. Partial volume correction yielded comparable results for the sphere-CF-RC (≤ 3.47%) and cylinder-CF-RC (≤ 3.53%). The accuracy of the kidney quantification was poorer (≤ 22.34%) for the sphere-CF without PVC compared to the cylinder-CF (≤ 2.44%). With PVC, the kidney quantification results improved and compared well for the sphere-CF-RC (≤ 3.50%) and the cylinder-CF-RC (≤ 3.45%). Conclusion The study demonstrated that upon careful selection of CF-RC combinations, comparable quantification errors (≤ 3.53%) were obtained between the sphere-CF-RC and cylinder-CF-RC, when all corrections were applied.

Download Full-text