Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery
Objectives The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS. Meth...
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| Veröffentlicht in: | European radiology 2022-01, Vol.32 (1), p.497-507 |
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| creator | Lee, Da Hyun Park, Ji Eun Kim, NakYoung Park, Seo Young Kim, Young-Hoon Cho, Young Hyun Kim, Ho Sung |
| description | Objectives
The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS.
Method
Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients.
Results
None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74,
p |
| doi_str_mv | 10.1007/s00330-021-08204-1 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2559433291</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2608265177</sourcerecordid><originalsourceid>FETCH-LOGICAL-c441t-acfd2168d9a8e0c2c169a259b99dad83927c5bad68a3bbc127e3062db92516e43</originalsourceid><addsrcrecordid>eNp9kcuKFTEQhoMoznH0BVxIwI2b1tz6kqUM4wUG3IzrUJ1On8lwOhlT6cV5Gx_V6nNGBRdCqCLJV39R9TP2Wor3Uoj-AwqhtWiEko0YlDCNfMJ20mjVSDGYp2wnrB6a3lpzwV4g3gshrDT9c3ahjW5708od-3m7LrnwOxhjhcohweGIEfl45AvsU6jR8xIwJ0g-8EhvMe35FLFSXiPeBeT1JPFQ8p5IjDnxueSFF5gi1O2agi95U42JjwUoLqEC0qFqmGsoHCmEXMGfGlJlxrXsQzm-ZM9mOGB49Zgv2fdP17dXX5qbb5-_Xn28abwxsjbg50nJbpgsDEF45WVnQbV2tHaCadBW9b4dYeoG0OPopeqDFp2aRqta2QWjL9m7sy7N8WMNWN0S0YfDAVLIKzrVttZorawk9O0_6H1eC22OqI6c6FrZ90SpM7XNjiXM7qHQ_srRSeE2_9zZP0f-uZN_bpN-8yi9jkuY_pT8NowAfQaQvhIt6G_v_8j-AnL-qp8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2608265177</pqid></control><display><type>article</type><title>Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery</title><source>MEDLINE</source><source>SpringerLink Journals</source><creator>Lee, Da Hyun ; Park, Ji Eun ; Kim, NakYoung ; Park, Seo Young ; Kim, Young-Hoon ; Cho, Young Hyun ; Kim, Ho Sung</creator><creatorcontrib>Lee, Da Hyun ; Park, Ji Eun ; Kim, NakYoung ; Park, Seo Young ; Kim, Young-Hoon ; Cho, Young Hyun ; Kim, Ho Sung</creatorcontrib><description>Objectives
The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS.
Method
Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients.
Results
None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74,
p
<.001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR 0.55,
p
<.001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77–0.94) and validation sets (AUC 0.86, 95% CI:0.70–0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11).
Conclusion
Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS.
Key Points
•
Structural MRI habitats helped to differentiate viable tumor from radiation necrosis.
•
Solid low-enhancing habitat was most helpful to find viable tumor.
•
Providing spatial information, the site of progression matched with solid low-enhancing habitat.</description><identifier>ISSN: 0938-7994</identifier><identifier>EISSN: 1432-1084</identifier><identifier>DOI: 10.1007/s00330-021-08204-1</identifier><identifier>PMID: 34357451</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Blood volume ; Brain ; Brain cancer ; Brain Neoplasms - diagnostic imaging ; Brain Neoplasms - radiotherapy ; Brain Neoplasms - surgery ; Brain tumors ; Cerebral blood flow ; Clustering ; Confidence intervals ; Diagnostic Radiology ; Diffusion coefficient ; Habitats ; Humans ; Imaging ; Internal Medicine ; Interventional Radiology ; Magnetic Resonance ; Magnetic Resonance Imaging ; Medical imaging ; Medicine ; Medicine & Public Health ; Metastases ; Metastasis ; Necrosis ; Neuroimaging ; Neuroradiology ; Radiation ; Radiation Injuries ; Radiology ; Radiosurgery ; Spatial data ; Statistical analysis ; Surgery ; Tumors ; Ultrasound</subject><ispartof>European radiology, 2022-01, Vol.32 (1), p.497-507</ispartof><rights>European Society of Radiology 2021</rights><rights>2021. European Society of Radiology.</rights><rights>European Society of Radiology 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-acfd2168d9a8e0c2c169a259b99dad83927c5bad68a3bbc127e3062db92516e43</citedby><cites>FETCH-LOGICAL-c441t-acfd2168d9a8e0c2c169a259b99dad83927c5bad68a3bbc127e3062db92516e43</cites><orcidid>0000-0002-4419-4682</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00330-021-08204-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00330-021-08204-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34357451$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Da Hyun</creatorcontrib><creatorcontrib>Park, Ji Eun</creatorcontrib><creatorcontrib>Kim, NakYoung</creatorcontrib><creatorcontrib>Park, Seo Young</creatorcontrib><creatorcontrib>Kim, Young-Hoon</creatorcontrib><creatorcontrib>Cho, Young Hyun</creatorcontrib><creatorcontrib>Kim, Ho Sung</creatorcontrib><title>Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery</title><title>European radiology</title><addtitle>Eur Radiol</addtitle><addtitle>Eur Radiol</addtitle><description>Objectives
The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS.
Method
Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients.
Results
None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74,
p
<.001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR 0.55,
p
<.001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77–0.94) and validation sets (AUC 0.86, 95% CI:0.70–0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11).
Conclusion
Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS.
Key Points
•
Structural MRI habitats helped to differentiate viable tumor from radiation necrosis.
•
Solid low-enhancing habitat was most helpful to find viable tumor.
•
Providing spatial information, the site of progression matched with solid low-enhancing habitat.</description><subject>Blood volume</subject><subject>Brain</subject><subject>Brain cancer</subject><subject>Brain Neoplasms - diagnostic imaging</subject><subject>Brain Neoplasms - radiotherapy</subject><subject>Brain Neoplasms - surgery</subject><subject>Brain tumors</subject><subject>Cerebral blood flow</subject><subject>Clustering</subject><subject>Confidence intervals</subject><subject>Diagnostic Radiology</subject><subject>Diffusion coefficient</subject><subject>Habitats</subject><subject>Humans</subject><subject>Imaging</subject><subject>Internal Medicine</subject><subject>Interventional Radiology</subject><subject>Magnetic Resonance</subject><subject>Magnetic Resonance Imaging</subject><subject>Medical imaging</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Necrosis</subject><subject>Neuroimaging</subject><subject>Neuroradiology</subject><subject>Radiation</subject><subject>Radiation Injuries</subject><subject>Radiology</subject><subject>Radiosurgery</subject><subject>Spatial data</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Tumors</subject><subject>Ultrasound</subject><issn>0938-7994</issn><issn>1432-1084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kcuKFTEQhoMoznH0BVxIwI2b1tz6kqUM4wUG3IzrUJ1On8lwOhlT6cV5Gx_V6nNGBRdCqCLJV39R9TP2Wor3Uoj-AwqhtWiEko0YlDCNfMJ20mjVSDGYp2wnrB6a3lpzwV4g3gshrDT9c3ahjW5708od-3m7LrnwOxhjhcohweGIEfl45AvsU6jR8xIwJ0g-8EhvMe35FLFSXiPeBeT1JPFQ8p5IjDnxueSFF5gi1O2agi95U42JjwUoLqEC0qFqmGsoHCmEXMGfGlJlxrXsQzm-ZM9mOGB49Zgv2fdP17dXX5qbb5-_Xn28abwxsjbg50nJbpgsDEF45WVnQbV2tHaCadBW9b4dYeoG0OPopeqDFp2aRqta2QWjL9m7sy7N8WMNWN0S0YfDAVLIKzrVttZorawk9O0_6H1eC22OqI6c6FrZ90SpM7XNjiXM7qHQ_srRSeE2_9zZP0f-uZN_bpN-8yi9jkuY_pT8NowAfQaQvhIt6G_v_8j-AnL-qp8</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Lee, Da Hyun</creator><creator>Park, Ji Eun</creator><creator>Kim, NakYoung</creator><creator>Park, Seo Young</creator><creator>Kim, Young-Hoon</creator><creator>Cho, Young Hyun</creator><creator>Kim, Ho Sung</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</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>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4419-4682</orcidid></search><sort><creationdate>20220101</creationdate><title>Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery</title><author>Lee, Da Hyun ; Park, Ji Eun ; Kim, NakYoung ; Park, Seo Young ; Kim, Young-Hoon ; Cho, Young Hyun ; Kim, Ho Sung</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-acfd2168d9a8e0c2c169a259b99dad83927c5bad68a3bbc127e3062db92516e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Blood volume</topic><topic>Brain</topic><topic>Brain cancer</topic><topic>Brain Neoplasms - diagnostic imaging</topic><topic>Brain Neoplasms - radiotherapy</topic><topic>Brain Neoplasms - surgery</topic><topic>Brain tumors</topic><topic>Cerebral blood flow</topic><topic>Clustering</topic><topic>Confidence intervals</topic><topic>Diagnostic Radiology</topic><topic>Diffusion coefficient</topic><topic>Habitats</topic><topic>Humans</topic><topic>Imaging</topic><topic>Internal Medicine</topic><topic>Interventional Radiology</topic><topic>Magnetic Resonance</topic><topic>Magnetic Resonance Imaging</topic><topic>Medical imaging</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metastases</topic><topic>Metastasis</topic><topic>Necrosis</topic><topic>Neuroimaging</topic><topic>Neuroradiology</topic><topic>Radiation</topic><topic>Radiation Injuries</topic><topic>Radiology</topic><topic>Radiosurgery</topic><topic>Spatial data</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Tumors</topic><topic>Ultrasound</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Da Hyun</creatorcontrib><creatorcontrib>Park, Ji Eun</creatorcontrib><creatorcontrib>Kim, NakYoung</creatorcontrib><creatorcontrib>Park, Seo Young</creatorcontrib><creatorcontrib>Kim, Young-Hoon</creatorcontrib><creatorcontrib>Cho, Young Hyun</creatorcontrib><creatorcontrib>Kim, Ho Sung</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</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>MEDLINE - Academic</collection><jtitle>European radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Da Hyun</au><au>Park, Ji Eun</au><au>Kim, NakYoung</au><au>Park, Seo Young</au><au>Kim, Young-Hoon</au><au>Cho, Young Hyun</au><au>Kim, Ho Sung</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery</atitle><jtitle>European radiology</jtitle><stitle>Eur Radiol</stitle><addtitle>Eur Radiol</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>32</volume><issue>1</issue><spage>497</spage><epage>507</epage><pages>497-507</pages><issn>0938-7994</issn><eissn>1432-1084</eissn><abstract>Objectives
The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS.
Method
Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients.
Results
None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74,
p
<.001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR 0.55,
p
<.001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77–0.94) and validation sets (AUC 0.86, 95% CI:0.70–0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11).
Conclusion
Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS.
Key Points
•
Structural MRI habitats helped to differentiate viable tumor from radiation necrosis.
•
Solid low-enhancing habitat was most helpful to find viable tumor.
•
Providing spatial information, the site of progression matched with solid low-enhancing habitat.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>34357451</pmid><doi>10.1007/s00330-021-08204-1</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-4419-4682</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0938-7994 |
| ispartof | European radiology, 2022-01, Vol.32 (1), p.497-507 |
| issn | 0938-7994 1432-1084 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2559433291 |
| source | MEDLINE; SpringerLink Journals |
| subjects | Blood volume Brain Brain cancer Brain Neoplasms - diagnostic imaging Brain Neoplasms - radiotherapy Brain Neoplasms - surgery Brain tumors Cerebral blood flow Clustering Confidence intervals Diagnostic Radiology Diffusion coefficient Habitats Humans Imaging Internal Medicine Interventional Radiology Magnetic Resonance Magnetic Resonance Imaging Medical imaging Medicine Medicine & Public Health Metastases Metastasis Necrosis Neuroimaging Neuroradiology Radiation Radiation Injuries Radiology Radiosurgery Spatial data Statistical analysis Surgery Tumors Ultrasound |
| title | Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery |
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