Evidence map›Paper›PMID 27613662›Full record

ArticlePathology, research and practice2016

Deformable image registration between pathological images and MR image via an optical macro image.

Takashi Ohnishi, Yuka Nakamura, Toru Tanaka, Takuya Tanaka, Noriaki Hashimoto, Hideaki Haneishi, Tracy T Batchelor, Elizabeth R Gerstner, Jennie W Taylor, Matija Snuderl and 1 more

Abstract read
In one paragraph

Article in Pathology, research and practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Three-dimensional histology reveals dissociable human hippocampal long-axis gradients of Alzheimer's pathology.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

11 authors.

Takashi OhnishiCenter for Frontier Medical Engineering, Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba 263-8522, Japan. Electronic address: t-ohnishi@chiba-u.jp.
Yuka NakamuraGraduate School of Engineering, Chiba University, Japan.
Toru TanakaGraduate School of Engineering, Chiba University, Japan.
Takuya TanakaGraduate School of Engineering, Chiba University, Japan.
Noriaki HashimotoCenter for Frontier Medical Engineering, Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba 263-8522, Japan.
Hideaki HaneishiCenter for Frontier Medical Engineering, Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba 263-8522, Japan.
Tracy T BatchelorMassachusetts General Hospital Cancer Center, Boston, MA 02144, USA; Harvard Medical School, Boston, MA 02215, USA.
Elizabeth R GerstnerMassachusetts General Hospital Cancer Center, Boston, MA 02144, USA; Harvard Medical School, Boston, MA 02215, USA.
Jennie W TaylorMassachusetts General Hospital Cancer Center, Boston, MA 02144, USA; Harvard Medical School, Boston, MA 02215, USA.
Matija SnuderlNew York University Langone Medical Center, New York, NY 10016, USA.
Yukako YagiHarvard Medical School, Boston, MA 02215, USA; Massachusetts General Hospital Pathology Imaging and Communication Technology (PICT) Center, Boston, MA 02214, USA.

Funding

Training Program in Nervous System TumorsK12CA090354 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI PLOTKIN, SCOTT R · 2001 to 2025
$16.3M
AZD2171 and chemoradiation for newly diagnosed glioblastomaR01CA129371 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BATCHELOR, TRACY T · 2007 to 2017
$6.2M
Clinical and Molecular Studies of Novel Therapeutics in Malignant Brain TumorsK24CA125440 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BATCHELOR, TRACY T · 2007 to 2016
$1.9M
NCI NIH HHS K12 CA090354NCI NIH HHS K24 CA125440NCI NIH HHS R01 CA129371
6 · The paper itself

Abstract

Computed tomography (CT) and magnetic resonance (MR) imaging have been widely used for visualizing the inside of the human body. However, in many cases, pathological diagnosis is conducted through a biopsy or resection of an organ to evaluate the condition of tissues as definitive diagnosis. To provide more advanced information onto CT or MR image, it is necessary to reveal the relationship between tissue information and image signals. We propose a registration scheme for a set of PT images of divided specimens and a 3D-MR image by reference to an optical macro image (OM image) captured by an optical camera. We conducted a fundamental study using a resected human brain after the death of a brain cancer patient. We constructed two kinds of registration processes using the OM image as the base for both registrations to make conversion parameters between the PT and MR images. The aligned PT images had shapes similar to the OM image. On the other hand, the extracted cross-sectional MR image was similar to the OM image. From these resultant conversion parameters, the corresponding region on the PT image could be searched and displayed when an arbitrary pixel on the MR image was selected. The relationship between the PT and MR images of the whole brain can be analyzed using the proposed method. We confirmed that same regions between the PT and MR images could be searched and displayed using resultant information obtained by the proposed method. In terms of the accuracy of proposed method, the TREs were 0.56±0.39mm and 0.87±0.42mm. We can analyze the relationship between tissue information and MR signals using the proposed method.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingHumansImage Interpretation, Computer-AssistedImage registrationMR imageOptical imagePathological imageWhole slide imaging

Identifiers

PMID27613662
PMCPMC5097673

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.