The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology
Purpose: In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological18F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth...
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description | Purpose:
In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological18F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders.
Methods:
Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of18F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of 18F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax–abdomen phantom and imaged with a PET–CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites’ PET threshold segmentations in terms of Dice index and volume error.
Results:
The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R
2 = 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the 18F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable bo |
doi_str_mv | 10.1118/1.4736812 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmed_primary_22957603</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1039038872</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4212-6dfd2ac2c0cb2287ac853638910cc1574540ea57302ee8a20364baf749f2849e3</originalsourceid><addsrcrecordid>eNp9kM1u1DAURi1ERYfCghdAltgAUlr72knsZVWVH6moXQxry-Nczxhl4mnsFA1Pj4cMqJuysuV7vmPdj5A3nJ1zztUFP5etaBSHZ2QB5VpJYPo5WTCmZQWS1afkZUo_GGONqNkLcgqg67ZhYkE2yw3SKSGNnv7C2IeMieZI1zjgaDPSu-sl3W3skOM2UR9HmkvgwfahsznE4ZC7n8o4-ODml5QPwXUoolDmg4t9XO9fkRNv-4Svj-cZ-f7penn1pbq5_fz16vKmchI4VE3nO7AOHHMrANVap2rRCKU5c47XrawlQ1u3ggGissBEI1fWt1J7UFKjOCPvZm9MOZjkykJu4-IwoMsGSi9K67ZQ72dqN8b7CVM225Ac9r0dME7JcCY0E0q1UNAPM-rGmNKI3uzGsLXjvkDmUL_h5lh_Yd8etdNqi90_8m_fBahm4Gfocf-0yXy7Owo_zvxhkT_1_vf3J-GHOD6S7zovfgM0-6h0</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1039038872</pqid></control><display><type>article</type><title>The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology</title><source>MEDLINE</source><source>Access via Wiley Online Library</source><source>Alma/SFX Local Collection</source><creator>Zito, Felicia ; De Bernardi, Elisabetta ; Soffientini, Chiara ; Canzi, Cristina ; Casati, Rosangela ; Gerundini, Paolo ; Baselli, Giuseppe</creator><creatorcontrib>Zito, Felicia ; De Bernardi, Elisabetta ; Soffientini, Chiara ; Canzi, Cristina ; Casati, Rosangela ; Gerundini, Paolo ; Baselli, Giuseppe</creatorcontrib><description>Purpose:
In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological18F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders.
Methods:
Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of18F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of 18F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax–abdomen phantom and imaged with a PET–CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites’ PET threshold segmentations in terms of Dice index and volume error.
Results:
The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R
2 = 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the 18F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable borders, as demonstrated by a mean absolute volume error of 2.8% with respect to the PET threshold segmentation corresponding to the maximum Dice.
Conclusions:
The proposed methodology allowed obtaining an experimental phantom data set that can be used as a feasible tool to test and validate quantification and segmentation algorithms for PET in oncology. The phantom is currently under consideration for being included in a benchmark designed by AAPM TG211, which will be available to the community to evaluate PET automatic segmentation methods.</description><identifier>ISSN: 0094-2405</identifier><identifier>EISSN: 2473-4209</identifier><identifier>DOI: 10.1118/1.4736812</identifier><identifier>PMID: 22957603</identifier><identifier>CODEN: MPHYA6</identifier><language>eng</language><publisher>United States: American Association of Physicists in Medicine</publisher><subject>18F‐FDG PET ; 60 APPLIED LIFE SCIENCES ; ABDOMEN ; Adsorption ; ALGORITHMS ; AQUEOUS SOLUTIONS ; BENCHMARKS ; cancer ; CAT SCANNING ; CHEST ; CLINOPTILOLITE ; Computed tomography ; Computerised tomographs ; computerised tomography ; Digital computing or data processing equipment or methods, specially adapted for specific applications ; FLUORINE 18 ; FLUORODEOXYGLUCOSE ; Fluorodeoxyglucose F18 ; Humans ; Image data processing or generation, in general ; IMAGE PROCESSING ; Image Processing, Computer-Assisted ; image reconstruction ; image segmentation ; Image sensors ; Liver ; Medical image contrast ; medical image processing ; Medical image reconstruction ; Medical image segmentation ; Medical imaging ; Multimodal Imaging ; NEOPLASMS ; Neoplasms - diagnostic imaging ; ORGANIC COMPOUNDS ; PET experimental phantom ; PHANTOMS ; Phantoms, Imaging ; Porosity ; POSITRON COMPUTED TOMOGRAPHY ; positron emission tomography ; Positron emission tomography (PET) ; Positron-Emission Tomography - instrumentation ; RADIOLOGY AND NUCLEAR MEDICINE ; Segmentation ; SIMULATION ; Tomography, X-Ray Computed ; tumours ; VALIDATION ; validation of quantification/segmentation algorithms ; X‐ray imaging ; Zeolites ; zeolites for PET lesion simulation</subject><ispartof>Medical physics (Lancaster), 2012-09, Vol.39 (9), p.5353-5361</ispartof><rights>American Association of Physicists in Medicine</rights><rights>2012 American Association of Physicists in Medicine</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4212-6dfd2ac2c0cb2287ac853638910cc1574540ea57302ee8a20364baf749f2849e3</citedby><cites>FETCH-LOGICAL-c4212-6dfd2ac2c0cb2287ac853638910cc1574540ea57302ee8a20364baf749f2849e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1118%2F1.4736812$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1118%2F1.4736812$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22957603$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/22098997$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Zito, Felicia</creatorcontrib><creatorcontrib>De Bernardi, Elisabetta</creatorcontrib><creatorcontrib>Soffientini, Chiara</creatorcontrib><creatorcontrib>Canzi, Cristina</creatorcontrib><creatorcontrib>Casati, Rosangela</creatorcontrib><creatorcontrib>Gerundini, Paolo</creatorcontrib><creatorcontrib>Baselli, Giuseppe</creatorcontrib><title>The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology</title><title>Medical physics (Lancaster)</title><addtitle>Med Phys</addtitle><description>Purpose:
In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological18F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders.
Methods:
Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of18F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of 18F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax–abdomen phantom and imaged with a PET–CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites’ PET threshold segmentations in terms of Dice index and volume error.
Results:
The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R
2 = 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the 18F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable borders, as demonstrated by a mean absolute volume error of 2.8% with respect to the PET threshold segmentation corresponding to the maximum Dice.
Conclusions:
The proposed methodology allowed obtaining an experimental phantom data set that can be used as a feasible tool to test and validate quantification and segmentation algorithms for PET in oncology. The phantom is currently under consideration for being included in a benchmark designed by AAPM TG211, which will be available to the community to evaluate PET automatic segmentation methods.</description><subject>18F‐FDG PET</subject><subject>60 APPLIED LIFE SCIENCES</subject><subject>ABDOMEN</subject><subject>Adsorption</subject><subject>ALGORITHMS</subject><subject>AQUEOUS SOLUTIONS</subject><subject>BENCHMARKS</subject><subject>cancer</subject><subject>CAT SCANNING</subject><subject>CHEST</subject><subject>CLINOPTILOLITE</subject><subject>Computed tomography</subject><subject>Computerised tomographs</subject><subject>computerised tomography</subject><subject>Digital computing or data processing equipment or methods, specially adapted for specific applications</subject><subject>FLUORINE 18</subject><subject>FLUORODEOXYGLUCOSE</subject><subject>Fluorodeoxyglucose F18</subject><subject>Humans</subject><subject>Image data processing or generation, in general</subject><subject>IMAGE PROCESSING</subject><subject>Image Processing, Computer-Assisted</subject><subject>image reconstruction</subject><subject>image segmentation</subject><subject>Image sensors</subject><subject>Liver</subject><subject>Medical image contrast</subject><subject>medical image processing</subject><subject>Medical image reconstruction</subject><subject>Medical image segmentation</subject><subject>Medical imaging</subject><subject>Multimodal Imaging</subject><subject>NEOPLASMS</subject><subject>Neoplasms - diagnostic imaging</subject><subject>ORGANIC COMPOUNDS</subject><subject>PET experimental phantom</subject><subject>PHANTOMS</subject><subject>Phantoms, Imaging</subject><subject>Porosity</subject><subject>POSITRON COMPUTED TOMOGRAPHY</subject><subject>positron emission tomography</subject><subject>Positron emission tomography (PET)</subject><subject>Positron-Emission Tomography - instrumentation</subject><subject>RADIOLOGY AND NUCLEAR MEDICINE</subject><subject>Segmentation</subject><subject>SIMULATION</subject><subject>Tomography, X-Ray Computed</subject><subject>tumours</subject><subject>VALIDATION</subject><subject>validation of quantification/segmentation algorithms</subject><subject>X‐ray imaging</subject><subject>Zeolites</subject><subject>zeolites for PET lesion simulation</subject><issn>0094-2405</issn><issn>2473-4209</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1u1DAURi1ERYfCghdAltgAUlr72knsZVWVH6moXQxry-Nczxhl4mnsFA1Pj4cMqJuysuV7vmPdj5A3nJ1zztUFP5etaBSHZ2QB5VpJYPo5WTCmZQWS1afkZUo_GGONqNkLcgqg67ZhYkE2yw3SKSGNnv7C2IeMieZI1zjgaDPSu-sl3W3skOM2UR9HmkvgwfahsznE4ZC7n8o4-ODml5QPwXUoolDmg4t9XO9fkRNv-4Svj-cZ-f7penn1pbq5_fz16vKmchI4VE3nO7AOHHMrANVap2rRCKU5c47XrawlQ1u3ggGissBEI1fWt1J7UFKjOCPvZm9MOZjkykJu4-IwoMsGSi9K67ZQ72dqN8b7CVM225Ac9r0dME7JcCY0E0q1UNAPM-rGmNKI3uzGsLXjvkDmUL_h5lh_Yd8etdNqi90_8m_fBahm4Gfocf-0yXy7Owo_zvxhkT_1_vf3J-GHOD6S7zovfgM0-6h0</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Zito, Felicia</creator><creator>De Bernardi, Elisabetta</creator><creator>Soffientini, Chiara</creator><creator>Canzi, Cristina</creator><creator>Casati, Rosangela</creator><creator>Gerundini, Paolo</creator><creator>Baselli, Giuseppe</creator><general>American Association of Physicists in Medicine</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>OTOTI</scope></search><sort><creationdate>201209</creationdate><title>The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology</title><author>Zito, Felicia ; De Bernardi, Elisabetta ; Soffientini, Chiara ; Canzi, Cristina ; Casati, Rosangela ; Gerundini, Paolo ; Baselli, Giuseppe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4212-6dfd2ac2c0cb2287ac853638910cc1574540ea57302ee8a20364baf749f2849e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>18F‐FDG PET</topic><topic>60 APPLIED LIFE SCIENCES</topic><topic>ABDOMEN</topic><topic>Adsorption</topic><topic>ALGORITHMS</topic><topic>AQUEOUS SOLUTIONS</topic><topic>BENCHMARKS</topic><topic>cancer</topic><topic>CAT SCANNING</topic><topic>CHEST</topic><topic>CLINOPTILOLITE</topic><topic>Computed tomography</topic><topic>Computerised tomographs</topic><topic>computerised tomography</topic><topic>Digital computing or data processing equipment or methods, specially adapted for specific applications</topic><topic>FLUORINE 18</topic><topic>FLUORODEOXYGLUCOSE</topic><topic>Fluorodeoxyglucose F18</topic><topic>Humans</topic><topic>Image data processing or generation, in general</topic><topic>IMAGE PROCESSING</topic><topic>Image Processing, Computer-Assisted</topic><topic>image reconstruction</topic><topic>image segmentation</topic><topic>Image sensors</topic><topic>Liver</topic><topic>Medical image contrast</topic><topic>medical image processing</topic><topic>Medical image reconstruction</topic><topic>Medical image segmentation</topic><topic>Medical imaging</topic><topic>Multimodal Imaging</topic><topic>NEOPLASMS</topic><topic>Neoplasms - diagnostic imaging</topic><topic>ORGANIC COMPOUNDS</topic><topic>PET experimental phantom</topic><topic>PHANTOMS</topic><topic>Phantoms, Imaging</topic><topic>Porosity</topic><topic>POSITRON COMPUTED TOMOGRAPHY</topic><topic>positron emission tomography</topic><topic>Positron emission tomography (PET)</topic><topic>Positron-Emission Tomography - instrumentation</topic><topic>RADIOLOGY AND NUCLEAR MEDICINE</topic><topic>Segmentation</topic><topic>SIMULATION</topic><topic>Tomography, X-Ray Computed</topic><topic>tumours</topic><topic>VALIDATION</topic><topic>validation of quantification/segmentation algorithms</topic><topic>X‐ray imaging</topic><topic>Zeolites</topic><topic>zeolites for PET lesion simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zito, Felicia</creatorcontrib><creatorcontrib>De Bernardi, Elisabetta</creatorcontrib><creatorcontrib>Soffientini, Chiara</creatorcontrib><creatorcontrib>Canzi, Cristina</creatorcontrib><creatorcontrib>Casati, Rosangela</creatorcontrib><creatorcontrib>Gerundini, Paolo</creatorcontrib><creatorcontrib>Baselli, Giuseppe</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>OSTI.GOV</collection><jtitle>Medical physics (Lancaster)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zito, Felicia</au><au>De Bernardi, Elisabetta</au><au>Soffientini, Chiara</au><au>Canzi, Cristina</au><au>Casati, Rosangela</au><au>Gerundini, Paolo</au><au>Baselli, Giuseppe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology</atitle><jtitle>Medical physics (Lancaster)</jtitle><addtitle>Med Phys</addtitle><date>2012-09</date><risdate>2012</risdate><volume>39</volume><issue>9</issue><spage>5353</spage><epage>5361</epage><pages>5353-5361</pages><issn>0094-2405</issn><eissn>2473-4209</eissn><coden>MPHYA6</coden><abstract>Purpose:
In recent years, segmentation algorithms and activity quantification methods have been proposed for oncological18F-fluorodeoxyglucose (FDG) PET. A full assessment of these algorithms, necessary for a clinical transfer, requires a validation on data sets provided with a reliable ground truth as to the imaged activity distribution, which must be as realistic as possible. The aim of this work is to propose a strategy to simulate lesions of uniform uptake and irregular shape in an anthropomorphic phantom, with the possibility to easily obtain a ground truth as to lesion activity and borders.
Methods:
Lesions were simulated with samples of clinoptilolite, a family of natural zeolites of irregular shape, able to absorb aqueous solutions of18F-FDG, available in a wide size range, and nontoxic. Zeolites were soaked in solutions of 18F-FDG for increasing times up to 120 min and their absorptive properties were characterized as function of soaking duration, solution concentration, and zeolite dry weight. Saturated zeolites were wrapped in Parafilm, positioned inside an Alderson thorax–abdomen phantom and imaged with a PET–CT scanner. The ground truth for the activity distribution of each zeolite was obtained by segmenting high-resolution finely aligned CT images, on the basis of independently obtained volume measurements. The fine alignment between CT and PET was validated by comparing the CT-derived ground truth to a set of zeolites’ PET threshold segmentations in terms of Dice index and volume error.
Results:
The soaking time necessary to achieve saturation increases with zeolite dry weight, with a maximum of about 90 min for the largest sample. At saturation, a linear dependence of the uptake normalized to the solution concentration on zeolite dry weight (R
2 = 0.988), as well as a uniform distribution of the activity over the entire zeolite volume from PET imaging were demonstrated. These findings indicate that the 18F-FDG solution is able to saturate the zeolite pores and that the concentration does not influence the distribution uniformity of both solution and solute, at least at the trace concentrations used for zeolite activation. An additional proof of uniformity of zeolite saturation was obtained observing a correspondence between uptake and adsorbed volume of solution, corresponding to about 27.8% of zeolite volume. As to the ground truth for zeolites positioned inside the phantom, the segmentation of finely aligned CT images provided reliable borders, as demonstrated by a mean absolute volume error of 2.8% with respect to the PET threshold segmentation corresponding to the maximum Dice.
Conclusions:
The proposed methodology allowed obtaining an experimental phantom data set that can be used as a feasible tool to test and validate quantification and segmentation algorithms for PET in oncology. The phantom is currently under consideration for being included in a benchmark designed by AAPM TG211, which will be available to the community to evaluate PET automatic segmentation methods.</abstract><cop>United States</cop><pub>American Association of Physicists in Medicine</pub><pmid>22957603</pmid><doi>10.1118/1.4736812</doi><tpages>9</tpages></addata></record> |
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subjects | 18F‐FDG PET 60 APPLIED LIFE SCIENCES ABDOMEN Adsorption ALGORITHMS AQUEOUS SOLUTIONS BENCHMARKS cancer CAT SCANNING CHEST CLINOPTILOLITE Computed tomography Computerised tomographs computerised tomography Digital computing or data processing equipment or methods, specially adapted for specific applications FLUORINE 18 FLUORODEOXYGLUCOSE Fluorodeoxyglucose F18 Humans Image data processing or generation, in general IMAGE PROCESSING Image Processing, Computer-Assisted image reconstruction image segmentation Image sensors Liver Medical image contrast medical image processing Medical image reconstruction Medical image segmentation Medical imaging Multimodal Imaging NEOPLASMS Neoplasms - diagnostic imaging ORGANIC COMPOUNDS PET experimental phantom PHANTOMS Phantoms, Imaging Porosity POSITRON COMPUTED TOMOGRAPHY positron emission tomography Positron emission tomography (PET) Positron-Emission Tomography - instrumentation RADIOLOGY AND NUCLEAR MEDICINE Segmentation SIMULATION Tomography, X-Ray Computed tumours VALIDATION validation of quantification/segmentation algorithms X‐ray imaging Zeolites zeolites for PET lesion simulation |
title | The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology |
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