Evidence map›Paper›PMID 27487870›Full record

ArticleMedical physics2016

Library based x-ray scatter correction for dedicated cone beam breast CT.

Linxi Shi, Srinivasan Vedantham, Andrew Karellas, Lei Zhu

Abstract readEvaluation Study
In one paragraph

Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Artificial Intelligence in Breast X-Ray Imaging.Seminars in ultrasound, CT, and MR · 2023
    Review
  4. Article
  5. Flat-panel conebeam CT in the clinic: history and current state.Journal of medical imaging (Bellingham, Wash.) · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Cone-beam breast computed tomography using ultra-fast image reconstruction with constrained, total-variation minimization for suppression of artifacts.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Emerging Breast Imaging Technologies on the Horizon.Seminars in ultrasound, CT, and MR · 2018
    Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

Linxi ShiNuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332.
Srinivasan VedanthamDepartment of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655.
Andrew KarellasDepartment of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655.
Lei ZhuNuclear and Radiological Engineering and Medical Physics Programs, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332.

Funding

Reducing mastectomy rates in invasive lobular carcinoma by high-resolution 3D breast CTR01CA195512 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI VEDANTHAM, SRINIVASAN · 2015 to 2017
$757k
Role of 3D Tomography in Breast CancerR21CA134128 · NCI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI GLICK, STEPHEN J, KARELLAS, ANDREW · 2009 to 2010
$723k
Volumetric CT Imaging using Primary ModulationR21EB019597 · NIBIB · GEORGIA INSTITUTE OF TECHNOLOGY · PI ZHU, LEI · 2015 to 2016
$411k
NCI NIH HHS R01 CA195512NCI NIH HHS R21 CA134128NIBIB NIH HHS R21 EB019597
6 · The paper itself

Abstract

purposeThe image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability.

methodsThe authors precompute a scatter library on simplified breast models with different sizes using the geant4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation.

resultsSince the time-consuming MC simulation for library generation is precomputed, the authors' method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors' method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views.

conclusionsThe library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors' approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.

Indexed as

Scattering, RadiationX-RaysAlgorithmsBreastComputer SimulationCone-Beam Computed TomographyDatasets as TopicFeasibility StudiesHumansMammographyModels, AnatomicMonte Carlo MethodOrgan SizeRetrospective StudiesTime Factors

Identifiers

PMID27487870
PMCPMC4947049

What OpenQuestion holds

Textmetadata
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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.