Evidence map›Paper›PMID 30422761›Full record

ReviewRadiographics : a review publication of the Radiological Society of North America, Inc

Deep Learning Electronic Cleansing for Single- and Dual-Energy CT Colonography.

Rie Tachibana, Janne J Näppi, Junko Ota, Nadja Kohlhase, Toru Hironaka, Se Hyung Kim, Daniele Regge, Hiroyuki Yoshida

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PubMed Full text at PMC Publisher
In one paragraph

Review in Radiographics : a review publication of the Radiological Society of North America, Inc. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

6 citing papers in PubMed, 27 citations in OpenAlex.

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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

8 authors at 4 institutions in 4 countries.

Rie TachibanaFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Janne J NäppiFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Junko OtaFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Nadja KohlhaseFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Toru HironakaFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Se Hyung KimFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).ORCID http://orcid.org/0000-0001-8664-0356
Daniele ReggeFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Hiroyuki YoshidaFrom the 3D Imaging Research Lab, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon St, Suite 400C, Boston, MA 02114 (R.T., J.J.N., N.K., T.H., H.Y.); Department of Information Science and Technology, National Institute of Technology, Oshima College, Yamaguchi, Japan (R.T.); Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan (J.O.); Department of Medical Physics, University of Applied Sciences Giessen, Giessen, Germany (N.K.); Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.K.); Department of Surgical Sciences, University of Torino, Turin, Italy (D.R.); and Candiolo Cancer Institute, Fondazione del Piemonte per l'Oncologia-Istituto di Ricovero e Cura a Carattere Scientifico (FPO-IRCCS), Candiolo, Turin, Italy (D.R.).
Harvard University · USCandiolo Cancer Institute · ITSeoul National University Hospital · KRThe University of Osaka · JP

Funding

Cloud-computer-aided diagnostic imaging decision support systemR01CA166816 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI YOSHIDA, HIROYUKI · 2012 to 2015
$1.9M
Spectral precision imaging for early diagnosis of colorectal lesions with CT colonographyR01CA212382 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI YOSHIDA, HIROYUKI · 2018 to 2022
$1.5M
Deep radiomic colon cleansing for laxative-free CT colonographyR21EB024025 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI NAPPI, JANNE JOHANNES · 2017 to 2018
$470k
NCI NIH HHS R01 CA166816NCI NIH HHS R01 CA212382NIBIB NIH HHS R21 EB024025
6 · The paper itself

Abstract

Electronic cleansing (EC) is used for computational removal of residual feces and fluid tagged with an orally administered contrast agent on CT colonographic images to improve the visibility of polyps during virtual endoscopic "fly-through" reading. A recent trend in CT colonography is to perform a low-dose CT scanning protocol with the patient having undergone reduced- or noncathartic bowel preparation. Although several EC schemes exist, they have been developed for use with cathartic bowel preparation and high-radiation-dose CT, and thus, at a low dose with noncathartic bowel preparation, they tend to generate cleansing artifacts that distract and mislead readers. Deep learning can be used for improvement of the image quality with EC at CT colonography. Deep learning EC can produce substantially fewer cleansing artifacts at dual-energy than at single-energy CT colonography, because the dual-energy information can be used to identify relevant material in the colon more precisely than is possible with the single x-ray attenuation value. Because the number of annotated training images is limited at CT colonography, transfer learning can be used for appropriate training of deep learning algorithms. The purposes of this article are to review the causes of cleansing artifacts that distract and mislead readers in conventional EC schemes, to describe the applications of deep learning and dual-energy CT colonography to EC of the colon, and to demonstrate the improvements in image quality with EC and deep learning at single-energy and dual-energy CT colonography with noncathartic bowel preparation.

Indexed as

Deep LearningAlgorithmsCatharticsColonography, Computed TomographicColorectal NeoplasmsContrast MediaFecesHumansRadiation DosageCatharticsContrast Media

Identifiers

PMID30422761
PMCPMC6276077
OpenAlexW2900582237

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.