Changing Threshold-Based Segmentation Has No Relevant Impact on Semi-Quantification in the Context of Structured Reporting for PSMA-PET/CT
Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA...
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| Veröffentlicht in: | Cancers 2022-01, Vol.14 (2), p.270 |
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| creator | Mihatsch, Patrick W Beissert, Matthias Pomper, Martin G Bley, Thorsten A Seitz, Anna K Kübler, Hubert Buck, Andreas K Rowe, Steven P Serfling, Sebastian E Hartrampf, Philipp E Werner, Rudolf A |
| description | Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with
F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV
, SUV
, SUV
) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (
≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV
and SUV
compared to the entire PSMA-RADS-4 or -5 cohort (
< 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (
< 0.0001), but not to the PSMA-RADS-4 cohort (SUV
,
= 0.07; SUV
,
= 0.08). SUV
(
= 0.30) and TL-PSMA (
= 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (
= 0.0066), which was driven by lymph nodes (
= 0.0239), but not bone lesions (
= 0.15). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in
F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV
and TL-PSMA in contrast to PSMA-TV. |
| doi_str_mv | 10.3390/cancers14020270 |
| format | Article |
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F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV
, SUV
, SUV
) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (
≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV
and SUV
compared to the entire PSMA-RADS-4 or -5 cohort (
< 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (
< 0.0001), but not to the PSMA-RADS-4 cohort (SUV
,
= 0.07; SUV
,
= 0.08). SUV
(
= 0.30) and TL-PSMA (
= 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (
= 0.0066), which was driven by lymph nodes (
= 0.0239), but not bone lesions (
= 0.15). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in
F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV
and TL-PSMA in contrast to PSMA-TV.</description><identifier>ISSN: 2072-6694</identifier><identifier>EISSN: 2072-6694</identifier><identifier>DOI: 10.3390/cancers14020270</identifier><identifier>PMID: 35053434</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Bone lesions ; Computed tomography ; Iodine ; Lymph nodes ; Metastases ; Metastasis ; Patients ; Positron emission tomography ; Prostate ; Prostate cancer ; Segmentation ; Software ; Tomography ; Tumors</subject><ispartof>Cancers, 2022-01, Vol.14 (2), p.270</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c421t-4ef556ca98a9fe12e0e94dfa97de849ff1f505a865b1e7424b4812bd02840653</citedby><cites>FETCH-LOGICAL-c421t-4ef556ca98a9fe12e0e94dfa97de849ff1f505a865b1e7424b4812bd02840653</cites><orcidid>0000-0001-5622-9849 ; 0000-0003-2897-4694</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773894/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773894/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35053434$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mihatsch, Patrick W</creatorcontrib><creatorcontrib>Beissert, Matthias</creatorcontrib><creatorcontrib>Pomper, Martin G</creatorcontrib><creatorcontrib>Bley, Thorsten A</creatorcontrib><creatorcontrib>Seitz, Anna K</creatorcontrib><creatorcontrib>Kübler, Hubert</creatorcontrib><creatorcontrib>Buck, Andreas K</creatorcontrib><creatorcontrib>Rowe, Steven P</creatorcontrib><creatorcontrib>Serfling, Sebastian E</creatorcontrib><creatorcontrib>Hartrampf, Philipp E</creatorcontrib><creatorcontrib>Werner, Rudolf A</creatorcontrib><title>Changing Threshold-Based Segmentation Has No Relevant Impact on Semi-Quantification in the Context of Structured Reporting for PSMA-PET/CT</title><title>Cancers</title><addtitle>Cancers (Basel)</addtitle><description>Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with
F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV
, SUV
, SUV
) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (
≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV
and SUV
compared to the entire PSMA-RADS-4 or -5 cohort (
< 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (
< 0.0001), but not to the PSMA-RADS-4 cohort (SUV
,
= 0.07; SUV
,
= 0.08). SUV
(
= 0.30) and TL-PSMA (
= 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (
= 0.0066), which was driven by lymph nodes (
= 0.0239), but not bone lesions (
= 0.15). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in
F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV
and TL-PSMA in contrast to PSMA-TV.</description><subject>Bone lesions</subject><subject>Computed tomography</subject><subject>Iodine</subject><subject>Lymph nodes</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Patients</subject><subject>Positron emission tomography</subject><subject>Prostate</subject><subject>Prostate cancer</subject><subject>Segmentation</subject><subject>Software</subject><subject>Tomography</subject><subject>Tumors</subject><issn>2072-6694</issn><issn>2072-6694</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkUtv1DAUhSMEolXpmh2yxIZNGL_y8AapRIVWKlA62Vse53riKrEH26nKX-BX49GUqtSba_l-91wfnaJ4S_BHxgReaeU0hEg4ppg2-EVxTHFDy7oW_OWT-1FxGuMtzocx0tTN6-KIVbhinPHj4k83Kre1bov6MUAc_TSUn1WEAa1hO4NLKlnv0IWK6LtHNzDBnXIJXc47pRPKnTXMtvy55EdrrD7Q1qE0Auq8S3CfKYPWKSw6LSHr3sDOh7TfaHxA1-tvZ-X1eb_q-jfFK6OmCKcP9aTov5z33UV59ePrZXd2VWpOSSo5mKqqtRKtEgYIBQyCD0aJZoCWC2OIye5UW1cbAg2nfMNbQjcDpi3HdcVOik8H2d2ymWHQ2WNQk9wFO6vwW3pl5f8dZ0e59XeybRrWCp4FPjwIBP9rgZjkbKOGaVIO_BIlrSmlLeWcZPT9M_TWL8Fld3uK0KYStM3U6kDp4GMMYB4_Q7DcJy2fJZ0n3j318Mj_y5X9BYm6pow</recordid><startdate>20220106</startdate><enddate>20220106</enddate><creator>Mihatsch, Patrick W</creator><creator>Beissert, Matthias</creator><creator>Pomper, Martin G</creator><creator>Bley, Thorsten A</creator><creator>Seitz, Anna K</creator><creator>Kübler, Hubert</creator><creator>Buck, Andreas K</creator><creator>Rowe, Steven P</creator><creator>Serfling, Sebastian E</creator><creator>Hartrampf, Philipp E</creator><creator>Werner, Rudolf A</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7TO</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5622-9849</orcidid><orcidid>https://orcid.org/0000-0003-2897-4694</orcidid></search><sort><creationdate>20220106</creationdate><title>Changing Threshold-Based Segmentation Has No Relevant Impact on Semi-Quantification in the Context of Structured Reporting for PSMA-PET/CT</title><author>Mihatsch, Patrick W ; Beissert, Matthias ; Pomper, Martin G ; Bley, Thorsten A ; Seitz, Anna K ; Kübler, Hubert ; Buck, Andreas K ; Rowe, Steven P ; Serfling, Sebastian E ; Hartrampf, Philipp E ; Werner, Rudolf A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c421t-4ef556ca98a9fe12e0e94dfa97de849ff1f505a865b1e7424b4812bd02840653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bone lesions</topic><topic>Computed tomography</topic><topic>Iodine</topic><topic>Lymph nodes</topic><topic>Metastases</topic><topic>Metastasis</topic><topic>Patients</topic><topic>Positron emission tomography</topic><topic>Prostate</topic><topic>Prostate cancer</topic><topic>Segmentation</topic><topic>Software</topic><topic>Tomography</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mihatsch, Patrick W</creatorcontrib><creatorcontrib>Beissert, Matthias</creatorcontrib><creatorcontrib>Pomper, Martin G</creatorcontrib><creatorcontrib>Bley, Thorsten A</creatorcontrib><creatorcontrib>Seitz, Anna K</creatorcontrib><creatorcontrib>Kübler, Hubert</creatorcontrib><creatorcontrib>Buck, Andreas K</creatorcontrib><creatorcontrib>Rowe, Steven P</creatorcontrib><creatorcontrib>Serfling, Sebastian E</creatorcontrib><creatorcontrib>Hartrampf, Philipp E</creatorcontrib><creatorcontrib>Werner, Rudolf A</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mihatsch, Patrick W</au><au>Beissert, Matthias</au><au>Pomper, Martin G</au><au>Bley, Thorsten A</au><au>Seitz, Anna K</au><au>Kübler, Hubert</au><au>Buck, Andreas K</au><au>Rowe, Steven P</au><au>Serfling, Sebastian E</au><au>Hartrampf, Philipp E</au><au>Werner, Rudolf A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Changing Threshold-Based Segmentation Has No Relevant Impact on Semi-Quantification in the Context of Structured Reporting for PSMA-PET/CT</atitle><jtitle>Cancers</jtitle><addtitle>Cancers (Basel)</addtitle><date>2022-01-06</date><risdate>2022</risdate><volume>14</volume><issue>2</issue><spage>270</spage><pages>270-</pages><issn>2072-6694</issn><eissn>2072-6694</eissn><abstract>Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with
F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV
, SUV
, SUV
) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (
≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV
and SUV
compared to the entire PSMA-RADS-4 or -5 cohort (
< 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (
< 0.0001), but not to the PSMA-RADS-4 cohort (SUV
,
= 0.07; SUV
,
= 0.08). SUV
(
= 0.30) and TL-PSMA (
= 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (
= 0.0066), which was driven by lymph nodes (
= 0.0239), but not bone lesions (
= 0.15). SUV
was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in
F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV
and TL-PSMA in contrast to PSMA-TV.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35053434</pmid><doi>10.3390/cancers14020270</doi><orcidid>https://orcid.org/0000-0001-5622-9849</orcidid><orcidid>https://orcid.org/0000-0003-2897-4694</orcidid><oa>free_for_read</oa></addata></record> |
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| source | PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Bone lesions Computed tomography Iodine Lymph nodes Metastases Metastasis Patients Positron emission tomography Prostate Prostate cancer Segmentation Software Tomography Tumors |
| title | Changing Threshold-Based Segmentation Has No Relevant Impact on Semi-Quantification in the Context of Structured Reporting for PSMA-PET/CT |
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