Abstract
Original language | English |
---|---|
Journal | Med. Oncol. |
Volume | 37 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- Artificial intelligence
- Breast cancer
- Breast imaging
- Breast MRI
- Diffusion-weighted imaging
- Oncology
- Radiology
- Vacuum-assisted breast biopsy
- gadolinium chelate
- adult
- aged
- Article
- artificial intelligence
- atypical ductal hyperplasia
- breast biopsy
- breast cancer
- breast carcinoma
- breast discharge
- breast fibrosis
- breast tumor
- cancer center
- cancer diagnosis
- diagnostic accuracy
- diagnostic test accuracy study
- diffusion weighted imaging
- female
- follow up
- human
- human tissue
- intraductal carcinoma
- invasive carcinoma
- major clinical study
- mammography
- nuclear magnetic resonance imaging
- predictive value
- priority journal
- retrospective study
- sensitivity and specificity
- tertiary care center
- vacuum
- adolescent
- breast
- diagnostic imaging
- image guided biopsy
- middle aged
- pathology
- very elderly
- young adult
- Adolescent
- Adult
- Aged
- Aged, 80 and over
- Artificial Intelligence
- Breast
- Breast Neoplasms
- Diffusion Magnetic Resonance Imaging
- Female
- Humans
- Image-Guided Biopsy
- Magnetic Resonance Imaging
- Middle Aged
- Retrospective Studies
- Sensitivity and Specificity
- Tertiary Care Centers
- Vacuum
- Young Adult
Fingerprint Dive into the research topics of 'MRI-guided vacuum-assisted breast biopsy: experience of a single tertiary referral cancer centre and prospects for the future: Medical Oncology'. Together they form a unique fingerprint.
Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS
MRI-guided vacuum-assisted breast biopsy: experience of a single tertiary referral cancer centre and prospects for the future : Medical Oncology. / Penco, S.; Rotili, A.; Pesapane, F.; Trentin, C.; Dominelli, V.; Faggian, A.; Farina, M.; Marinucci, I.; Bozzini, A.; Pizzamiglio, M.; Ierardi, A.M.; Cassano, E.
In: Med. Oncol., Vol. 37, No. 5, 2020.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - MRI-guided vacuum-assisted breast biopsy: experience of a single tertiary referral cancer centre and prospects for the future
T2 - Medical Oncology
AU - Penco, S.
AU - Rotili, A.
AU - Pesapane, F.
AU - Trentin, C.
AU - Dominelli, V.
AU - Faggian, A.
AU - Farina, M.
AU - Marinucci, I.
AU - Bozzini, A.
AU - Pizzamiglio, M.
AU - Ierardi, A.M.
AU - Cassano, E.
N1 - Cited By :2 Export Date: 4 March 2021 CODEN: MONCE Correspondence Address: Pesapane, F.; Breast Imaging Division, Via Giuseppe Ripamonti, 435, Italy; email: filippo.pesapane@ieo.it Tradenames: Optima MR450w, GE Healthcare, United States Manufacturers: GE Healthcare, United States Funding details: 5 × 1000 Funding text 1: This work was partially supported by the Italian Ministry of Health with Ricerca Corrente and 5 × 1000 funds. References: Kuhl, C.K., Schrading, S., Bieling, H.B., Wardelmann, E., Leutner, C.C., Koenig, R., MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study (2007) Lancet, 370 (9586), pp. 485-492; Menell, J.H., Morris, E.A., Dershaw, D.D., Abramson, A.F., Brogi, E., Liberman, L., Determination of the presence and extent of pure ductal carcinoma in situ by mammography and magnetic resonance imaging (2005) Breast J, 11 (6), pp. 382-390; Peters, N.H., Borel Rinkes, I.H., Zuithoff, N.P., Mali, W.P., Moons, K.G., Peeters, P.H., Meta-analysis of MR imaging in the diagnosis of breast lesions (2008) Radiology, 246 (1), pp. 116-124; Spick, C., Baltzer, P.A., Diagnostic utility of second-look US for breast lesions identified at MR imaging: systematic review and meta-analysis (2014) Radiology, 273 (2), pp. 401-409; Abe, H., Schmidt, R.A., Shah, R.N., Shimauchi, A., Kulkarni, K., Sennett, C.A., MR-directed ("Second-Look") ultrasound examination for breast lesions detected initially on MRI: MR and sonographic findings (2010) AJR Am J Roentgenol, 194 (2), pp. 370-377; Sardanelli, F., Boetes, C., Borisch, B., Decker, T., Federico, M., Gilbert, F.J., Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group (2010) Eur J Cancer, 46 (8), pp. 1296-1316; Mann, R.M., Balleyguier, C., Baltzer, P.A., Bick, U., Colin, C., Cornford, E., Breast MRI: EUSOBI recommendations for women's information (2015) Eur Radiol, 25 (12), pp. 3669-3678; Rauch, G.M., Dogan, B.E., Smith, T.B., Liu, P., Yang, W.T., Outcome analysis of 9-gauge MRI-guided vacuum-assisted core needle breast biopsies (2012) AJR Am J Roentgenol, 198 (2), pp. 292-299; Imschweiler, T., Haueisen, H., Kampmann, G., Rageth, L., Seifert, B., Rageth, C., MRI-guided vacuum-assisted breast biopsy: comparison with stereotactically guided and ultrasound-guided techniques (2014) Eur Radiol, 24 (1), pp. 128-135; Perlet, C., Heywang-Kobrunner, S.H., Heinig, A., Sittek, H., Casselman, J., Anderson, I., Magnetic resonance-guided, vacuum-assisted breast biopsy: results from a European multicenter study of 538 lesions (2006) Cancer, 106 (5), pp. 982-990; McGrath, A.L., Price, E.R., Eby, P.R., Rahbar, H., MRI-guided breast interventions (2017) J Magn Reson Imaging, 46 (3), pp. 631-645; Spick, C., Schernthaner, M., Pinker, K., Kapetas, P., Bernathova, M., Polanec, S.H., MR-guided vacuum-assisted breast biopsy of MRI-only lesions: a single center experience (2016) Eur Radiol, 26 (11), pp. 3908-3916; Berger, N., Varga, Z., Frauenfelder, T., Boss, A., MRI-guided breast vacuum biopsy: Localization of the lesion without contrast-agent application using diffusion-weighted imaging (2017) Magn Reson Imaging, 38, pp. 1-5; Spick, C., Pinker-Domenig, K., Rudas, M., Helbich, T.H., Baltzer, P.A., MRI-only lesions: application of diffusion-weighted imaging obviates unnecessary MR-guided breast biopsies (2014) Eur Radiol, 24 (6), pp. 1204-1210; Kuhl, C.K., Abbreviated magnetic resonance imaging (MRI) for breast cancer screening: rationale, concept, and transfer to clinical practice (2019) Annu Rev Med, 70, pp. 501-519; McDonald, R.J., McDonald, J.S., Kallmes, D.F., Jentoft, M.E., Paolini, M.A., Murray, D.L., Gadolinium deposition in human brain tissues after contrast-enhanced mr imaging in adult patients without intracranial abnormalities (2017) Radiology; Mithal, L.B., Patel, P.S., Mithal, D., Palac, H.L., Rozenfeld, M.N., Use of gadolinium-based magnetic resonance imaging contrast agents and awareness of brain gadolinium deposition among pediatric providers in North America (2017) Pediatr Radiol, 47 (6), pp. 657-664; Baltzer, P.A.T., Bickel, H., Spick, C., Wengert, G., Woitek, R., Kapetas, P., Potential of noncontrast magnetic resonance imaging with diffusion-weighted imaging in characterization of breast lesions: intraindividual comparison with dynamic contrast-enhanced magnetic resonance imaging (2018) Invest Radiol, 53 (4), pp. 229-235; Rotili, A., Trimboli, R.M., Penco, S., Pesapane, F., Tantrige, P., Cassano, E., Double reading of diffusion-weighted magnetic resonance imaging for breast cancer detection (2020) Breast Cancer Res Treat; Yamada, T., Kanemaki, Y., Okamoto, S., Nakajima, Y., Comparison of detectability of breast cancer by abbreviated breast MRI based on diffusion-weighted images and postcontrast MRI (2018) Jpn J Radiol, 36 (5), pp. 331-339; Barentsz, M.W., Taviani, V., Chang, J.M., Ikeda, D.M., Miyake, K.K., Banerjee, S., Assessment of tumor morphology on diffusion-weighted (DWI) breast MRI: diagnostic value of reduced field of view DWI (2015) J Magn Reson Imaging, 42 (6), pp. 1656-1665; Baltzer, P.A., Benndorf, M., Dietzel, M., Gajda, M., Camara, O., Kaiser, W.A., Sensitivity and specificity of unenhanced MR mammography (DWI combined with T2-weighted TSE imaging, ueMRM) for the differentiation of mass lesions (2010) Eur Radiol, 20 (5), pp. 1101-1110; Lakhani, P., Prater, A.B., Hutson, R.K., Andriole, K.P., Dreyer, K.J., Morey, J., Machine learning in radiology: applications beyond image interpretation (2018) J Am Coll Radiol, 15 (2), pp. 350-359; Pesapane, F., Volonte, C., Codari, M., Sardanelli, F., Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States (2018) Insights Imaging; Russell, S., Bohannon, J., Artificial intelligence. Fears of an AI pioneer (2015) Science, 349 (6245), p. 252; Pesapane, F., Codari, M., Sardanelli, F., Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine (2018) Eur Radiol Exp, 2 (1), p. 35; Pizzini, F.B., Pesapane, F., Niessen, W., Geerts-Ossevoort, L., Broeckx, N., ESMRMB round table report on "can europe lead in machine learning of MRI-data?" (2020) MAGMA; Nance, J.W., Jr., Meenan, C., Nagy, P.G., The future of the radiology information system (2013) AJR Am J Roentgenol, 200 (5), pp. 1064-1070; Chaudhary, K., Poirion, O.B., Lu, L., Garmire, L.X., Deep learning-based multi-omics integration robustly predicts survival in liver cancer (2018) Clin Cancer Res, 24 (6), pp. 1248-1259; Abajian, A., Murali, N., Savic, L.J., Laage-Gaupp, F.M., Nezami, N., Duncan, J.S., Predicting treatment response to intra-arterial therapies for hepatocellular carcinoma with the use of supervised machine learning-an artificial intelligence concept (2018) J Vasc Interv Radiol; El-Sayed, M.E., Rakha, E.A., Reed, J., Lee, A.H., Evans, A.J., Ellis, I.O., Predictive value of needle core biopsy diagnoses of lesions of uncertain malignant potential (B3) in abnormalities detected by mammographic screening (2008) Histopathology, 53 (6), pp. 650-657; McKinney, S.M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., International evaluation of an AI system for breast cancer screening (2020) Nature., 577 (7788), pp. 89-94; Codari, M., Schiaffino, S., Sardanelli, F., Trimboli, R.M., Artificial intelligence for breast MRI in 2008–2018: a systematic mapping review (2019) AJR Am J Roentgenol, 212 (2), pp. 280-292; Lee, C.H., Dershaw, D.D., Kopans, D., Evans, P., Monsees, B., Monticciolo, D., Breast cancer screening with imaging: recommendations from the Society of Breast Imaging and the ACR on the use of mammography, breast MRI, breast ultrasound, and other technologies for the detection of clinically occult breast cancer (2010) J Am Coll Radiol, 7 (1), pp. 18-27; Saslow, D., Boetes, C., Burke, W., Harms, S., Leach, M.O., Lehman, C.D., American Cancer Society guidelines for breast screening with MRI as an adjunct to mammography (2007) CA Cancer J Clin, 57 (2), pp. 75-89; (2019), https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems, American College of Radiology (ACR). ACR reporting and data systems (RADS) 2019., Accessed 1 Mar 2020; Kuhl, C., The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice (2007) Radiology, 244 (2), pp. 356-378; Mann, R.M., Kuhl, C.K., Kinkel, K., Boetes, C., Breast MRI: guidelines from the European Society of Breast Imaging (2008) Eur Radiol, 18 (7), pp. 1307-1318; Liberman, L., Percutaneous image-guided core breast biopsy (2002) Radiol Clin N Am, 40 (3), pp. 483-500; Malhaire, C., El Khoury, C., Thibault, F., Athanasiou, A., Petrow, P., Ollivier, L., Vacuum-assisted biopsies under MR guidance: results of 72 procedures (2010) Eur Radiol, 20 (7), pp. 1554-1562; Brennan, S.B., Sung, J.S., Dershaw, D.D., Liberman, L., Morris, E.A., Cancellation of MR imaging-guided breast biopsy due to lesion nonvisualization: frequency and follow-up (2011) Radiology, 261 (1), pp. 92-99; Mahoney, M.C., Newell, M.S., Screening MR imaging versus screening ultrasound: pros and cons (2013) Magn Reson Imaging Clin N Am, 21 (3), pp. 495-508; Le Bihan, D., Intravoxel incoherent motion perfusion MR imaging: a wake-up call (2008) Radiology, 249 (3), pp. 748-752; Pesapane, F., Patella, F., Fumarola, E.M., Panella, S., Ierardi, A.M., Pompili, G.G., Intravoxel incoherent motion (IVIM) diffusion weighted imaging (DWI) in the periferic prostate cancer detection and stratification (2017) Med Oncol, 34 (3), p. 35; Sardanelli, F., Carbonaro, L.A., Montemezzi, S., Cavedon, C., Trimboli, R.M., Clinical breast MR using MRS or DWI: who is the winner? (2016) Front Oncol, 6, p. 217; Bickelhaupt, S., Paech, D., Kickingereder, P., Steudle, F., Lederer, W., Daniel, H., Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography (2017) J Magn Reson Imaging, 46 (2), pp. 604-616; Bickelhaupt, S., Tesdorff, J., Laun, F.B., Kuder, T.A., Lederer, W., Teiner, S., Independent value of image fusion in unenhanced breast MRI using diffusion-weighted and morphological T2-weighted images for lesion characterization in patients with recently detected BI-RADS 4/5 x-ray mammography findings (2017) Eur Radiol, 27 (2), pp. 562-569; Pesapane, F., How scientific mobility can help current and future radiology research: a radiology trainee's perspective (2019) Insights Imaging, 10 (1), p. 85; Kuhl, C., Weigel, S., Schrading, S., Arand, B., Bieling, H., Konig, R., Prospective multicenter cohort study to refine management recommendations for women at elevated familial risk of breast cancer: the EVA trial (2010) J Clin Oncol, 28 (9), pp. 1450-1457; Sardanelli, F., Podo, F., D'Agnolo, G., Verdecchia, A., Santaquilani, M., Musumeci, R., Multicenter comparative multimodality surveillance of women at genetic-familial high risk for breast cancer (HIBCRIT study): interim results (2007) Radiology, 242 (3), pp. 698-715
PY - 2020
Y1 - 2020
N2 - MRI-guided vacuum-assisted breast biopsy (VABB) is used for suspicious breast cancer (BC) lesions which are detectable only with MRI: because the high sensitivity but limited specificity of breast MRI it is a fundamental tool in breast imaging divisions. We analyse our experience of MRI-guided VABB and critically discuss the potentialities of diffusion-weighted imaging (DWI) and artificial intelligence (AI) in this matter. We retrospectively analysed a population of consecutive women underwent VABB at our tertiary referral BC centre from 01/2011 to 01/2019. Reference standard was histological diagnosis or at least 1-year negative follow-up. McNemar, Mann–Whitney and χ2 tests at 95% level of significance were used as statistical exams. 217 women (mean age = 52, 18–72 years) underwent MRI-guided VABB; 11 were excluded and 208 MRI-guided VABB lesions were performed: 34/208 invasive carcinomas, 32/208 DCIS, 8/208 LCIS, 3/208 high-risk lesions and 131/208 benign lesions were reported. Accuracy of MRI-guided VABB was 97%. The predictive features for malignancy were mass with irregular shape (OR 8.4; 95% CI 0.59–31.6), size of the lesion (OR 4.4; 95% CI 1.69–9.7) and mass with irregular/spiculated margins (OR 5.4; 95% CI 6.8–31.1). Six-month follow-up showed 4 false-negative cases (1.9%). Invasive BC showed a statistically significant higher hyperintense signal at DWI compared to benign lesions (p = 0.03). No major complications occurred. MR-guided VABB showed high accuracy. Benign-concordant lesions should be followed up with breast MRI in 6–12 months due to the risk of false-negative results. DWI and AI applications showed potential benefit as support tools for radiologists. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
AB - MRI-guided vacuum-assisted breast biopsy (VABB) is used for suspicious breast cancer (BC) lesions which are detectable only with MRI: because the high sensitivity but limited specificity of breast MRI it is a fundamental tool in breast imaging divisions. We analyse our experience of MRI-guided VABB and critically discuss the potentialities of diffusion-weighted imaging (DWI) and artificial intelligence (AI) in this matter. We retrospectively analysed a population of consecutive women underwent VABB at our tertiary referral BC centre from 01/2011 to 01/2019. Reference standard was histological diagnosis or at least 1-year negative follow-up. McNemar, Mann–Whitney and χ2 tests at 95% level of significance were used as statistical exams. 217 women (mean age = 52, 18–72 years) underwent MRI-guided VABB; 11 were excluded and 208 MRI-guided VABB lesions were performed: 34/208 invasive carcinomas, 32/208 DCIS, 8/208 LCIS, 3/208 high-risk lesions and 131/208 benign lesions were reported. Accuracy of MRI-guided VABB was 97%. The predictive features for malignancy were mass with irregular shape (OR 8.4; 95% CI 0.59–31.6), size of the lesion (OR 4.4; 95% CI 1.69–9.7) and mass with irregular/spiculated margins (OR 5.4; 95% CI 6.8–31.1). Six-month follow-up showed 4 false-negative cases (1.9%). Invasive BC showed a statistically significant higher hyperintense signal at DWI compared to benign lesions (p = 0.03). No major complications occurred. MR-guided VABB showed high accuracy. Benign-concordant lesions should be followed up with breast MRI in 6–12 months due to the risk of false-negative results. DWI and AI applications showed potential benefit as support tools for radiologists. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
KW - Artificial intelligence
KW - Breast cancer
KW - Breast imaging
KW - Breast MRI
KW - Diffusion-weighted imaging
KW - Oncology
KW - Radiology
KW - Vacuum-assisted breast biopsy
KW - gadolinium chelate
KW - adult
KW - aged
KW - Article
KW - artificial intelligence
KW - atypical ductal hyperplasia
KW - breast biopsy
KW - breast cancer
KW - breast carcinoma
KW - breast discharge
KW - breast fibrosis
KW - breast tumor
KW - cancer center
KW - cancer diagnosis
KW - diagnostic accuracy
KW - diagnostic test accuracy study
KW - diffusion weighted imaging
KW - female
KW - follow up
KW - human
KW - human tissue
KW - intraductal carcinoma
KW - invasive carcinoma
KW - major clinical study
KW - mammography
KW - nuclear magnetic resonance imaging
KW - predictive value
KW - priority journal
KW - retrospective study
KW - sensitivity and specificity
KW - tertiary care center
KW - vacuum
KW - adolescent
KW - breast
KW - diagnostic imaging
KW - image guided biopsy
KW - middle aged
KW - pathology
KW - very elderly
KW - young adult
KW - Adolescent
KW - Adult
KW - Aged
KW - Aged, 80 and over
KW - Artificial Intelligence
KW - Breast
KW - Breast Neoplasms
KW - Diffusion Magnetic Resonance Imaging
KW - Female
KW - Humans
KW - Image-Guided Biopsy
KW - Magnetic Resonance Imaging
KW - Middle Aged
KW - Retrospective Studies
KW - Sensitivity and Specificity
KW - Tertiary Care Centers
KW - Vacuum
KW - Young Adult
U2 - 10.1007/s12032-020-01358-w
DO - 10.1007/s12032-020-01358-w
M3 - Article
VL - 37
JO - Med. Oncol.
JF - Med. Oncol.
SN - 1357-0560
IS - 5
ER -