SPECT and CT misregistration reduction in [99mTc]Tc-MAA SPECT/CT for precision liver radioembolization treatment planning

Purpose Respiration and body movement induce misregistration between static [ 99m Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for 90 Y radioembolization planning. We aim to alleviate the misregistration between [ 99m Tc]Tc-MAA SPECT and C...

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Published inEuropean journal of nuclear medicine and molecular imaging Vol. 50; no. 8; pp. 2319 - 2330
Main Authors Lu, Zhonglin, Chen, Gefei, Jiang, Han, Sun, Jingzhang, Lin, Ko-Han, Mok, Greta S. P.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2023
Springer Nature B.V
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Online AccessGet full text
ISSN1619-7070
1619-7089
DOI10.1007/s00259-023-06149-9

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Abstract Purpose Respiration and body movement induce misregistration between static [ 99m Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for 90 Y radioembolization planning. We aim to alleviate the misregistration between [ 99m Tc]Tc-MAA SPECT and CT using two registration schemes on simulation and clinical data. Methods In the simulation study, 70 XCAT phantoms were modeled. The SIMIND Monte Carlo program and OS-EM algorithm were used for projection generation and reconstruction, respectively. Low-dose CT (LDCT) at end-inspiration was simulated for attenuation correction (AC), lungs and liver segmentation, while contrast-enhanced CT (CECT) was simulated for tumor and perfused liver segmentation. In the clinical study, 16 patient data including [ 99m Tc]Tc-MAA SPECT/LDCT and CECT with observed SPECT and CT mismatch were analyzed. Two liver-based registration schemes were studied: SPECT registered to LDCT/CECT and vice versa. Mean count density (MCD) of different volumes-of-interest (VOIs), normalized mutual information (NMI), LSF, TNR, and maximum injected activity (MIA) based on the partition model before and after registration were compared. Wilcoxon signed-rank test was performed. Results In the simulation study, compared to before registration, registrations significantly reduced estimation errors of MCD of all VOIs, LSF (Scheme 1: − 100.28%, Scheme 2: − 101.59%), and TNR (Scheme 1: − 7.00%, Scheme 2: − 5.67%), as well as MIA (Scheme 1: − 3.22%, Scheme 2: − 2.40%). In the clinical study, Scheme 1 reduced 33.68% LSF and increased 14.75% TNR, while Scheme 2 reduced 38.88% LSF and increased 6.28% TNR compared to before registration. One patient may change from 90 Y radioembolization untreatable to treatable and other patients may change the MIA up to 25% after registration. NMI between SPECT and CT was significantly increased after registrations in both studies. Conclusion Registration between static [ 99m Tc]Tc-MAA SPECT and corresponding CTs is feasible to reduce their spatial mismatch and improve dosimetric estimation. The improvement of LSF is larger than TNR. Our method can potentially improve patient selection and personalized treatment planning for liver radioembolization.
AbstractList PurposeRespiration and body movement induce misregistration between static [99mTc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for 90Y radioembolization planning. We aim to alleviate the misregistration between [99mTc]Tc-MAA SPECT and CT using two registration schemes on simulation and clinical data.MethodsIn the simulation study, 70 XCAT phantoms were modeled. The SIMIND Monte Carlo program and OS-EM algorithm were used for projection generation and reconstruction, respectively. Low-dose CT (LDCT) at end-inspiration was simulated for attenuation correction (AC), lungs and liver segmentation, while contrast-enhanced CT (CECT) was simulated for tumor and perfused liver segmentation. In the clinical study, 16 patient data including [99mTc]Tc-MAA SPECT/LDCT and CECT with observed SPECT and CT mismatch were analyzed. Two liver-based registration schemes were studied: SPECT registered to LDCT/CECT and vice versa. Mean count density (MCD) of different volumes-of-interest (VOIs), normalized mutual information (NMI), LSF, TNR, and maximum injected activity (MIA) based on the partition model before and after registration were compared. Wilcoxon signed-rank test was performed.ResultsIn the simulation study, compared to before registration, registrations significantly reduced estimation errors of MCD of all VOIs, LSF (Scheme 1: − 100.28%, Scheme 2: − 101.59%), and TNR (Scheme 1: − 7.00%, Scheme 2: − 5.67%), as well as MIA (Scheme 1: − 3.22%, Scheme 2: − 2.40%). In the clinical study, Scheme 1 reduced 33.68% LSF and increased 14.75% TNR, while Scheme 2 reduced 38.88% LSF and increased 6.28% TNR compared to before registration. One patient may change from 90Y radioembolization untreatable to treatable and other patients may change the MIA up to 25% after registration. NMI between SPECT and CT was significantly increased after registrations in both studies.ConclusionRegistration between static [99mTc]Tc-MAA SPECT and corresponding CTs is feasible to reduce their spatial mismatch and improve dosimetric estimation. The improvement of LSF is larger than TNR. Our method can potentially improve patient selection and personalized treatment planning for liver radioembolization.
Respiration and body movement induce misregistration between static [ Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for Y radioembolization planning. We aim to alleviate the misregistration between [ Tc]Tc-MAA SPECT and CT using two registration schemes on simulation and clinical data. In the simulation study, 70 XCAT phantoms were modeled. The SIMIND Monte Carlo program and OS-EM algorithm were used for projection generation and reconstruction, respectively. Low-dose CT (LDCT) at end-inspiration was simulated for attenuation correction (AC), lungs and liver segmentation, while contrast-enhanced CT (CECT) was simulated for tumor and perfused liver segmentation. In the clinical study, 16 patient data including [ Tc]Tc-MAA SPECT/LDCT and CECT with observed SPECT and CT mismatch were analyzed. Two liver-based registration schemes were studied: SPECT registered to LDCT/CECT and vice versa. Mean count density (MCD) of different volumes-of-interest (VOIs), normalized mutual information (NMI), LSF, TNR, and maximum injected activity (MIA) based on the partition model before and after registration were compared. Wilcoxon signed-rank test was performed. In the simulation study, compared to before registration, registrations significantly reduced estimation errors of MCD of all VOIs, LSF (Scheme 1: - 100.28%, Scheme 2: - 101.59%), and TNR (Scheme 1: - 7.00%, Scheme 2: - 5.67%), as well as MIA (Scheme 1: - 3.22%, Scheme 2: - 2.40%). In the clinical study, Scheme 1 reduced 33.68% LSF and increased 14.75% TNR, while Scheme 2 reduced 38.88% LSF and increased 6.28% TNR compared to before registration. One patient may change from Y radioembolization untreatable to treatable and other patients may change the MIA up to 25% after registration. NMI between SPECT and CT was significantly increased after registrations in both studies. Registration between static [ Tc]Tc-MAA SPECT and corresponding CTs is feasible to reduce their spatial mismatch and improve dosimetric estimation. The improvement of LSF is larger than TNR. Our method can potentially improve patient selection and personalized treatment planning for liver radioembolization.
Purpose Respiration and body movement induce misregistration between static [ 99m Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver ratio (TNR) errors for 90 Y radioembolization planning. We aim to alleviate the misregistration between [ 99m Tc]Tc-MAA SPECT and CT using two registration schemes on simulation and clinical data. Methods In the simulation study, 70 XCAT phantoms were modeled. The SIMIND Monte Carlo program and OS-EM algorithm were used for projection generation and reconstruction, respectively. Low-dose CT (LDCT) at end-inspiration was simulated for attenuation correction (AC), lungs and liver segmentation, while contrast-enhanced CT (CECT) was simulated for tumor and perfused liver segmentation. In the clinical study, 16 patient data including [ 99m Tc]Tc-MAA SPECT/LDCT and CECT with observed SPECT and CT mismatch were analyzed. Two liver-based registration schemes were studied: SPECT registered to LDCT/CECT and vice versa. Mean count density (MCD) of different volumes-of-interest (VOIs), normalized mutual information (NMI), LSF, TNR, and maximum injected activity (MIA) based on the partition model before and after registration were compared. Wilcoxon signed-rank test was performed. Results In the simulation study, compared to before registration, registrations significantly reduced estimation errors of MCD of all VOIs, LSF (Scheme 1: − 100.28%, Scheme 2: − 101.59%), and TNR (Scheme 1: − 7.00%, Scheme 2: − 5.67%), as well as MIA (Scheme 1: − 3.22%, Scheme 2: − 2.40%). In the clinical study, Scheme 1 reduced 33.68% LSF and increased 14.75% TNR, while Scheme 2 reduced 38.88% LSF and increased 6.28% TNR compared to before registration. One patient may change from 90 Y radioembolization untreatable to treatable and other patients may change the MIA up to 25% after registration. NMI between SPECT and CT was significantly increased after registrations in both studies. Conclusion Registration between static [ 99m Tc]Tc-MAA SPECT and corresponding CTs is feasible to reduce their spatial mismatch and improve dosimetric estimation. The improvement of LSF is larger than TNR. Our method can potentially improve patient selection and personalized treatment planning for liver radioembolization.
Author Jiang, Han
Sun, Jingzhang
Lin, Ko-Han
Mok, Greta S. P.
Chen, Gefei
Lu, Zhonglin
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/36877236$$D View this record in MEDLINE/PubMed
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CitedBy_id crossref_primary_10_3389_fmed_2023_1171118
crossref_primary_10_1038_s41598_023_30824_4
crossref_primary_10_1039_D4TB00923A
crossref_primary_10_2967_jnumed_124_267421
crossref_primary_10_3389_fmed_2023_1246881
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Issue 8
Keywords Respiratory motion
[
Tc]Tc-macroaggregated albumin
Registration
SPECT/CT
[99mTc]Tc-macroaggregated albumin
Language English
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PublicationTitle European journal of nuclear medicine and molecular imaging
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SSID ssj0018289
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Snippet Purpose Respiration and body movement induce misregistration between static [ 99m Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and...
Respiration and body movement induce misregistration between static [ Tc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal liver...
PurposeRespiration and body movement induce misregistration between static [99mTc]Tc-MAA SPECT and CT, causing lung shunting fraction (LSF) and tumor-to-normal...
SourceID proquest
pubmed
crossref
springer
SourceType Aggregation Database
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Enrichment Source
Publisher
StartPage 2319
SubjectTerms Algorithms
Cardiology
Computer simulation
Dosimetry
Embolization, Therapeutic - methods
Errors
Humans
Imaging
Liver
Liver Neoplasms - diagnostic imaging
Liver Neoplasms - radiotherapy
Lungs
Medicine
Medicine & Public Health
Microspheres
Nuclear Medicine
Oncology
Original Article
Orthopedics
Patients
Radiology
Rank tests
Registration
Retrospective Studies
Segmentation
Simulation
Single photon emission computed tomography
Single Photon Emission Computed Tomography Computed Tomography
Technetium Tc 99m Aggregated Albumin
Tomography, Emission-Computed, Single-Photon - methods
Tumors
Yttrium isotopes
Yttrium Radioisotopes - therapeutic use
Title SPECT and CT misregistration reduction in [99mTc]Tc-MAA SPECT/CT for precision liver radioembolization treatment planning
URI https://link.springer.com/article/10.1007/s00259-023-06149-9
https://www.ncbi.nlm.nih.gov/pubmed/36877236
https://www.proquest.com/docview/2825530189
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