The efficiency of volumetric apparent diffusion coefficient histogram analysis in breast papillary neoplasms: ADC histogram in breast papillary neoplasm

Mustafa Orhan Nalbant; Aysegul Akdogan  Gemici; Mehmet  Karadag; Ercan  Inci

doi:10.28982/josam.7715

Authors

Mustafa Orhan Nalbant Department of Radiology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Turkey https://orcid.org/0000-0002-5277-9111
Aysegul Akdogan Gemici Department of Radiology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Turkey https://orcid.org/0000-0002-7707-1849
Mehmet Karadag Department of Radiology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Turkey https://orcid.org/0000-0002-7646-7200
Ercan Inci Department of Radiology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, Turkey https://orcid.org/0000-0002-3791-2471

DOI:

https://doi.org/10.28982/josam.7715

Keywords:

Apparent diffusion coefficient, magnetic resonance imaging, papillary neoplasia, volumetric histogram analysis

Abstract

Background/Aim: Papillary neoplasia encompasses both malignant and benign lesions, and core needle biopsy (CNB) is crucial in their diagnosis. Histological findings determine their management. Here we compare volumetric apparent diffusion coefficient (ADC) histogram analysis of carcinomas and benign pathologies identified by histopathology from excisional biopsies.

Methods: This retrospective study included 524 patients who underwent breast magnetic resonance imaging (MRI) for a suspicious breast mass from January 2018 to October 2022. Patients with benign lesions, incompatible ultrasound-guided CNB results with papillary neoplasia, and those with MRI exams insufficient for diagnosis due to motion artifacts were excluded. After applying the exclusion criteria, the study included 48 patients (average aged 61.5 (14.8) years; range, 31 to 72 years). After excisional biopsies, 30 benign lesions and 18 carcinomas were identified. MRI was acquired at 1.5 T (Verio; Siemens Medical Solutions, Erlangen, Germany), and the b-values for diffusion-weighted imaging were calculated at 1000 s/mm². Histogram parameters were computed. Receiver operating characteristic (ROC) curve analysis was performed to investigate diagnostic accuracy, evaluate histogram analysis performance, and determine threshold values.

Results: The ADCmin, ADCmean, ADCmax, and all ADC value percentiles were significantly lower in the carcinoma group than in the benign group (P<0.001). The variance, skewness, and kurtosis were higher in the carcinoma group. ADCmax had the highest area under the curve (AUC: 0.985; cut-off 1.247 × 10^-3 mm²/s; sensitivity 86%, and specificity 92%), followed by ADCmean (AUC: 0.950; cut-off 0.903 × 10^-3 mm²/s; sensitivity 94%, and specificity 96%).

Conclusion: Volumetric ADC histogram analysis of papillary neoplasia at higher b-values can be an imaging marker to detect carcinoma and quantitatively reveal the lesions’ diffusion characteristics.

Downloads

Download data is not yet available.

References

Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S, et al. Cree IA; WHO Classification of Tumours Editorial Board. The 2019 World Health Organization classification of tumors of the breast. Histopathology. 2020;77(2):181-5. doi: 10.1111/his.14091. DOI: https://doi.org/10.1111/his.14091

Rakha EA, Ellis IO. Diagnostic challenges in papillary lesions of the breast. Pathology. 2018;50(1):100-10. doi: 10.1016/j.pathol.2017.10.005. DOI: https://doi.org/10.1016/j.pathol.2017.10.005

Rageth CJ, O'Flynn EAM, Pinker K, Kubik-Huch RA, Mundinger A, Decker T, et al. Second International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions). Breast Cancer Res Treat. 2019;174(2):279-96. doi: 10.1007/s10549-018-05071-1. DOI: https://doi.org/10.1007/s10549-018-05071-1

Richter-Ehrenstein C, Maak K, Röger S, Ehrenstein T. Lesions of "uncertain malignant potential" in the breast (B3) identified with mammography screening. BMC Cancer. 2018;18(1):829. doi: 10.1186/s12885-018-4742-6. DOI: https://doi.org/10.1186/s12885-018-4742-6

Nakhlis F. How Do We Approach Benign Proliferative Lesions? Curr Oncol Rep. 2018;20(4):34. doi: 10.1007/s11912-018-0682-1. DOI: https://doi.org/10.1007/s11912-018-0682-1

Heywang-Köbrunner SH, Nährig J, Hacker A, Sedlacek S, Höfler H. B3 Lesions: Radiological Assessment and Multi-Disciplinary Aspects. Breast Care (Basel). 2010;5(4):209-17. doi: 10.1159/000319326. DOI: https://doi.org/10.1159/000319326

Linda A, Zuiani C, Bazzocchi M, Furlan A, Londero V. Borderline breast lesions diagnosed at core needle biopsy: can magnetic resonance mammography rule out associated malignancy? Preliminary results based on 79 surgically excised lesions. Breast. 2008;17(2):125-31. doi: 10.1016/j.breast.2007.11.002. DOI: https://doi.org/10.1016/j.breast.2007.11.002

Pediconi F, Padula S, Dominelli V, Luciani M, Telesca M, Casali V, et al. Role of breast MR imaging for predicting malignancy of histologically borderline lesions diagnosed at core needle biopsy: prospective evaluation. Radiology. 2010;257(3):653-61. doi: 10.1148/radiol.10100732. DOI: https://doi.org/10.1148/radiol.10100732

Ei Khouli RH, Jacobs MA, Mezban SD, Huang P, Kamel IR, Macura KJ, et al. Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging. Radiology. 2010;256(1):64-73. doi: 10.1148/radiol.10091367. DOI: https://doi.org/10.1148/radiol.10091367

Guo Y, Cai YQ, Cai ZL, Gao YG, An NY, Ma L, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging. 2002;16(2):172-8. doi: 10.1002/jmri.10140. DOI: https://doi.org/10.1002/jmri.10140

Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C. Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol. 2007;17(10):2646-55. doi: 10.1007/s00330-007-0621-2. DOI: https://doi.org/10.1007/s00330-007-0621-2

Partridge SC, Demartini WB, Kurland BF, Eby PR, White SW, Lehman CD. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010;31(3):562-70. doi: 10.1002/jmri.22078. DOI: https://doi.org/10.1002/jmri.22078

Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol. 2007;188(6):1622-35. doi: 10.2214/AJR.06.1403. DOI: https://doi.org/10.2214/AJR.06.1403

Surov A, Meyer HJ, Wienke A. Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget. 2017;8(35):59492-9. doi: 10.18632/oncotarget.17752. DOI: https://doi.org/10.18632/oncotarget.17752

Meyer HJ, Leifels L, Hamerla G, Höhn AK, Surov A. ADC-histogram analysis in head and neck squamous cell carcinoma. Associations with different histopathological features including expression of EGFR, VEGF, HIF-1α, Her 2 and p53. A preliminary study. Magn Reson Imaging. 2018;54:214-7. doi: 10.1016/j.mri.2018.07.013. DOI: https://doi.org/10.1016/j.mri.2018.07.013

Iima M, Le Bihan D. Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future. Radiology. 2016;278(1):13-32. doi:10.1148/radiol.2015150244. DOI: https://doi.org/10.1148/radiol.2015150244

Choi MH, Oh SN, Rha SE, Choi JI, Lee SH, Jang HS, et al. Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer. J Magn Reson Imaging. 2016;44(1):212-20. doi: 10.1002/jmri.25117. DOI: https://doi.org/10.1002/jmri.25117

Surov A, Ginat DT, Lim T, Cabada T, Baskan O, Schob S, et al. Histogram Analysis Parameters Apparent Diffusion Coefficient for Distinguishing High and Low-Grade Meningiomas: A Multicenter Study. Transl Oncol. 2018;11(5):1074-9. doi: 10.1016/j.tranon.2018.06.010. DOI: https://doi.org/10.1016/j.tranon.2018.06.010

Thust SC, Maynard JA, Benenati M, Wastling SJ, Mancini L, Jaunmuktane Z, et al. Regional and Volumetric Parameters for Diffusion-Weighted WHO Grade II and III Glioma Genotyping: A Method Comparison. AJNR Am J Neuroradiol. 2021;42(3):441-7. doi: 10.3174/ajnr.A6965. DOI: https://doi.org/10.3174/ajnr.A6965

Ma X, Shen M, He Y, Ma F, Liu J, Zhang G, et al. The role of volumetric ADC histogram analysis in preoperatively evaluating the tumour subtype and grade of endometrial cancer. Eur J Radiol. 2021;140:109745. doi: 10.1016/j.ejrad.2021.109745. DOI: https://doi.org/10.1016/j.ejrad.2021.109745

Li S, Liang P, Wang Y, Feng C, Shen Y, Hu X, et al. Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer. Abdom Radiol (NY). 2021;46(9):4301-10. doi: 10.1007/s00261-021-03091-y. DOI: https://doi.org/10.1007/s00261-021-03091-y

Muehlematter UJ, Mannil M, Becker AS, Vokinger KN, Finkenstaedt T, Osterhoff G, et al. Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning. Eur Radiol. 2019;29(5):2207-17. doi: 10.1007/s00330-018-5846-8. DOI: https://doi.org/10.1007/s00330-018-5846-8

Tsili AC, Astrakas LG, Goussia AC, Sofikitis N, Argyropoulou MI. Volumetric apparent diffusion coefficient histogram analysis of the testes in nonobstructive azoospermia: a noninvasive fingerprint of impaired spermatogenesis? Eur Radiol. 2022;32(11):7522-31. doi: 10.1007/s00330-022-08817-0. DOI: https://doi.org/10.1007/s00330-022-08817-0

Newitt DC, Amouzandeh G, Partridge SC, Marques HS, Herman BA, Ross BD, et al. Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial. Tomography. 2020;6(2):177-85. doi: 10.18383/j.tom.2020.00008. DOI: https://doi.org/10.18383/j.tom.2020.00008

Guo Y, Kong QC, Li LQ, Tang WJ, Zhang WL, Ning GY, et al. Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index. Biomed Res Int. 2021;2021:4970265. doi: 10.1155/2021/4970265. DOI: https://doi.org/10.1155/2021/4970265

Tagliati C, Ercolani P, Marconi E, Simonetti BF, Giuseppetti GM, Giovagnoni A. Apparent diffusion coefficient value in breast papillary lesions without atypia at core needle biopsy. Clin Imaging. 2020;59(2):148-53. doi: 10.1016/j.clinimag.2019.10.010. Epub 2019 November 20. PMID: 31821971. DOI: https://doi.org/10.1016/j.clinimag.2019.10.010

Lv W, Zheng D, Guan W, Wu P. Contribution of Diffusion-Weighted Imaging and ADC Values to Papillary Breast Lesions. Front Oncol. 2022;12:911790. doi: 10.3389/fonc.2022.911790. DOI: https://doi.org/10.3389/fonc.2022.911790

Nadrljanski MM, Milosevic ZC. Relative apparent diffusion coefficient (rADC) in breast lesions of uncertain malignant potential (B3 lesions) and pathologically proven breast carcinoma (B5 lesions) following breast biopsy. Eur J Radiol. 2020;124:108854. doi: 10.1016/j.ejrad.2020.108854. DOI: https://doi.org/10.1016/j.ejrad.2020.108854

Cheeney S, Rahbar H, Dontchos BN, Javid SH, Rendi MH, Partridge SC. Apparent diffusion coefficient values may help predict which MRI-detected high-risk breast lesions will upgrade at surgical excision. J Magn Reson Imaging. 2017;46(4):1028-36. doi: 10.1002/jmri.25656. DOI: https://doi.org/10.1002/jmri.25656

Tang W, Chen L, Jin Z, Liang Y, Zuo W, Wei X, et al. The diagnostic dilemma with the plateau pattern of the time-intensity curve: can the relative apparent diffusion coefficient (rADC) optimise the ADC parameter for differentiating breast lesions? Clin Radiol. 2021;76(9):688-95. doi: 10.1016/j.crad.2021.04.015. DOI: https://doi.org/10.1016/j.crad.2021.04.015