Evidence map›Paper›PMID 25222610›Full record

ArticlePloS one2014

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

Kendra A Batchelder, Aaron B Tanenbaum, Seth Albert, Lyne Guimond, Pierre Kestener, Alain Arneodo, Andre Khalil

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
8.5field-weighted citation impact, top 2% 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

10 citing papers in PubMed, 40 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

7 authors at 3 institutions in 2 countries.

Kendra A BatchelderCompuMAINE Lab, University of Maine, Orono, Maine, United States of America; Department of Mathematics and Statistics, University of Maine, Orono, Maine, United States of America; Institute for Molecular Biophysics, University of Maine, Orono, Maine, United States of America.
Aaron B TanenbaumCompuMAINE Lab, University of Maine, Orono, Maine, United States of America; Department of Mathematics and Statistics, University of Maine, Orono, Maine, United States of America; Institute for Molecular Biophysics, University of Maine, Orono, Maine, United States of America.
Seth AlbertCompuMAINE Lab, University of Maine, Orono, Maine, United States of America; Department of Mathematics and Statistics, University of Maine, Orono, Maine, United States of America; Institute for Molecular Biophysics, University of Maine, Orono, Maine, United States of America.
Lyne GuimondCompuMAINE Lab, University of Maine, Orono, Maine, United States of America; Department of Mathematics and Statistics, University of Maine, Orono, Maine, United States of America; Institute for Molecular Biophysics, University of Maine, Orono, Maine, United States of America.
Pierre KestenerCommissariat a l'Energie Atomique, Gif-sur-Yvette, France.
Alain ArneodoLaboratoire de Physique, Ecole Normale Superieure de Lyon, Lyon, France; Centre National de Recherche Scientifique, Ecole Normale Superieure de Lyon, Lyon, France.
Andre KhalilCompuMAINE Lab, University of Maine, Orono, Maine, United States of America; Department of Mathematics and Statistics, University of Maine, Orono, Maine, United States of America; Institute for Molecular Biophysics, University of Maine, Orono, Maine, United States of America.
University of Maine · USCommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRÉcole Normale Supérieure de Lyon · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.

Indexed as

Radiographic Image Interpretation, Computer-AssistedBayes TheoremBreast NeoplasmsCalcinosisFemaleFractalsHumansMammography

Identifiers

PMID25222610
PMCPMC4164655
OpenAlexW2117424789

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.