Dosimetric Variability Across a Library of Computational Tumor Phantoms Article Swipe
Lukas M. Carter
,
Simone Krebs
,
Harry Marquis
,
Juan Camilo Ocampo Ramos
,
E Olguin
,
Emilia O. Mason
,
Wesley E. Bolch
,
Pat Zanzonico
,
Adam Kesner
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.2967/jnumed.122.264916
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.2967/jnumed.122.264916
In radiopharmaceutical therapy, dosimetry-based treatment planning and response evaluation require accurate estimates of tumor-absorbed dose. Tumor dose estimates are routinely derived using simplistic spherical models, despite the well-established influence of tumor geometry on the dosimetry. Moreover, the degree of disease invasiveness correlates with departure from ideal geometry; malignant lesions often possess lobular, spiculated, or otherwise irregular margins in contrast to the commonly regular or smooth contours characteristic of benign lesions. To assess the effects of tumor shape, size, and margin contour on absorbed dose, an array of tumor geometries was modeled using computer-aided design software, and the models were used to calculate absorbed dose per unit of time-integrated activity (i.e., S values) for several clinically applied therapeutic radionuclides ((90)Y, (131)I, (177)Lu, (211)At, (225)Ac, (213)Bi, and (223)Ra). Methods: Three-dimensional tumor models of several different shape classifications were generated using Blender software. Ovoid shapes were generated using axial scaling. Lobulated, spiculated, and irregular contours were generated using noise-based mesh deformation. The meshes were rigidly scaled to different volumes, and S values were then computed using PARaDIM software. Radiomic features were extracted for each shape, and the impact on S values was examined. Finally, the systematic error present in dose calculations that model complex tumor shapes versus equivalent-mass spheres was estimated. Results: The dependence of tumor S values on shape was largest for extreme departures from spherical geometry and for long-range emissions (e.g., (90)Y β-emissions). S values for spheres agreed reasonably well with lobulated, spiculated, or irregular contours if the surface perturbation was small. For marked deviations from spherical shape and small volumes, the systematic error of the equivalent-sphere approximation increased to 30%–75% depending on radionuclide. The errors were largest for shapes with many long spicules and for spherical shells with a thickness less than or comparable to the particle range in tissue. Conclusion: Variability in tumor S values as a function of tumor shape and margin contour was observed, suggesting use of contour-matched phantoms to improve the accuracy of tumor dosimetry in organ-level dosimetry paradigms. Implementing a library of tumor phantoms in organ-level dosimetry software may facilitate optimization strategies for personalized radionuclide therapies.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2967/jnumed.122.264916
- https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdf
- OA Status
- bronze
- Cited By
- 6
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4311937304
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4311937304Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.2967/jnumed.122.264916Digital Object Identifier
- Title
-
Dosimetric Variability Across a Library of Computational Tumor PhantomsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-12-08Full publication date if available
- Authors
-
Lukas M. Carter, Simone Krebs, Harry Marquis, Juan Camilo Ocampo Ramos, E Olguin, Emilia O. Mason, Wesley E. Bolch, Pat Zanzonico, Adam KesnerList of authors in order
- Landing page
-
https://doi.org/10.2967/jnumed.122.264916Publisher landing page
- PDF URL
-
https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdfDirect OA link when available
- Concepts
-
Dosimetry, Nuclear medicine, Margin (machine learning), Absorbed dose, Radiation treatment planning, Geometry, Physics, Radiation therapy, Mathematics, Computer science, Medicine, Radiology, Machine learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4311937304 |
|---|---|
| doi | https://doi.org/10.2967/jnumed.122.264916 |
| ids.doi | https://doi.org/10.2967/jnumed.122.264916 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/37074039 |
| ids.openalex | https://openalex.org/W4311937304 |
| fwci | 1.17149707 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D006801 |
| mesh[0].is_major_topic | False |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Humans |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D011874 |
| mesh[1].is_major_topic | True |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Radiometry |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D019047 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Phantoms, Imaging |
| mesh[3].qualifier_ui | Q000000981 |
| mesh[3].descriptor_ui | D009369 |
| mesh[3].is_major_topic | True |
| mesh[3].qualifier_name | diagnostic imaging |
| mesh[3].descriptor_name | Neoplasms |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D009010 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Monte Carlo Method |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D011829 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Radiation Dosage |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D006801 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Humans |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D011874 |
| mesh[7].is_major_topic | True |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Radiometry |
| mesh[8].qualifier_ui | |
| mesh[8].descriptor_ui | D019047 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | |
| mesh[8].descriptor_name | Phantoms, Imaging |
| mesh[9].qualifier_ui | Q000000981 |
| mesh[9].descriptor_ui | D009369 |
| mesh[9].is_major_topic | True |
| mesh[9].qualifier_name | diagnostic imaging |
| mesh[9].descriptor_name | Neoplasms |
| mesh[10].qualifier_ui | |
| mesh[10].descriptor_ui | D009010 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | |
| mesh[10].descriptor_name | Monte Carlo Method |
| mesh[11].qualifier_ui | |
| mesh[11].descriptor_ui | D011829 |
| mesh[11].is_major_topic | False |
| mesh[11].qualifier_name | |
| mesh[11].descriptor_name | Radiation Dosage |
| mesh[12].qualifier_ui | |
| mesh[12].descriptor_ui | D006801 |
| mesh[12].is_major_topic | False |
| mesh[12].qualifier_name | |
| mesh[12].descriptor_name | Humans |
| mesh[13].qualifier_ui | |
| mesh[13].descriptor_ui | D011874 |
| mesh[13].is_major_topic | True |
| mesh[13].qualifier_name | |
| mesh[13].descriptor_name | Radiometry |
| mesh[14].qualifier_ui | |
| mesh[14].descriptor_ui | D019047 |
| mesh[14].is_major_topic | False |
| mesh[14].qualifier_name | |
| mesh[14].descriptor_name | Phantoms, Imaging |
| mesh[15].qualifier_ui | Q000000981 |
| mesh[15].descriptor_ui | D009369 |
| mesh[15].is_major_topic | True |
| mesh[15].qualifier_name | diagnostic imaging |
| mesh[15].descriptor_name | Neoplasms |
| mesh[16].qualifier_ui | |
| mesh[16].descriptor_ui | D009010 |
| mesh[16].is_major_topic | False |
| mesh[16].qualifier_name | |
| mesh[16].descriptor_name | Monte Carlo Method |
| mesh[17].qualifier_ui | |
| mesh[17].descriptor_ui | D011829 |
| mesh[17].is_major_topic | False |
| mesh[17].qualifier_name | |
| mesh[17].descriptor_name | Radiation Dosage |
| mesh[18].qualifier_ui | |
| mesh[18].descriptor_ui | D006801 |
| mesh[18].is_major_topic | False |
| mesh[18].qualifier_name | |
| mesh[18].descriptor_name | Humans |
| mesh[19].qualifier_ui | |
| mesh[19].descriptor_ui | D011874 |
| mesh[19].is_major_topic | True |
| mesh[19].qualifier_name | |
| mesh[19].descriptor_name | Radiometry |
| mesh[20].qualifier_ui | |
| mesh[20].descriptor_ui | D019047 |
| mesh[20].is_major_topic | False |
| mesh[20].qualifier_name | |
| mesh[20].descriptor_name | Phantoms, Imaging |
| mesh[21].qualifier_ui | Q000000981 |
| mesh[21].descriptor_ui | D009369 |
| mesh[21].is_major_topic | True |
| mesh[21].qualifier_name | diagnostic imaging |
| mesh[21].descriptor_name | Neoplasms |
| mesh[22].qualifier_ui | |
| mesh[22].descriptor_ui | D009010 |
| mesh[22].is_major_topic | False |
| mesh[22].qualifier_name | |
| mesh[22].descriptor_name | Monte Carlo Method |
| mesh[23].qualifier_ui | |
| mesh[23].descriptor_ui | D011829 |
| mesh[23].is_major_topic | False |
| mesh[23].qualifier_name | |
| mesh[23].descriptor_name | Radiation Dosage |
| type | article |
| title | Dosimetric Variability Across a Library of Computational Tumor Phantoms |
| biblio.issue | 5 |
| biblio.volume | 64 |
| biblio.last_page | 790 |
| biblio.first_page | 782 |
| topics[0].id | https://openalex.org/T11395 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2741 |
| topics[0].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[0].display_name | Radiopharmaceutical Chemistry and Applications |
| topics[1].id | https://openalex.org/T12422 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9988999962806702 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2741 |
| topics[1].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[1].display_name | Radiomics and Machine Learning in Medical Imaging |
| topics[2].id | https://openalex.org/T10358 |
| topics[2].field.id | https://openalex.org/fields/31 |
| topics[2].field.display_name | Physics and Astronomy |
| topics[2].score | 0.9976000189781189 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3108 |
| topics[2].subfield.display_name | Radiation |
| topics[2].display_name | Advanced Radiotherapy Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C75088862 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7355861663818359 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2291081 |
| concepts[0].display_name | Dosimetry |
| concepts[1].id | https://openalex.org/C2989005 |
| concepts[1].level | 1 |
| concepts[1].score | 0.5915213823318481 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q214963 |
| concepts[1].display_name | Nuclear medicine |
| concepts[2].id | https://openalex.org/C774472 |
| concepts[2].level | 2 |
| concepts[2].score | 0.4683349132537842 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q6760393 |
| concepts[2].display_name | Margin (machine learning) |
| concepts[3].id | https://openalex.org/C151337348 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4424988627433777 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q215313 |
| concepts[3].display_name | Absorbed dose |
| concepts[4].id | https://openalex.org/C201645570 |
| concepts[4].level | 3 |
| concepts[4].score | 0.42031678557395935 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q830637 |
| concepts[4].display_name | Radiation treatment planning |
| concepts[5].id | https://openalex.org/C2524010 |
| concepts[5].level | 1 |
| concepts[5].score | 0.41746535897254944 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[5].display_name | Geometry |
| concepts[6].id | https://openalex.org/C121332964 |
| concepts[6].level | 0 |
| concepts[6].score | 0.3995247185230255 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[6].display_name | Physics |
| concepts[7].id | https://openalex.org/C509974204 |
| concepts[7].level | 2 |
| concepts[7].score | 0.3699601888656616 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q180507 |
| concepts[7].display_name | Radiation therapy |
| concepts[8].id | https://openalex.org/C33923547 |
| concepts[8].level | 0 |
| concepts[8].score | 0.3583453893661499 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[8].display_name | Mathematics |
| concepts[9].id | https://openalex.org/C41008148 |
| concepts[9].level | 0 |
| concepts[9].score | 0.2824555039405823 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[9].display_name | Computer science |
| concepts[10].id | https://openalex.org/C71924100 |
| concepts[10].level | 0 |
| concepts[10].score | 0.24441778659820557 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[10].display_name | Medicine |
| concepts[11].id | https://openalex.org/C126838900 |
| concepts[11].level | 1 |
| concepts[11].score | 0.16930848360061646 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[11].display_name | Radiology |
| concepts[12].id | https://openalex.org/C119857082 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[12].display_name | Machine learning |
| keywords[0].id | https://openalex.org/keywords/dosimetry |
| keywords[0].score | 0.7355861663818359 |
| keywords[0].display_name | Dosimetry |
| keywords[1].id | https://openalex.org/keywords/nuclear-medicine |
| keywords[1].score | 0.5915213823318481 |
| keywords[1].display_name | Nuclear medicine |
| keywords[2].id | https://openalex.org/keywords/margin |
| keywords[2].score | 0.4683349132537842 |
| keywords[2].display_name | Margin (machine learning) |
| keywords[3].id | https://openalex.org/keywords/absorbed-dose |
| keywords[3].score | 0.4424988627433777 |
| keywords[3].display_name | Absorbed dose |
| keywords[4].id | https://openalex.org/keywords/radiation-treatment-planning |
| keywords[4].score | 0.42031678557395935 |
| keywords[4].display_name | Radiation treatment planning |
| keywords[5].id | https://openalex.org/keywords/geometry |
| keywords[5].score | 0.41746535897254944 |
| keywords[5].display_name | Geometry |
| keywords[6].id | https://openalex.org/keywords/physics |
| keywords[6].score | 0.3995247185230255 |
| keywords[6].display_name | Physics |
| keywords[7].id | https://openalex.org/keywords/radiation-therapy |
| keywords[7].score | 0.3699601888656616 |
| keywords[7].display_name | Radiation therapy |
| keywords[8].id | https://openalex.org/keywords/mathematics |
| keywords[8].score | 0.3583453893661499 |
| keywords[8].display_name | Mathematics |
| keywords[9].id | https://openalex.org/keywords/computer-science |
| keywords[9].score | 0.2824555039405823 |
| keywords[9].display_name | Computer science |
| keywords[10].id | https://openalex.org/keywords/medicine |
| keywords[10].score | 0.24441778659820557 |
| keywords[10].display_name | Medicine |
| keywords[11].id | https://openalex.org/keywords/radiology |
| keywords[11].score | 0.16930848360061646 |
| keywords[11].display_name | Radiology |
| language | en |
| locations[0].id | doi:10.2967/jnumed.122.264916 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210180780 |
| locations[0].source.issn | 2159-662X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 2159-662X |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Journal of Nuclear Medicine |
| locations[0].source.host_organization | https://openalex.org/P4310315767 |
| locations[0].source.host_organization_name | Society of Nuclear Medicine and Molecular Imaging |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315767 |
| locations[0].source.host_organization_lineage_names | Society of Nuclear Medicine and Molecular Imaging |
| locations[0].license | |
| locations[0].pdf_url | https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of Nuclear Medicine |
| locations[0].landing_page_url | https://doi.org/10.2967/jnumed.122.264916 |
| locations[1].id | pmid:37074039 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Journal of nuclear medicine : official publication, Society of Nuclear Medicine |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/37074039 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:10152122 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | |
| locations[2].pdf_url | https://pmc.ncbi.nlm.nih.gov/articles/PMC10152122/pdf/jnumed.122.264916.pdf |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | J Nucl Med |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/10152122 |
| indexed_in | crossref, pubmed |
| authorships[0].author.id | https://openalex.org/A5073619753 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4848-4190 |
| authorships[0].author.display_name | Lukas M. Carter |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[0].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[0].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Lukas M. Carter |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[1].author.id | https://openalex.org/A5064278810 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-9909-4531 |
| authorships[1].author.display_name | Simone Krebs |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[1].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[1].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[1].institutions[0].type | healthcare |
| authorships[1].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Simone Krebs |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[2].author.id | https://openalex.org/A5051413710 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0970-5907 |
| authorships[2].author.display_name | Harry Marquis |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[2].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[2].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Harry Marquis |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[3].author.id | https://openalex.org/A5112660730 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-2333-5618 |
| authorships[3].author.display_name | Juan Camilo Ocampo Ramos |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[3].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[3].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[3].institutions[0].type | healthcare |
| authorships[3].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Juan C. Ocampo Ramos |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[4].author.id | https://openalex.org/A5031878906 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-2719-2634 |
| authorships[4].author.display_name | E Olguin |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I1316535847, https://openalex.org/I136199984 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Radiology, Beth Israel Deaconess Medical Center, Harvard University, Boston, Massachusetts |
| authorships[4].institutions[0].id | https://openalex.org/I1316535847 |
| authorships[4].institutions[0].ror | https://ror.org/04drvxt59 |
| authorships[4].institutions[0].type | healthcare |
| authorships[4].institutions[0].lineage | https://openalex.org/I1316535847 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | Beth Israel Deaconess Medical Center |
| authorships[4].institutions[1].id | https://openalex.org/I136199984 |
| authorships[4].institutions[1].ror | https://ror.org/03vek6s52 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I136199984 |
| authorships[4].institutions[1].country_code | US |
| authorships[4].institutions[1].display_name | Harvard University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Edmond A. Olguin |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Radiology, Beth Israel Deaconess Medical Center, Harvard University, Boston, Massachusetts |
| authorships[5].author.id | https://openalex.org/A5001757758 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Emilia O. Mason |
| authorships[5].countries | US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I145608581, https://openalex.org/I4210157065 |
| authorships[5].affiliations[0].raw_affiliation_string | Department of Medicine, Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida |
| authorships[5].institutions[0].id | https://openalex.org/I4210157065 |
| authorships[5].institutions[0].ror | https://ror.org/0552r4b12 |
| authorships[5].institutions[0].type | healthcare |
| authorships[5].institutions[0].lineage | https://openalex.org/I145608581, https://openalex.org/I4210101935, https://openalex.org/I4210157065 |
| authorships[5].institutions[0].country_code | US |
| authorships[5].institutions[0].display_name | Sylvester Comprehensive Cancer Center |
| authorships[5].institutions[1].id | https://openalex.org/I145608581 |
| authorships[5].institutions[1].ror | https://ror.org/02dgjyy92 |
| authorships[5].institutions[1].type | education |
| authorships[5].institutions[1].lineage | https://openalex.org/I145608581 |
| authorships[5].institutions[1].country_code | US |
| authorships[5].institutions[1].display_name | University of Miami |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Emilia O. Mason |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Department of Medicine, Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida |
| authorships[6].author.id | https://openalex.org/A5061230004 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-7175-9968 |
| authorships[6].author.display_name | Wesley E. Bolch |
| authorships[6].countries | US |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I33213144 |
| authorships[6].affiliations[0].raw_affiliation_string | J. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville, Florida |
| authorships[6].institutions[0].id | https://openalex.org/I33213144 |
| authorships[6].institutions[0].ror | https://ror.org/02y3ad647 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I33213144 |
| authorships[6].institutions[0].country_code | US |
| authorships[6].institutions[0].display_name | University of Florida |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Wesley E. Bolch |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | J. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville, Florida |
| authorships[7].author.id | https://openalex.org/A5056859109 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-7334-2752 |
| authorships[7].author.display_name | Pat Zanzonico |
| authorships[7].countries | US |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[7].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[7].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[7].institutions[0].type | healthcare |
| authorships[7].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[7].institutions[0].country_code | US |
| authorships[7].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Pat B. Zanzonico |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[8].author.id | https://openalex.org/A5041144284 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-0686-8316 |
| authorships[8].author.display_name | Adam Kesner |
| authorships[8].countries | US |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[8].affiliations[0].raw_affiliation_string | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| authorships[8].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[8].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[8].institutions[0].type | healthcare |
| authorships[8].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[8].institutions[0].country_code | US |
| authorships[8].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[8].author_position | last |
| authorships[8].raw_author_name | Adam L. Kesner |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdf |
| open_access.oa_status | bronze |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Dosimetric Variability Across a Library of Computational Tumor Phantoms |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11395 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2741 |
| primary_topic.subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| primary_topic.display_name | Radiopharmaceutical Chemistry and Applications |
| related_works | https://openalex.org/W3088366447, https://openalex.org/W758638019, https://openalex.org/W1965151911, https://openalex.org/W2083061615, https://openalex.org/W1990885697, https://openalex.org/W2316654980, https://openalex.org/W2227230075, https://openalex.org/W4255937668, https://openalex.org/W2003305474, https://openalex.org/W1977728264 |
| cited_by_count | 6 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 5 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 3 |
| best_oa_location.id | doi:10.2967/jnumed.122.264916 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210180780 |
| best_oa_location.source.issn | 2159-662X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 2159-662X |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Journal of Nuclear Medicine |
| best_oa_location.source.host_organization | https://openalex.org/P4310315767 |
| best_oa_location.source.host_organization_name | Society of Nuclear Medicine and Molecular Imaging |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315767 |
| best_oa_location.source.host_organization_lineage_names | Society of Nuclear Medicine and Molecular Imaging |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of Nuclear Medicine |
| best_oa_location.landing_page_url | https://doi.org/10.2967/jnumed.122.264916 |
| primary_location.id | doi:10.2967/jnumed.122.264916 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210180780 |
| primary_location.source.issn | 2159-662X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 2159-662X |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Journal of Nuclear Medicine |
| primary_location.source.host_organization | https://openalex.org/P4310315767 |
| primary_location.source.host_organization_name | Society of Nuclear Medicine and Molecular Imaging |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315767 |
| primary_location.source.host_organization_lineage_names | Society of Nuclear Medicine and Molecular Imaging |
| primary_location.license | |
| primary_location.pdf_url | https://jnm.snmjournals.org/content/jnumed/64/5/782.full.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of Nuclear Medicine |
| primary_location.landing_page_url | https://doi.org/10.2967/jnumed.122.264916 |
| publication_date | 2022-12-08 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2440288526, https://openalex.org/W3041875154, https://openalex.org/W3095642462, https://openalex.org/W2952055480, https://openalex.org/W6640860455, https://openalex.org/W1946923111, https://openalex.org/W2766416509, https://openalex.org/W3131646642, https://openalex.org/W3090223225, https://openalex.org/W2036812736, https://openalex.org/W2767128594, https://openalex.org/W2109991971, https://openalex.org/W2032747682, https://openalex.org/W2781913512, https://openalex.org/W2970628000, https://openalex.org/W61836806, https://openalex.org/W2535300095, https://openalex.org/W2883890283, https://openalex.org/W4284989178, https://openalex.org/W1987054640, https://openalex.org/W2921132910, https://openalex.org/W2977291208, https://openalex.org/W1985850867, https://openalex.org/W4210499118, https://openalex.org/W4220809790, https://openalex.org/W2467018059, https://openalex.org/W2143818728, https://openalex.org/W2416734619, https://openalex.org/W4225960017, https://openalex.org/W4225143192, https://openalex.org/W2763355946 |
| referenced_works_count | 31 |
| abstract_inverted_index.S | 110, 167, 186, 213, 232, 304 |
| abstract_inverted_index.a | 288, 307, 334 |
| abstract_inverted_index.In | 0 |
| abstract_inverted_index.To | 70 |
| abstract_inverted_index.an | 84 |
| abstract_inverted_index.as | 306 |
| abstract_inverted_index.if | 245 |
| abstract_inverted_index.in | 57, 195, 298, 302, 329, 339 |
| abstract_inverted_index.of | 12, 29, 38, 67, 74, 86, 106, 130, 211, 263, 309, 319, 326, 336 |
| abstract_inverted_index.on | 32, 81, 185, 215, 271 |
| abstract_inverted_index.or | 53, 63, 242, 292 |
| abstract_inverted_index.to | 59, 100, 163, 268, 294, 322 |
| abstract_inverted_index.For | 251 |
| abstract_inverted_index.The | 158, 209, 273 |
| abstract_inverted_index.and | 6, 78, 95, 124, 149, 166, 182, 225, 257, 283, 312 |
| abstract_inverted_index.are | 18 |
| abstract_inverted_index.for | 112, 179, 219, 226, 234, 277, 284, 347 |
| abstract_inverted_index.may | 343 |
| abstract_inverted_index.per | 104 |
| abstract_inverted_index.the | 26, 33, 36, 60, 72, 96, 183, 191, 246, 260, 264, 295, 324 |
| abstract_inverted_index.use | 318 |
| abstract_inverted_index.was | 89, 188, 206, 217, 249, 315 |
| abstract_inverted_index.dose | 16, 103, 196 |
| abstract_inverted_index.each | 180 |
| abstract_inverted_index.from | 44, 222, 254 |
| abstract_inverted_index.less | 290 |
| abstract_inverted_index.long | 281 |
| abstract_inverted_index.many | 280 |
| abstract_inverted_index.mesh | 156 |
| abstract_inverted_index.than | 291 |
| abstract_inverted_index.that | 198 |
| abstract_inverted_index.then | 170 |
| abstract_inverted_index.unit | 105 |
| abstract_inverted_index.used | 99 |
| abstract_inverted_index.well | 238 |
| abstract_inverted_index.were | 98, 135, 142, 152, 160, 169, 177, 275 |
| abstract_inverted_index.with | 42, 239, 279, 287 |
| abstract_inverted_index.(90)Y | 230 |
| abstract_inverted_index.Ovoid | 140 |
| abstract_inverted_index.Tumor | 15 |
| abstract_inverted_index.array | 85 |
| abstract_inverted_index.axial | 145 |
| abstract_inverted_index.dose, | 83 |
| abstract_inverted_index.dose. | 14 |
| abstract_inverted_index.error | 193, 262 |
| abstract_inverted_index.ideal | 45 |
| abstract_inverted_index.model | 199 |
| abstract_inverted_index.often | 49 |
| abstract_inverted_index.range | 297 |
| abstract_inverted_index.shape | 133, 216, 256, 311 |
| abstract_inverted_index.size, | 77 |
| abstract_inverted_index.small | 258 |
| abstract_inverted_index.tumor | 30, 75, 87, 128, 201, 212, 303, 310, 327, 337 |
| abstract_inverted_index.using | 21, 91, 137, 144, 154, 172 |
| abstract_inverted_index.(e.g., | 229 |
| abstract_inverted_index.(i.e., | 109 |
| abstract_inverted_index.agreed | 236 |
| abstract_inverted_index.assess | 71 |
| abstract_inverted_index.benign | 68 |
| abstract_inverted_index.degree | 37 |
| abstract_inverted_index.design | 93 |
| abstract_inverted_index.errors | 274 |
| abstract_inverted_index.impact | 184 |
| abstract_inverted_index.margin | 79, 313 |
| abstract_inverted_index.marked | 252 |
| abstract_inverted_index.meshes | 159 |
| abstract_inverted_index.models | 97, 129 |
| abstract_inverted_index.scaled | 162 |
| abstract_inverted_index.shape, | 76, 181 |
| abstract_inverted_index.shapes | 141, 202, 278 |
| abstract_inverted_index.shells | 286 |
| abstract_inverted_index.small. | 250 |
| abstract_inverted_index.smooth | 64 |
| abstract_inverted_index.values | 168, 187, 214, 233, 305 |
| abstract_inverted_index.versus | 203 |
| abstract_inverted_index.((90)Y, | 118 |
| abstract_inverted_index.(131)I, | 119 |
| abstract_inverted_index.Blender | 138 |
| abstract_inverted_index.PARaDIM | 173 |
| abstract_inverted_index.applied | 115 |
| abstract_inverted_index.complex | 200 |
| abstract_inverted_index.contour | 80, 314 |
| abstract_inverted_index.derived | 20 |
| abstract_inverted_index.despite | 25 |
| abstract_inverted_index.disease | 39 |
| abstract_inverted_index.effects | 73 |
| abstract_inverted_index.extreme | 220 |
| abstract_inverted_index.improve | 323 |
| abstract_inverted_index.largest | 218, 276 |
| abstract_inverted_index.lesions | 48 |
| abstract_inverted_index.library | 335 |
| abstract_inverted_index.margins | 56 |
| abstract_inverted_index.modeled | 90 |
| abstract_inverted_index.models, | 24 |
| abstract_inverted_index.possess | 50 |
| abstract_inverted_index.present | 194 |
| abstract_inverted_index.regular | 62 |
| abstract_inverted_index.require | 9 |
| abstract_inverted_index.rigidly | 161 |
| abstract_inverted_index.several | 113, 131 |
| abstract_inverted_index.spheres | 205, 235 |
| abstract_inverted_index.surface | 247 |
| abstract_inverted_index.tissue. | 299 |
| abstract_inverted_index.values) | 111 |
| abstract_inverted_index.(177)Lu, | 120 |
| abstract_inverted_index.(211)At, | 121 |
| abstract_inverted_index.(213)Bi, | 123 |
| abstract_inverted_index.(225)Ac, | 122 |
| abstract_inverted_index.Finally, | 190 |
| abstract_inverted_index.Methods: | 126 |
| abstract_inverted_index.Radiomic | 175 |
| abstract_inverted_index.Results: | 208 |
| abstract_inverted_index.absorbed | 82, 102 |
| abstract_inverted_index.accuracy | 325 |
| abstract_inverted_index.accurate | 10 |
| abstract_inverted_index.activity | 108 |
| abstract_inverted_index.commonly | 61 |
| abstract_inverted_index.computed | 171 |
| abstract_inverted_index.contours | 65, 151, 244 |
| abstract_inverted_index.contrast | 58 |
| abstract_inverted_index.features | 176 |
| abstract_inverted_index.function | 308 |
| abstract_inverted_index.geometry | 31, 224 |
| abstract_inverted_index.lesions. | 69 |
| abstract_inverted_index.lobular, | 51 |
| abstract_inverted_index.particle | 296 |
| abstract_inverted_index.phantoms | 321, 338 |
| abstract_inverted_index.planning | 5 |
| abstract_inverted_index.response | 7 |
| abstract_inverted_index.scaling. | 146 |
| abstract_inverted_index.software | 342 |
| abstract_inverted_index.spicules | 282 |
| abstract_inverted_index.therapy, | 2 |
| abstract_inverted_index.volumes, | 165, 259 |
| abstract_inverted_index.(223)Ra). | 125 |
| abstract_inverted_index.30%–75% | 269 |
| abstract_inverted_index.Moreover, | 35 |
| abstract_inverted_index.calculate | 101 |
| abstract_inverted_index.departure | 43 |
| abstract_inverted_index.depending | 270 |
| abstract_inverted_index.different | 132, 164 |
| abstract_inverted_index.dosimetry | 328, 331, 341 |
| abstract_inverted_index.emissions | 228 |
| abstract_inverted_index.estimates | 11, 17 |
| abstract_inverted_index.examined. | 189 |
| abstract_inverted_index.extracted | 178 |
| abstract_inverted_index.generated | 136, 143, 153 |
| abstract_inverted_index.geometry; | 46 |
| abstract_inverted_index.increased | 267 |
| abstract_inverted_index.influence | 28 |
| abstract_inverted_index.irregular | 55, 150, 243 |
| abstract_inverted_index.malignant | 47 |
| abstract_inverted_index.observed, | 316 |
| abstract_inverted_index.otherwise | 54 |
| abstract_inverted_index.routinely | 19 |
| abstract_inverted_index.software, | 94 |
| abstract_inverted_index.software. | 139, 174 |
| abstract_inverted_index.spherical | 23, 223, 255, 285 |
| abstract_inverted_index.thickness | 289 |
| abstract_inverted_index.treatment | 4 |
| abstract_inverted_index.Lobulated, | 147 |
| abstract_inverted_index.clinically | 114 |
| abstract_inverted_index.comparable | 293 |
| abstract_inverted_index.correlates | 41 |
| abstract_inverted_index.departures | 221 |
| abstract_inverted_index.dependence | 210 |
| abstract_inverted_index.deviations | 253 |
| abstract_inverted_index.dosimetry. | 34 |
| abstract_inverted_index.estimated. | 207 |
| abstract_inverted_index.evaluation | 8 |
| abstract_inverted_index.facilitate | 344 |
| abstract_inverted_index.geometries | 88 |
| abstract_inverted_index.lobulated, | 240 |
| abstract_inverted_index.long-range | 227 |
| abstract_inverted_index.paradigms. | 332 |
| abstract_inverted_index.reasonably | 237 |
| abstract_inverted_index.simplistic | 22 |
| abstract_inverted_index.strategies | 346 |
| abstract_inverted_index.suggesting | 317 |
| abstract_inverted_index.systematic | 192, 261 |
| abstract_inverted_index.therapies. | 350 |
| abstract_inverted_index.Conclusion: | 300 |
| abstract_inverted_index.Variability | 301 |
| abstract_inverted_index.noise-based | 155 |
| abstract_inverted_index.organ-level | 330, 340 |
| abstract_inverted_index.spiculated, | 52, 148, 241 |
| abstract_inverted_index.therapeutic | 116 |
| abstract_inverted_index.Implementing | 333 |
| abstract_inverted_index.calculations | 197 |
| abstract_inverted_index.deformation. | 157 |
| abstract_inverted_index.invasiveness | 40 |
| abstract_inverted_index.optimization | 345 |
| abstract_inverted_index.personalized | 348 |
| abstract_inverted_index.perturbation | 248 |
| abstract_inverted_index.radionuclide | 349 |
| abstract_inverted_index.approximation | 266 |
| abstract_inverted_index.radionuclide. | 272 |
| abstract_inverted_index.radionuclides | 117 |
| abstract_inverted_index.characteristic | 66 |
| abstract_inverted_index.computer-aided | 92 |
| abstract_inverted_index.tumor-absorbed | 13 |
| abstract_inverted_index.β-emissions). | 231 |
| abstract_inverted_index.classifications | 134 |
| abstract_inverted_index.contour-matched | 320 |
| abstract_inverted_index.dosimetry-based | 3 |
| abstract_inverted_index.equivalent-mass | 204 |
| abstract_inverted_index.time-integrated | 107 |
| abstract_inverted_index.well-established | 27 |
| abstract_inverted_index.Three-dimensional | 127 |
| abstract_inverted_index.equivalent-sphere | 265 |
| abstract_inverted_index.radiopharmaceutical | 1 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6000000238418579 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.73934953 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |