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Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions

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Abstract

Purpose

To assess the diagnostic performance of radiomic analysis using high temporal resolution (HTR)-dynamic contrast enhancement (DCE) MR sequences compared to BI-RADS analysis to distinguish benign from malignant breast lesions.

Materials and methods

We retrospectively analyzed data from consecutive women who underwent breast MRI including HTR-DCE MR sequencing for abnormal enhancing lesions and who had subsequent pathological analysis at our tertiary center. Semi-quantitative enhancement parameters and textural features were extracted. Temporal change across each phase of textural features in HTR-DCE MR sequences was calculated and called “kinetic textural parameters.” Statistical analysis by LASSO logistic regression and cross validation was performed to build a model. The diagnostic performance of the radiomic model was compared to the results of BI-RADS MR score analysis.

Results

We included 117 women with a mean age of 54 years (28–88). Of the 174 lesions analyzed, 75 were benign and 99 malignant. Seven semi-quantitative enhancement parameters and 57 textural features were extracted. Regression analysis selected 15 significant variables in a radiomic model (called “malignant probability score”) which displayed an AUC = 0.876 (sensitivity = 0.98, specificity = 0.52, accuracy = 0.78). The performance of the malignant probability score to distinguish benign from malignant breast lesions (AUC = 0.876, 95%CI 0.825–0.925) was significantly better than that of BI-RADS analysis (AUC = 0.831, 95%CI 0.769–0.892). The radiomic model significantly reduced false positives (42%) with the same number of missed cancers (n = 2).

Conclusion

A radiomic model including kinetic textural features extracted from an HTR-DCE MR sequence improves diagnostic performance over BI-RADS analysis.

Key Points

• Radiomic analysis using HTR-DCE is of better diagnostic performance (AUC = 0.876) than conventional breast MRI reading with BI-RADS (AUC = 0.831) (p < 0.001).

• A radiomic malignant probability score under 19.5% gives a negative predictive value of 100% while a malignant probability score over 81% gives a positive predictive value of 100%.

• Kinetic textural features extracted from HTR-DCE-MRI have a major role to play in distinguishing benign from malignant breast lesions.

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Abbreviations

AUC:

Area under the receiver operating characteristic curve

BI-RADS:

Breast Imaging Reporting and Data System

CCC:

Concordance correlation coefficient

CEROG:

Comité d’Ethique de la Recherche en Obstetrique et Gynecologie

DCE:

Dynamic contrast enhancement

DCIS:

Ductal carcinomas in situ

DISCO:

Differential Subsampling with Cartesian Ordering

EA:

Enhancement amplitude

EI:

Enhancement integral

GLCM:

Gray-level co-occurrence matrix

GLDM:

Gray-level dependence matrix

GLRLM:

Gray-level run length matrix

GLSZM:

Gray-level size zone matrix

HTR:

High temporal resolution

ICC:

Intra-class correlation coefficient

IDC:

Invasive ductal carcinoma

Imc1:

Informational measure of correlation 1

LASSO:

Least Absolute Shrinkage and Selection Operator

MR:

Magnetic resonance

MSI:

Maximum slope of increase

PACS:

Picture archiving and communication system

RLNN:

Run length non-uniformity normalized

Rmax:

Maximum of enhancement

RmaxTiming:

Timing of maximum of enhancement

ROC:

Receiver operating characteristic

ROI:

Region of interest

SPGR:

Spoiled gradient recalled

STD:

Standard deviation of signal intensity

THR:

Time of half rising

WIR:

Wash-in-rate

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Acknowledgments

Nicolas Mion Eng. and Julie Poujol, PhD.

Funding

Saskia Vande Perre has received a Young Award from the Société Francaise de Radiologie.

Author information

Authors and Affiliations

  1. Tenon Hospital, APHP, Sorbonne Université, 75020, Paris, France

    Saskia Vande Perre, Audrey Milon, Asma Bekhouche, Francois H. Cornelis & Isabelle Thomassin-Naggara

  2. PARCC, INSERM, Université de Paris, F-75015, Paris, France

    Saskia Vande Perre, Loïc Duron, Daniel Balvay & Laure Fournier

  3. ISCD, Sorbonne Université, 75005, Paris, France

    Francois H. Cornelis & Isabelle Thomassin-Naggara

  4. HEGP, APHP Université de Paris, Univ Paris 06, IUC, 75015, Paris, France

    Laure Fournier

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Correspondence to Isabelle Thomassin-Naggara.

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Guarantor

The scientific guarantor of this publication is Isabelle Thomassin-Naggara.

Conflict of interest

Saskia Vande Perre, Loic Duron, Audrey Milon, Asma Bekhouche, Daniel Balvay, and François H. Cornelis: no relationships with any companies, whose products or services may be related to the subject matter of the article.

Laure Fournier: Receipt of grants/research supports (related with the subject matter of the article) with Philips, ArianaPharma, Evolucare, Invectys. Receipt of honoraria or consultation fees (not related with the subject) with Novartis, Janssen, and Sanofi. Speaker fees (not related with the subject) with Novartis, Bayer, Janssen, Sanofi, Pfizer, GE Healthcare.

Isabelle Thomassin - Naggara: Remunerated lecture with GE, Hologic, Canon, Guerbet, and one participation to board expert meeting (Siemens).

Statistics and biometry

Nicolas Mion, engineer, kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

CEROG 2018-GYN-0803.

Study subjects or cohorts overlap

One study has been previously published on the same cohort:

Milon, A. et al Abbreviated breast MRI combining FAST protocol and high temporal resolution (HTR) dynamic contrast enhanced (DCE) sequence. European Journal of Radiology 117, 199–208 (2019).

Methodology

• retrospective

• diagnostic study

• performed at one institution

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Perre, S.V., Duron, L., Milon, A. et al. Radiomic analysis of HTR-DCE MR sequences improves diagnostic performance compared to BI-RADS analysis of breast MR lesions. Eur Radiol 31, 4848–4859 (2021). https://doi.org/10.1007/s00330-020-07519-9

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