A comparison of methods for adapting 177Lu dose-voxel-kernels to tissue inhomogeneities

Abstract

In radionuclide therapies, dosimetry is used for determining patient-individual dose burden. Standard approaches provide whole organ doses only. For assessing dose heterogeneity inside organs, voxel-wise dosimetry based on 3D SPECT/CT imaging could be applied. Often, this is achieved by convolving voxel-wise time-activity-curves with appropriate dose-voxel-kernels (DVK). The DVKs are meant to model dose deposition, and can be more accurate if modelled for the specific tissue type under consideration. In literature, DVKs are often not adapted to these inhomogeneities, or simple approximation schemes are applied. For 26 patients, which had previously undergone a -PSMA or -DOTATOC therapy, decay maps, mass-density maps as well as tissue-type maps were derived from SPECT/CT acquisitions. These were used for a voxel-based dosimetry based on convolution with DVKs (each of size ) obtained by four different DVK methods proposed in literature. The simplest only considers a spatially constant soft-tissue DVK (herein named ‘constant’), while others either take into account only the local density of the center voxel of the DVK (herein named ‘center-voxel’) or scale each voxel linearly according to the proper mass density deduced from the CT image (herein named ‘density’) or considered both the local mass density as well as the direct path between the center voxel and any voxel in its surrounding (herein named ‘percentage’). Deviations between resulting dose values and those from full Monte-Carlo simulations (MC simulations) were compared for selected organs and tissue-types. For each DVK method, inter-patient variability was considerable showing both under- and over-estimation of energy dose compared to the MC result for all tissue densities higher than soft tissue. In kidneys and spleen, ‘constant’ and ‘density’-scaled DVKs achieved estimated doses with smallest deviations to the full MC gold standard (∼ underestimation). For low and high density tissue types such as lung and adipose or bone tissue, alternative DVK methods like ‘center-voxel’- and ‘percentage’- scaled achieved superior results, respectively. Concerning computational load, dose estimation with the DVK method ‘constant’ needs about 1.1 s per patient, center-voxel scaling amounts to 1.2 s, density scaling needs 1.4 s while percentage scaling consumes 860.3 s per patient. In this study encompassing a large patient cohort and four different DVK estimation methods, no single DVK-adaption method was consistently better than any other in case of soft tissue kernels. Hence in such cases the simplest DVK method, labeled ‘constant’, suffices. In case of tumors, often located in tissues of low (lung) or high (bone) density, more sophisticated DVK methods excel. The high inter-patient variability indicates that for evaluating new algorithms, a sufficiently large patient cohort needs to be involved.

DblurDoseNet: A deep residual learning network for voxel radionuclide dosimetry compensating for single‐photon emission computerized tomography imaging resolution

“…Here, after convolution, each voxel was scaled by 1.04 ($${\rm{g}}/{\rm{c}}{{\rm{m}}^3}$$) and divided by the local voxel density value ($${\rm{g}}/{\rm{c}}{{\rm{m}}^3}$$) derived from the CT scan. Because our goal was to generate a reasonably accurate and quick initial estimate for the residual learning process, we did not pursue other more sophisticated approaches 28,29 that account for tissue heterogeneities. To address the very high dose‐rate estimate in extra low‐density regions, for example, air gaps, we set the dose‐rate in regions where the density is less than 0.1 $${\rm{g}}/{\rm{c}}{{\rm{m}}^3}$$ to 0.…”

ICRU REPORT 96, Dosimetry-Guided Radiopharmaceutical Therapy

“…In a study by Minguez et al (2016), soft tissue VSVs were rescaled by simple ratios of tissue densities ( / ) ρ ρ soft tissue t hyroid in their study of 131 I-NaI remnant dosimetry in the treatment of differential thyroid cancer. Density scaling approaches were also applied by Götz et al (2019) in applications to 177 Lu VSVs (termed dose voxel kernels in this study) within tissue heterogeneities. In the study by Moghadam et al (2016), VSVs were computed by MC radiation transport simulation for 90 Y, 177 Lu, and 32 P in 9 different tissues-bone, lung, adipose, breast, heart, intestine, kidney, liver, and spleen-along with S-coefficient scaling factors to account for dose reductions and/or enhancement at tissue interfaces.…”

Averaging of absorbed doses: How matter matters

“…The dosimetry methods used range from simpler whole‐organ‐based methods to more complex voxel‐wise calculations. Several studies also focus on method development or method comparison 8–13 …”

“…Several studies also focus on method development or method comparison. [8][9][10][11][12][13] Recently, three major guidance documents on patientspecific dosimetry in radionuclide therapy have been issued. [14][15][16] However, there is yet no formal codeof -practice for how dosimetry in radionuclide therapy should be performed or methods validated.…”

“…24 Voxel-based dosimetry can be accomplished from a series of SPECT/CT images, with the patient specific source-distribution derived from the SPECT image, and the radiation transport calculated in the CT-derived geometry. 25,26 Different voxel-based calculation algorithms are available, 9,27 with direct Monte Carlo simulations typically considered to be the most accurate but suffering from a relatively high complexity and computational burden.…”