Quantitative Imaging Informatics for Cancer Research

Fedorov, Andrey; Beichel, Reinhard; Kalpathy–Cramer, Jayashree; Clunie, David A.; Onken, Michael D.; Riesmeier, Jörg; Herz, Christian; Bauer, Christian; Beers, Andrew; Fillion‐Robin, Jean‐Christophe; Lassó, András; Pintér, Csaba; Pieper, Steve; Nolden, Marco; Maier‐Hein, Klaus H.; Herrmann, Markus D.; Saltz, Joel; Prior, Fred; Fennessy, Fiona M.; Buatti, John M.; Kikinis, Ron

doi:10.1200/cci.19.00165

Cited by 13 publications

(14 citation statements)

References 34 publications

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“…Although not included in the present study, the first aimed to deliver an extensible platform to support site-specific workflows and accommodate evolving research requirements, according to DICOM specifications. Instead, IDC highlighted the role of the DICOM format as a cornerstone for sharing data and harmonizing analyses [ 104 ].…”

Section: Discussionmentioning

confidence: 99%

How does DICOM support big data management? Investigating its use in medical imaging community

Aiello

Esposito²,

Pagliari³

et al. 2021

Insights Imaging

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The diagnostic imaging field is experiencing considerable growth, followed by increasing production of massive amounts of data. The lack of standardization and privacy concerns are considered the main barriers to big data capitalization. This work aims to verify whether the advanced features of the DICOM standard, beyond imaging data storage, are effectively used in research practice. This issue will be analyzed by investigating the publicly shared medical imaging databases and assessing how much the most common medical imaging software tools support DICOM in all its potential. Therefore, 100 public databases and ten medical imaging software tools were selected and examined using a systematic approach. In particular, the DICOM fields related to privacy, segmentation and reporting have been assessed in the selected database; software tools have been evaluated for reading and writing the same DICOM fields. From our analysis, less than a third of the databases examined use the DICOM format to record meaningful information to manage the images. Regarding software, the vast majority does not allow the management, reading and writing of some or all the DICOM fields. Surprisingly, if we observe chest computed tomography data sharing to address the COVID-19 emergency, there are only two datasets out of 12 released in DICOM format. Our work shows how the DICOM can potentially fully support big data management; however, further efforts are still needed from the scientific and technological community to promote the use of the existing standard, encouraging data sharing and interoperability for a concrete development of big data analytics.

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Section: Discussionmentioning

confidence: 99%

How does DICOM support big data management? Investigating its use in medical imaging community

Aiello

Esposito²,

Pagliari³

et al. 2021

Insights Imaging

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“…The human leukocyte antigen (HLA) alleles of patients were downloaded from TCIA database [15], the mutations of patients in TCGA pan-cancer cohort (N = 10967) were downloaded from the cBioPortal database [16], and the recurrent mutations (frequency ≥ 2) of PTPRT were selected for neoantigen prediction using NetMHC [17],…”

Section: The Neoantigen Prediction For Recurrent Mutations In Ptprtmentioning

confidence: 99%

Association of PTPRT Mutations with Cancer Metastasis in Multiple Cancer Types

Chen

Liu

et al. 2022

BioMed Research International

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Metastasis is one of the characteristics of advanced cancer and the primary cause of cancer-related deaths from cancer, but the mechanism underlying metastasis is unclear, and there is a lack of metastasis markers. PTPRT is a protein-coding gene involved in both signal transduction and cellular adhesion. It is also known as a tumor suppressor gene that inhibits cell malignant proliferation by inhibiting the STAT3 pathway. Recent studies have reported that PTPRT is involved in the early metastatic seeding of colorectal cancer; however, the correlation between PTPRT and metastasis in other types of cancer has not been revealed. A combined analysis using a dataset from the genomics evidence neoplasia information exchange (GENIE) and cBioPortal revealed that PTPRT mutation is associated with poor prognosis in pan-cancer and non-small-cell lung cancer. The mutations of PTPRT or “gene modules” containing PTPRT are significantly enriched in patients with metastatic cancer in multiple cancers, suggesting that the PTPRT mutations serve as potential biomarkers of cancer metastasis.

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“…Equally important is the ability to support the results obtained by analysis of imaging data, such as annotations of image regions of interest or various descriptors of image findings. DICOM defines data models and standard information objects that cover a significant portion of the expected needs in communicating image analysis results [14][15][16]. It can also be extended to support new types of data, wherever possible retaining compatibility with legacy systems [17].…”

Section: Data Modelingmentioning

confidence: 99%

NCI Imaging Data Commons

et al. 2021

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The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloudbased data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot™. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of de-identified imaging data and to support integrated analyses with non-imaging data. We achieve this goal by co-locating versatile imaging collections with cloudbased computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research.Significance: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud.

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Quantitative Imaging Informatics for Cancer Research

Cited by 13 publications

References 34 publications

How does DICOM support big data management? Investigating its use in medical imaging community

How does DICOM support big data management? Investigating its use in medical imaging community

Association of PTPRT Mutations with Cancer Metastasis in Multiple Cancer Types

NCI Imaging Data Commons

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