Evidence map›Paper›PMID 35040676›Full record

ArticleRadiology2022

Semisupervised Training of a Brain MRI Tumor Detection Model Using Mined Annotations.

Nathaniel C Swinburne, Vivek Yadav, Julie Kim, Ye R Choi, David C Gutman, Jonathan T Yang, Nelson Moss, Jacqueline Stone, Jamie Tisnado, Vaios Hatzoglou and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Blind spots in brain imaging: a pictorial essay.Quantitative imaging in medicine and surgery · 2025
    Review
  5. Review
  6. A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Nathaniel C Swinburne *From the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0001-5831-7287
Vivek Yadav *From the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0001-6145-0281
Julie KimFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0001-7613-4089
Ye R ChoiFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
David C GutmanFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
Jonathan T YangFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
Nelson MossFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0002-0930-1681
Jacqueline StoneFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
Jamie TisnadoFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0003-1608-3595
Vaios HatzoglouFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0003-0252-0694
Sofia S HaqueFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0003-4673-9997
Sasan KarimiFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
John LyoFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0002-6453-6539
Krishna JuluruFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0001-8203-8894
Karl PichottaFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0001-7062-2970
Jianjiong GaoFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
Sohrab P ShahFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
Andrei I HolodnyFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).ORCID 0000-0002-1159-2705
Robert J YoungFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).
MSK MIND ConsortiumFrom the Departments of Radiology (N.C.S., V.Y., Y.R.C., D.C.G., J.T., V.H., S.S.H., S.K., J.L., K.J., A.I.H., R.J.Y.), Radiation Oncology (J.T.Y.), Neurosurgery (N.M.), Neurology (J.S.), and Epidemiology and Biostatistics, Division of Computational Oncology, (K.P., J.G., S.P.S.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Weill Cornell Medical College, New York, NY (J.K.).

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Training and Career Development and Education CoreU54CA137788 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Daniel Alan Heller · 2008 to 2026
$28.1M
Supplement: Network Methods for Brain Imaging with TumorsR01EB022720 · NIBIB · CITY COLLEGE OF NEW YORK · PI HOLODNY, ANDREI I, MAKSE, HERNAN · 2016 to 2018
$1.3M
Identification of Essential Areas of the Brain in Pre-Operative Brain Tumor Patients Using BOLD fMRI and Independent Physiological ParametersR21CA220144 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI HOLODNY, ANDREI I, PECK, KYUNG · 2017 to 2019
$427k
NCI NIH HHS P30 CA008748NCI NIH HHS R21 CA220144NCI NIH HHS U54 CA137788NIBIB NIH HHS R01 EB022720
6 · The paper itself

Abstract

Background Artificial intelligence (AI) applications for cancer imaging conceptually begin with automated tumor detection, which can provide the foundation for downstream AI tasks. However, supervised training requires many image annotations, and performing dedicated post hoc image labeling is burdensome and costly. Purpose To investigate whether clinically generated image annotations can be data mined from the picture archiving and communication system (PACS), automatically curated, and used for semisupervised training of a brain MRI tumor detection model. Materials and Methods In this retrospective study, the cancer center PACS was mined for brain MRI scans acquired between January 2012 and December 2017 and included all annotated axial T1 postcontrast images. Line annotations were converted to boxes, excluding boxes shorter than 1 cm or longer than 7 cm. The resulting boxes were used for supervised training of object detection models using RetinaNet and Mask region-based convolutional neural network (R-CNN) architectures. The best-performing model trained from the mined data set was used to detect unannotated tumors on training images themselves (self-labeling), automatically correcting many of the missing labels. After self-labeling, new models were trained using this expanded data set. Models were scored for precision, recall, and F

Indexed as

Artificial IntelligenceNeural Networks, ComputerBrainHumansMagnetic Resonance ImagingRetrospective Studies

Identifiers

PMID35040676
PMCPMC8962822

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.