The physics of radioembolization

Bastiaannet, Remco; Kappadath, S. Cheenu; Kunnen, Britt; Braat, Arthur J. A. T.; Lam, Marnix G. E. H.; Jong, Hugo W. A. M. de

doi:10.1186/s40658-018-0221-z

Cited by 89 publications

(101 citation statements)

References 136 publications

(151 reference statements)

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“…This requires a T/N ratio (partition model) for dosage calculation. The downside of using the T/N ratio is that there is currently no consensus on how to calculate the T/N and how to deal with multiple tumors . Chiesa et al proposed to use a multi‐compartment model using the parenchymal dose as input for dosage calculation.…”

Section: Discussionmentioning

confidence: 99%

“…This pretreatment safety procedure is mainly performed to estimate the lung shunt fraction (LSF) and to detect potential extrahepatic depositions . In addition, a single photon emission computed tomography/computed tomography (SPECT/CT) scan of 99m Tc‐MAA may be used for intrahepatic dosimetry …”

Section: Introductionmentioning

confidence: 99%

“…Another model to calculate prescribed activity is the partition model, which takes the average tumor to nontumor ratio into account . However, this method may still be an oversimplification in the case of multiple tumors with varying uptake . As an alternative to the tumor to nontumor ratio, the tumor dose may be maximized based on the maximal parenchymal dose …”

Section: Introductionmentioning

confidence: 99%

“…1 In addition, a single photon emission computed tomography/computed tomography (SPECT/CT) scan of 99m Tc-MAA may be used for intrahepatic dosimetry. 2 The prescribed activity of 90 Y microspheres can be calculated based on the body surface area (BSA)-method for resin microspheres or the mono-compartment model for glass microspheres. 3,4 Both methods assume a uniform dose distribution within the (targeted) liver volume, and thereby neglect individual patient's dose distribution.…”

Section: Introductionmentioning

confidence: 99%

“…5 However, this method may still be an oversimplification in the case of multiple tumors with varying uptake. 2 As an alternative to the tumor to nontumor ratio, the tumor dose may be maximized based on the maximal parenchymal dose. 6 All image-based dosimetry methods rely on the accuracy of the pretreatment procedure, which is often limited in case of 99m Tc-MAA.…”

Section: Introductionmentioning

confidence: 99%

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Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

et al. 2020

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Purpose Prior to 90Y hepatic radioembolization, a dosage of 99mTc‐macroaggregated albumin (99mTc‐MAA) is administered to simulate the distribution of the 90Y‐loaded microspheres. This pretreatment procedure enables lung shunt estimation, detection of potential extrahepatic depositions, and estimation of the intrahepatic dose distribution. However, the predictive accuracy of the MAA particle distribution is often limited. Ideally, 90Y microspheres would also be used for the pretreatment procedure. Based on previous research, the pretreatment activity should be limited to the estimated safety threshold of 100 MBq, making imaging challenging. The purpose of this study was to evaluate the quality of intra‐ and extrahepatic imaging of 90Y‐based pretreatment positron emission tomography/computed tomography (PET/CT) and quantitative single photon emission computed tomography (SPECT)/CT scans, by means of phantom experiments and a patient study. Methods An anthropomorphic phantom with three extrahepatic depositions was filled with 90Y chloride to simulate a lung shunt fraction (LSF) of 5.3% and a tumor to nontumor ratio (T/N) of 7.9. PET /CT (Siemens Biograph mCT) and Bremsstrahlung SPECT/CT (Siemens Symbia T16) images were acquired at activities ranging from 1999 MBq down to 24 MBq, representing post‐ and pretreatment activities. PET/CT images were reconstructed with the clinical protocol and SPECT/CT images were reconstructed with a quantitative Monte Carlo‐based reconstruction protocol. Estimated LSF, T/N, contrast to noise ratio of all extrahepatic depositions, and liver parenchymal and tumor dose were compared with the phantom ground truth. A clinically reconstructed SPECT/CT of 150 MBq 99mTc represented the current clinical standard. In addition, a 90Y pretreatment scan was simulated for a patient by acquiring posttreatment PET/CT and SPECT/CT data with shortened acquisition times. Results At an activity of 100 MBq 90Y, PET/CT overestimated LSF [+10 percentage point (pp)], underestimated liver parenchymal dose (−3 Gy/GBq), and could not detect the extrahepatic depositions. SPECT/CT more accurately estimated LSF (−0.7 pp), parenchymal dose (−0.3 Gy/GBq) and could detect all three extrahepatic depositions. 99mTc SPECT/CT showed similar accuracy as 90Y SPECT/CT (LSF: +0.2 pp, parenchymal dose: +0.4 Gy/GBq, all extrahepatic depositions visible), although the noise level in the liver compartment was considerably lower for 99mTc SPECT/CT compared to 90Y SPECT/CT. The patient’s SPECT/CT simulating a pretreatment 90Y procedure accurately represented the posttreatment 90Y microsphere distribution. Conclusions Quantitative SPECT/CT of 100 MBq 90Y could accurately estimate LSF, T/N, parenchymal and tumor dose, and visualize extrahepatic depositions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

et al. 2020

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Evaluation of different CT maps for attenuation correction and segmentation in static ^99mTc‐MAA SPECT/CT for ⁹⁰Y radioembolization treatment planning: A simulation study

et al. 2021

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Conventional 99m Tc-macroaggregated albumin ( 99m Tc-MAA) planar scintigraphy overestimates lung shunt fraction (LSF) compared to SPECT/CT. However, the respiratory motion artifact due to the temporal mismatch between static SPECT and helical CT (HCT) may compromise the SPECT quantitation accuracy by incorrect attenuation correction (AC) and volume-of-interest (VOI) segmentation. This study aims to evaluate AC and VOI segmentation effects systematically and to propose a CT map for LSF and tumor-to-normal liver ratio (TNR) estimation in static 99m Tc-MAA SPECT/CT. Methods: The 4D XCAT phantom was used to simulate a phantom population of 120 phantoms, modeling 10 different anatomical variations, nine TNRs (2-13.2), nine tumor sizes (2-6.7 cm diameter), eight tumor locations, three axial motion amplitudes of 1, 1.5, and 2 (cm), and four LSFs of 5%, 10%, 15%, and 20%. An analytical projector for low-energy high-resolution parallel-hole collimator was used to simulate 60 noisy projections over 360°, modeling attenuation and geometric collimator-detector response (GCDR). AC and VOI mismatch effects were investigated independently and together, using cine average CT (CACT), HCT at end-inspiration (HCT-IN), mid-respiration (HCT-MID), and end-expiration (HCT-EX) respectively as attenuation and segmentation maps. SPECT images without motion, AC, and VOI errors were also generated as reference. LSF and TNR errors were measured as compared to the ground truth. Results: HCT-MID has slightly better performance for AC effect compared with other CT maps in LSF and TNR estimation, while HCT-EX and HCT-MID perform better for VOI effect. For a respiratory motion amplitude of 1.5 cm and a LSF of 5%, the LSF errors are 19.56 AE 4.58%,

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A deep‐learning‐based prediction model for the biodistribution of ⁹⁰Y microspheres in liver radioembolization

et al. 2021

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Background Radioembolization with 90Y microspheres is a treatment approach for liver cancer. Currently, employed dosimetric calculations exhibit low accuracy, lacking consideration of individual patient, and tissue characteristics. Purpose The purpose of the present study was to employ deep learning (DL) algorithms to differentiate patterns of pretreatment distribution of 99mTc‐macroaggregated albumin on SPECT/CT and post‐treatment distribution of 90Y microspheres on PET/CT and to accurately predict how the 90Y‐microspheres will be distributed in the liver tissue by radioembolization therapy. Methods Data for 19 patients with liver cancer (10 with hepatocellular carcinoma, 5 with intrahepatic cholangiocarcinoma, 4 with liver metastases) who underwent radioembolization with 90Y microspheres were used for the DL training. We developed a 3D voxel‐based variation of the Pix2Pix model, which is a special type of conditional GANs designed to perform image‐to‐image translation. SPECT and CT scans along with the clinical target volume for each patient were used as inputs, as were their corresponding post‐treatment PET scans. The real and predicted absorbed PET doses for the tumor and the whole liver area were compared. Our model was evaluated using the leave‐one‐out method, and the dose calculations were measured using a tissue‐specific dose voxel kernel. Results The comparison of the real and predicted PET/CT scans showed an average absorbed dose difference of 5.42% ± 19.31% and 0.44% ± 1.64% for the tumor and the liver area, respectively. The average absorbed dose differences were 7.98 ± 31.39 Gy and 0.03 ± 0.25 Gy for the tumor and the non‐tumor liver parenchyma, respectively. Our model had a general tendency to underpredict the dosimetric results; the largest differences were noticed in one case, where the model underestimated the dose to the tumor area by 56.75% or 72.82 Gy. Conclusions The proposed deep‐learning‐based pretreatment planning method for liver radioembolization accurately predicted 90Y microsphere biodistribution. Its combination with a rapid and accurate 3D dosimetry method will render it clinically suitable and could improve patient‐specific pretreatment planning.

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The physics of radioembolization

Cited by 89 publications

References 136 publications

Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Evaluation of different CT maps for attenuation correction and segmentation in static ^99mTc‐MAA SPECT/CT for ⁹⁰Y radioembolization treatment planning: A simulation study

A deep‐learning‐based prediction model for the biodistribution of ⁹⁰Y microspheres in liver radioembolization

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The physics of radioembolization

Cited by 89 publications

References 136 publications

Feasibility of imaging 90Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Feasibility of imaging 90Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Evaluation of different CT maps for attenuation correction and segmentation in static 99mTc‐MAA SPECT/CT for 90Y radioembolization treatment planning: A simulation study

A deep‐learning‐based prediction model for the biodistribution of 90Y microspheres in liver radioembolization

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Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Feasibility of imaging ⁹⁰Y microspheres at diagnostic activity levels for hepatic radioembolization treatment planning

Evaluation of different CT maps for attenuation correction and segmentation in static ^99mTc‐MAA SPECT/CT for ⁹⁰Y radioembolization treatment planning: A simulation study

A deep‐learning‐based prediction model for the biodistribution of ⁹⁰Y microspheres in liver radioembolization