Q (sonnet): is there any imaging data? ▶ read_guide { "uri": "cbioportal://external-resources-guide" } ◀ result # External Resources Guide Use this guide when the user asks about data that may be linked from cBioPortal rather than stored directly in molecular or clinical tables. ## Routing Triggers Read this guide before answering or refusing questions that mention: - imaging, radiology, CT, MRI, pathology slides, histology, Minerva, viewer - external portal, external resource, image data, spatial data - HTAN studies or study-specific linked viewers ## Core Rule Do not say cBioPortal has no imaging or external-resource data until you have checked: - `resource_definition` - `resource_study` - `resource_sample` - `resource_patient` cBioPortal may store links to external viewers or portals even when it does not store raw images. ## Which Studies Have Imaging Data For "which studies have imaging / pathology slides / CT" or "how many samples have images", read `cancer_study.resource_sample_counts` — per-study sample counts keyed by resource display name, the same numbers as the portal's "Data type" filter. One query, no joins: ```sql SELECT cancer_study_identifier, name, resource_sample_counts['Slide Microscopy'] AS slide_microscopy_samples FROM cancer_study WHERE resource_sample_counts['Slide Microscopy'] > 0 ORDER BY slide_microscopy_samples DESC; ``` List the resource names that exist with `SELECT DISTINCT arrayJoin(mapKeys(resource_sample_counts)) FROM cancer_study` (e.g. `'Slide Microscopy'`, `'Computed Tomography'`, `'Magnetic Resonance'`, `'H&E Slide'`, `'MxIF Image'`). The map counts sample- and patient-level resources only. For study-level links (`resource_study`) and for the URLs themselves, use the queries below. ## Discovery Query Start with table and column validation, then use this pattern: ```sql SELECT rd.resource_id, rd.display_name, rd.description, rd.resource_type, rs.cancer_study_identifier, rs.url FROM resource_study rs JOIN resource_definition rd ON rs.resource_id = rd.resource_id WHERE lower(rd.display_name) LIKE '%minerva%' OR lower(rd.description) LIKE '%minerva%' OR lower(rd.display_name) LIKE '%image%' OR lower(rd.description) LIKE '%image%' OR lower(rd.display_name) LIKE '%pathology%' OR lower(rd.description) LIKE '%pathology%' OR lower(rd.display_name) LIKE '%histology%' OR lower(rd.description) LIKE '%histology%' ORDER BY rs.cancer_study_identifier, rd.display_name LIMIT 100; ``` If no study-level rows appear, check sample- and patient-level resource links: ```sql SELECT rd.resource_id, rd.display_name, rd.description, rs.cancer_study_identifier, rs.sample_unique_id, rs.url FROM resource_sample rs JOIN resource_definition rd ON rs.resource_id = rd.resource_id WHERE lower(rd.display_name) LIKE '%minerva%' OR lower(rd.description) LIKE '%minerva%' OR lower(rd.display_name) LIKE '%image%' OR lower(rd.description) LIKE '%image%' OR lower(rd.display_name) LIKE '%pathology%' OR lower(rd.description) LIKE '%pathology%' … (981 more chars) ▶ clickhouse_run_select_query { "query": "SELECT DISTINCT arrayJoin(mapKeys(resource_sample_counts)) AS resource_name FROM cancer_study" } ◀ result {"rows":[{"resource_name":"MxIF Image"},{"resource_name":"H&E Slide"},{"resource_name":"CyCIF"},{"resource_name":"Slide Microscopy"},{"resource_name":"Computed Tomography"},{"resource_name":"Magnetic Resonance"},{"resource_name":"Positron Emission Tomography"},{"resource_name":"Nuclear Medicine"},{"resource_name":"Computed Radiography"},{"resource_name":"Mammography"},{"resource_name":"Digital Radiography"}]} ▶ clickhouse_run_select_query { "query": " SELECT cancer_study_identifier, name, resource_sample_counts['Slide Microscopy'] AS slide_microscopy, resource_sample_counts['H&E Slide'] AS he_slide, resource_sample_counts['MxIF Image'] AS mxif, resource_sample_counts['CyCIF'] AS cycif, resource_sample_counts['Computed Tomography'] AS ct, resource_sample_counts['Magnetic Resonance'] AS mri, resource_sample_counts['Positron Emission Tomography'] AS pet, resource_sample_counts['Nuclear Medicine'] AS nuc_med, resource_sample_counts['Computed Radiography'] AS comp_rad, resource_sample_counts['Mammography'] AS mammo, resource_sample_counts['Digital Radiography'] AS digital_rad FROM cancer_study WHERE resource_sample_counts['Slide Microscopy'] > 0 OR resource_sample_counts['H&E Slide'] > 0 OR resource_sample_counts['MxIF Image'] > 0 OR resource_sample_counts['CyCIF'] > 0 OR resource_sample_counts['Computed Tomography'] > 0 OR resource_sample_counts['Magnetic Resonance'] > 0 OR resource_sample_counts['Positron Emission Tomography'] > 0 OR resource_sample_counts['Nuclear Medicine'] > 0 OR resource_sample_counts['Computed Radiography'] > 0 OR resource_sample_counts['Mammography'] > 0 OR resource_sample_counts['Digital Radiography'] > 0 ORDER BY slide_microscopy DESC ", "max_rows": 100 } ◀ result {"rows":[{"cancer_study_identifier":"brca_tcga_pan_can_atlas_2018","name":"Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":1084,"he_slide":0,"mxif":0,"cycif":0,"ct":0,"mri":136,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":5,"digital_rad":0},{"cancer_study_identifier":"coadread_tcga_pan_can_atlas_2018","name":"Colorectal Adenocarcinoma (TCGA, PanCancer Atlas)","slide_microscopy":594,"he_slide":0,"mxif":0,"cycif":0,"ct":21,"mri":0,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"gbm_tcga_pan_can_atlas_2018","name":"Glioblastoma Multiforme (TCGA, PanCancer Atlas)","slide_microscopy":592,"he_slide":0,"mxif":0,"cycif":0,"ct":0,"mri":0,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","slide_microscopy":575,"he_slide":0,"mxif":0,"cycif":0,"ct":140,"mri":1,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"ucec_tcga_pan_can_atlas_2018","name":"Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":529,"he_slide":0,"mxif":0,"cycif":0,"ct":65,"mri":8,"pet":5,"nuc_med":0,"comp_rad":1,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"hnsc_tcga_pan_can_atlas_2018","name":"Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":518,"he_slide":0,"mxif":0,"cycif":0,"ct":0,"mri":0,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"lgg_tcga_pan_can_atlas_2018","name":"Brain Lower Grade Glioma (TCGA, PanCancer Atlas)","slide_microscopy":514,"he_slide":0,"mxif":0,"cycif":0,"ct":0,"mri":0,"pet":0,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"luad_tcga_pan_can_atlas_2018","name":"Lung Adenocarcinoma (TCGA, PanCancer Atlas)","slide_microscopy":514,"he_slide":0,"mxif":0,"cycif":0,"ct":60,"mri":0,"pet":23,"nuc_med":2,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"kirc_tcga_pan_can_atlas_2018","name":"Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":512,"he_slide":0,"mxif":0,"cycif":0,"ct":221,"mri":60,"pet":0,"nuc_med":0,"comp_rad":1,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"thca_tcga_pan_can_atlas_2018","name":"Thyroid Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":500,"he_slide":0,"mxif":0,"cycif":0,"ct":6,"mri":0,"pet":1,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"prad_tcga_pan_can_atlas_2018","name":"Prostate Adenocarcinoma (TCGA, PanCancer Atlas)","slide_microscopy":494,"he_slide":0,"mxif":0,"cycif":0,"ct":4,"mri":10,"pet":3,"nuc_med":0,"comp_rad":0,"mammo":0,"digital_rad":0},{"cancer_study_identifier":"lusc_tcga_pan_can_atlas_2018","name":"Lung Squamous Cell Carcinoma (TCGA, PanCancer Atlas)","slide_microscopy":487,"he_slide":0,"mxif":0,"cycif":0,"ct":33,"mri":0,"pet":19,"nuc_med":2,"comp_rad":0,"mammo":0,"digit … (6325 more chars) ═ answer (success) Yes — cBioPortal links to imaging and pathology resources for many studies, though it stores links to external viewers rather than raw image files/pixels directly in its own database. Types found include: - **Slide Microscopy / H&E slides** (histopathology whole-slide images) - **Multiplex imaging**: MxIF, CyCIF - **Radiology**: Computed Tomography (CT), Magnetic Resonance (MRI), Positron Emission Tomography (PET), Nuclear Medicine, Mammography, Computed/Digital Radiography **Notable examples:** | Study | Slide Microscopy | CT | MRI | Other | |---|---|---|---|---| | [Breast Invasive Carcinoma (TCGA PanCancer Atlas)](https://www.cbioportal.org/study/summary?id=brca_tcga_pan_can_atlas_2018) | 1,084 samples | – | 136 | 5 mammography | | [Kidney Renal Clear Cell Carcinoma (TCGA PanCancer Atlas)](https://www.cbioportal.org/study/summary?id=kirc_tcga_pan_can_atlas_2018) | 512 | 221 | 60 | 1 radiography | | [Ovarian Serous Cystadenocarcinoma (TCGA PanCancer Atlas)](https://www.cbioportal.org/study/summary?id=ov_tcga_pan_can_can_atlas_2018) | 575 | 140 | 1 | – | | [Ovarian Cancer – MSK SPECTRUM](https://www.cbioportal.org/study/summary?id=msk_spectrum_tme_2022) | – | – | – | 37 H&E slides, 8 MxIF | | [Ovarian Cancer (Gray Foundation)](https://www.cbioportal.org/study/summary?id=ovary_geomx_gray_foundation_2024) | – | – | – | 567 CyCIF images | | [Colorectal Cancer (HTAN MSK)](https://www.cbioportal.org/study/summary?id=crc_hta8_htan_2024) | – | – | – | 58 MxIF images | | [Pre-cancer Colorectal Polyps (HTAN Vanderbilt)](https://www.cbioportal.org/study/summary?id=crc_hta11_htan_2021) | – | – | – | 26 H&E, 25 MxIF | Essentially all TCGA PanCancer Atlas studies (34 shown above) have slide microscopy links, and several also have radiology (CT/MRI/PET) links. The HTAN- and MSK-derived studies (SPECTRUM, HTAN colorectal, Orion, Gray Foundation) additionally carry multiplex fluorescence/H&E imaging, often viewable through embedded viewers like Minerva. Would you like me to open a specific study's summary page to explore its imaging data availability directly (e.g., filter samples by "Slide Microscopy" or view the Minerva-linked images)?