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Chen K, Yu C, Pan J, Xu Y, Luo Y, Yang T, Yang X, Xie L, Zhang J, Zhuo R. Prediction of the Nottingham prognostic index and molecular subtypes of breast cancer through multimodal magnetic resonance imaging. Magn Reson Imaging 2024; 108:168-175. [PMID: 38408689 DOI: 10.1016/j.mri.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/19/2024] [Accepted: 02/21/2024] [Indexed: 02/28/2024]
Abstract
PURPOSE To explore the ability of intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and background parenchyma enhancement (BPE) to predict the Nottingham prognostic index (NPI) and molecular subtypes of breast cancer (BC). MATERIALS AND METHODS In this study, 93 patients with BC were included, and they all underwent DKI, IVIM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations. The corresponding mean kurtosis value (MK), pure diffusion (MD), perfusion fraction (f), pseudo diffusion coefficient (D*), true diffusion coefficient (D), and BPE were measured. We used logistic regression analysis to investigate the relevance between the NPI, molecular subtypes and variables. The diagnostic efficacy was analyzed using receiver operating characteristic curves (ROC). RESULTS The MD and D values of the high-level NPI group were significantly lower than those of the low-level NPI group (p < 0.01), and the f value of the high-level NPI group was obviously higher than that of low-level NPI group (p < 0.001). The area under curve (AUC) of the combined model (f + D) was 0.824. Comparing with non-Luminal subtypes, the Luminal subtypes showed obviously lower MK, f and D*, and the AUC of the combined model (MK + f + D*) was 0.785. In comparison to other subtypes, the MK and D* values of triple-negative subtype were higher than other subtypes, and the combined model (MK + D*) represented an AUC of 0.865. CONCLUSION The quantitative parameters of DKI and IVIM have vital value in predicting the NPI and molecular subtypes of BC, while BPE could not provide additional information. Besides, these combined models can obviously improve the prediction performance.
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Affiliation(s)
- Kewei Chen
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China; Department of Radiology, Women and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China
| | - Chengxin Yu
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China.
| | - Junlong Pan
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Yaqia Xu
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Yuqing Luo
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Ting Yang
- Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China
| | - Xiaoling Yang
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Lisi Xie
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Jing Zhang
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
| | - Renfeng Zhuo
- Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China
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Tunlayadechanont P, Panyaping T, Chansakul T, Hirunpat P, Kampaengtip A. Intravoxel incoherent motion for differentiating residual/recurrent tumor from post-treatment change in patients with high-grade glioma. Neuroradiol J 2023; 36:657-664. [PMID: 37105183 PMCID: PMC10649527 DOI: 10.1177/19714009231173108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023] Open
Abstract
PURPOSE To investigate the diagnostic value of f derived from IVIM technique and to correlate it with rCBV derived from DSC for the differentiation of residual/recurrent tumor from post-treatment change in patients with high-grade glioma. MATERIALS AND METHODS Patients who underwent MR imaging with IVIM and DSC studies for evaluation of high-grade glioma after standard treatment were enrolled in this retrospective study. For qualitative analysis, the f and rCBV maps were interpreted as hypoperfused or hyperperfused in each parameter. Quantitative analysis was performed using ROI analysis in f and rCBV parameters. The lesions were divided into residual/recurrent tumor and post-treatment change groups. RESULTS Nineteen patients with high-grade glioma were included. In qualitative analysis, the f-map shows higher sensitivity (100.0%) than rCBV map (92.3%), while the rCBV map shows higher specificity (100.0%) than the f-map (83.3%). In quantitative analysis, the optimal cutoff values of 1.19 for f and 1.06 for rCBV are shown to provide high diagnostic value with high sensitivity (91.7%) for both parameters but slightly higher specificity of rCBV (85.7%) than f (71.4%). The correlation between f and rCBV was good with ICC of 0.810. CONCLUSION The f value measured by IVIM technique, non-contrast perfusion technique, has high diagnostic performance and potential to be an alternative method to CBV measured by DSC for differentiation between residual/recurrent tumor and post-treatment change in patients with high-grade glioma.
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Affiliation(s)
- Padcha Tunlayadechanont
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Theeraphol Panyaping
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Thanissara Chansakul
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Pornrujee Hirunpat
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Adun Kampaengtip
- Division of Neurological Radiology, Department of Diagnostic and Therapeutic Radiology, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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Nissan N, Anaby D, Mahameed G, Bauer E, Moss Massasa EE, Menes T, Agassi R, Brodsky A, Grimm R, Nickel MD, Roccia E, Sklair-Levy M. Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement. Eur Radiol 2023; 33:8122-8131. [PMID: 37278853 DOI: 10.1007/s00330-023-09805-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 03/31/2023] [Accepted: 04/27/2023] [Indexed: 06/07/2023]
Abstract
OBJECTIVE To investigate the utility of ultrafast dynamic-contrast-enhanced (DCE) MRI in visualization and quantitative characterization of pregnancy-associated breast cancer (PABC) and its differentiation from background-parenchymal-enhancement (BPE) among lactating patients. MATERIALS AND METHODS Twenty-nine lactating participants, including 10 PABC patients and 19 healthy controls, were scanned on 3-T MRI using a conventional DCE protocol interleaved with a golden-angle radial sparse parallel (GRASP) ultrafast sequence for the initial phase. The timing of the visualization of PABC lesions was compared to lactational BPE. Contrast-noise ratio (CNR) was compared between the ultrafast and conventional DCE sequences. The differences in each group's ultrafast-derived kinetic parameters including maximal slope (MS), time to enhancement (TTE), and area under the curve (AUC) were statistically examined using the Mann-Whitney test and receiver operator characteristic (ROC) curve analysis. RESULTS On ultrafast MRI, breast cancer lesions enhanced earlier than BPE (p < 0.0001), enabling breast cancer visualization freed from lactation BPE. A higher CNR was found for ultrafast acquisitions vs. conventional DCE (p < 0.05). Significant differences in AUC, MS, and TTE values were found between the tumor and BPE (p < 0.05), with ROC-derived AUC of 0.86 ± 0.06, 0.82 ± 0.07, and 0.68 ± 0.08, respectively. The BPE grades of the lactating PABC patients were reduced as compared with the healthy lactating controls (p < 0.005). CONCLUSION Ultrafast DCE MRI allows BPE-free visualization of lesions, improved tumor conspicuity, and kinetic quantification of breast cancer during lactation. Implementation of this method may assist in the utilization of breast MRI for lactating patients. CLINICAL RELEVANCE The ultrafast sequence appears to be superior to conventional DCE MRI in the challenging evaluation of the lactating breast. Thus, supporting its possible utilization in the setting of high-risk screening during lactation and the diagnostic workup of PABC. KEY POINTS • Differences in the enhancement slope of cancer relative to BPE allowed the optimal visualization of PABC lesions on mid-acquisitions of ultrafast DCE, in which the tumor enhanced prior to the background parenchyma. • The conspicuity of PABC lesions on top of the lactation-related BPE was increased using an ultrafast sequence as compared with conventional DCE MRI. • Ultrafast-derived maps provided further characterization and parametric contrast between PABC lesions and lactation-related BPE.
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Affiliation(s)
- Noam Nissan
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel.
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Gazal Mahameed
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ethan Bauer
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Efi Efraim Moss Massasa
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
| | - Tehillah Menes
- Department of General Surgery, Sheba Medical Center, Ramat Gan, Israel
| | - Ravit Agassi
- Department of General Surgery, Soroka Medical Center, Beersheba, Israel
| | - Asia Brodsky
- Department of General Surgery, Bnei Zion Medical Center, Haifa, Israel
| | - Robert Grimm
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Elisa Roccia
- MR Scientific Marketing, Siemens Healthcare GmbH, Erlangen, Germany
| | - Miri Sklair-Levy
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 St. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Nissan N, Massasa EEM, Bauer E, Halshtok-Neiman O, Shalmon A, Gotlieb M, Faermann R, Samoocha D, Yagil Y, Ziv-Baran T, Anaby D, Sklair-Levy M. MRI can accurately diagnose breast cancer during lactation. Eur Radiol 2023; 33:2935-2944. [PMID: 36348090 DOI: 10.1007/s00330-022-09234-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/27/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To test the diagnostic performance of breast dynamic contrast-enhanced (DCE) MRI during lactation. MATERIALS AND METHODS Datasets of 198 lactating patients, including 66 pregnancy-associated breast cancer (PABC) patients and 132 controls, who were scanned by DCE on 1.5-T MRI, were retrospectively evaluated. Six blinded, expert radiologists independently read a single DCE maximal intensity projection (MIP) image for each case and were asked to determine whether malignancy was suspected and the background-parenchymal-enhancement (BPE) grade. Likewise, computer-aided diagnosis CAD MIP images were independently read by the readers. Contrast-to-noise ratio (CNR) analysis was measured and compared among four consecutive acquisitions of DCE subtraction images. RESULTS For MIP-DCE images, the readers achieved the following means: sensitivity 93.3%, specificity 80.3%, positive-predictive-value 70.4, negative-predictive-value 96.2, and diagnostic accuracy of 84.6%, with a substantial inter-rater agreement (Kappa = 0.673, p value < 0.001). Most false-positive interpretations were attributed to either the MIP presentation, an underlying benign lesion, or an asymmetric appearance due to prior treatments. CAD's derived diagnostic accuracy was similar (p = 0.41). BPE grades were significantly increased in the healthy controls compared to the PABC cohort (p < 0.001). CNR significantly decreased by 11-13% in each of the four post-contrast images (p < 0.001). CONCLUSION Breast DCE MRI maintains its high efficiency among the lactating population, probably due to a vascular-steal phenomenon, which causes a significant reduction of BPE in cancer cases. Upon validation by prospective, multicenter trials, this study could open up the opportunity for breast MRI to be indicated in the screening and diagnosis of lactating patients, with the aim of facilitating an earlier diagnosis of PABC. KEY POINTS • A single DCE MIP image was sufficient to reach a mean sensitivity of 93.3% and NPV of 96.2%, to stress the high efficiency of breast MRI during lactation. • Reduction in BPE among PABC patients compared to the lactating controls suggests that several factors, including a possible vascular steal phenomenon, may affect cancer patients. • Reduction in CNR along four consecutive post-contrast acquisitions highlights the differences in breast carcinoma and BPE kinetics and explains the sufficient conspicuity on the first subtracted image.
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Affiliation(s)
- Noam Nissan
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel.
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Efi Efraim Moss Massasa
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
| | - Ethan Bauer
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Osnat Halshtok-Neiman
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Anat Shalmon
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michael Gotlieb
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Renata Faermann
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - David Samoocha
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yael Yagil
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tomer Ziv-Baran
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Debbie Anaby
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Miri Sklair-Levy
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st. Tel Hashomer, 5265601, Ramat Gan, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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Nissan N, Bauer E, Moss Massasa EE, Sklair-Levy M. Breast MRI during pregnancy and lactation: clinical challenges and technical advances. Insights Imaging 2022; 13:71. [PMID: 35397082 PMCID: PMC8994812 DOI: 10.1186/s13244-022-01214-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/21/2022] [Indexed: 12/12/2022] Open
Abstract
The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.
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Affiliation(s)
- Noam Nissan
- Radiology Department, Sheba Medical Center, 5265601, Tel Hashomer, Israel. .,Sackler Medicine School, Tel Aviv University, Tel Aviv, Israel.
| | - Ethan Bauer
- Sackler Medicine School, New-York Program, Tel Aviv University, Tel Aviv, Israel
| | - Efi Efraim Moss Massasa
- Joint Medicine School Program of Sheba Medical Center, St. George's, University of London and the University of Nicosia, Sheba Medical Center, Tel Hashomer, Israel
| | - Miri Sklair-Levy
- Radiology Department, Sheba Medical Center, 5265601, Tel Hashomer, Israel.,Sackler Medicine School, Tel Aviv University, Tel Aviv, Israel
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MRI of the Lactating Breast: Computer-Aided Diagnosis False Positive Rates and Background Parenchymal Enhancement Kinetic Features. Acad Radiol 2021; 29:1332-1341. [PMID: 34857455 DOI: 10.1016/j.acra.2021.11.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 11/01/2021] [Accepted: 11/01/2021] [Indexed: 12/28/2022]
Abstract
RATIONALE AND OBJECTIVES To investigate the application of computer-added diagnosis (CAD) in dynamic contrast-enhanced (DCE) MRI of the healthy lactating breast, focusing on false-positive rates and background parenchymal enhancement (BPE) coloring patterns in comparison with breast cancer features in non-lactating patients. MATERIALS AND METHODS The study population was composed of 58 healthy lactating patients and control groups of 113 healthy premenopausal non-lactating patients and 55 premenopausal non-lactating patients with newly-diagnosed breast cancer. Patients were scanned on 1.5-T MRI using conventional DCE protocol. A retrospective analysis of DCE-derived CAD properties was conducted using a commercial software that is regularly utilized in our routine radiological work-up. Qualitative morphological characterization and automatically-obtained quantitative parametric measurements of the BPE-induced CAD coloring were categorized and subgroups' trends and differences between the lactating and cancer cohorts were statistically assessed. RESULTS CAD false-positive coloring was found in the majority of lactating cases (87%). Lactation BPE coloring was characteristically non-mass enhancement (NME)-like shaped (87%), bilateral (79%) and symmetric (64%), whereas, unilateral coloring was associated with prior irradiation (p <0.0001). Inter-individual variability in CAD appearance of both scoring-grade and kinetic-curve dominance was found among the lactating cohort. When compared with healthy non-lactating controls, CAD false positive probability was significantly increased [Odds ratio 40.2, p <0001], while in comparison with the breast cancer cohort, CAD features were mostly inconclusive, even though increased size parameters were significantly associated with lactation-BPE (p <0.00001). CONCLUSION BPE was identified as a common source for false-positive CAD coloring on breast DCE-MRI among lactating population. Despite several typical characteristics, overlapping features with breast malignancy warrant a careful evaluation and clinical correlation in all cases with suspected lactation induced CAD coloring.
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Nissan N, Sandler I, Eifer M, Eshet Y, Davidson T, Bernstine H, Groshar D, Sklair-Levy M, Domachevsky L. Physiologic and hypermetabolic breast 18-F FDG uptake on PET/CT during lactation. Eur Radiol 2020; 31:163-170. [PMID: 32749586 DOI: 10.1007/s00330-020-07081-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 07/16/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To investigate the patterns of breast cancer-related and lactation-related 18F-FDG uptake in breasts of lactating patients with pregnancy-associated breast cancer (PABC) and without breast cancer. METHODS 18F-FDG-PET/CT datasets of 16 lactating patients with PABC and 16 non-breast cancer lactating patients (controls) were retrospectively evaluated. Uptake was assessed in the tumor and non-affected lactating tissue of the PABC group, and in healthy lactating breasts of the control group, using maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), and breast-SUVmax/liver-SUVmean ratio. Statistical tests were used to evaluate differences and correlations between the groups. RESULTS Physiological uptake in non-breast cancer lactating patients' breasts was characteristically high regardless of active malignancy status other than breast cancer (SUVmax = 5.0 ± 1.7, n = 32 breasts). Uptake correlated highly between the two breasts (r = 0.61, p = 0.01), but was not correlated with age or lactation duration (p = 0.24 and p = 0.61, respectively). Among PABC patients, the tumors demonstrated high 18F-FDG uptake (SUVmax = 7.8 ± 7.2, n = 16), which was 326-643% higher than the mostly low physiological FDG uptake observed in the non-affected lactating parenchyma of these patients (SUVmax = 2.1 ± 1.1). Overall, 18F-FDG uptake in lactating breasts of PABC patients was significantly decreased by 59% (p < 0.0001) compared with that of lactating controls without breast cancer. CONCLUSION 18F-FDG uptake in lactating tissue of PABC patients is markedly lower compared with the characteristically high physiological uptake among lactating patients without breast cancer. Consequently, breast tumors visualized by 18F-FDG uptake in PET/CT were comfortably depicted on top of the background 18F-FDG uptake in lactating tissue of PABC patients. KEY POINTS • FDG uptake in the breast is characteristically high among lactating patients regardless of the presence of an active malignancy other than breast cancer. • FDG uptake in non-affected lactating breast tissue is significantly lower among PABC patients compared with that in lactating women who do not have breast cancer. • In pregnancy-associated breast cancer patients, 18F-FDG uptake is markedly increased in the breast tumor compared with uptake in the non-affected lactating tissue, enabling its prompt visualization on PET/CT.
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Affiliation(s)
- Noam Nissan
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st., Tel Hashomer, 5265601, Ramat Gan, Israel. .,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Israel Sandler
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st., Tel Hashomer, 5265601, Ramat Gan, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michal Eifer
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Institute of Nuclear Medicine, Sheba Medical Center, Ramat Gan, Israel
| | - Yael Eshet
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Institute of Nuclear Medicine, Sheba Medical Center, Ramat Gan, Israel
| | - Tima Davidson
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Institute of Nuclear Medicine, Sheba Medical Center, Ramat Gan, Israel
| | - Hanna Bernstine
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Department of Nuclear Medicine, Assuta Medical Centers, Tel Aviv, Israel
| | - David Groshar
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Department of Nuclear Medicine, Assuta Medical Centers, Tel Aviv, Israel
| | - Miri Sklair-Levy
- Department of Radiology, Sheba Medical Center, Emek Ha-Ella 1 st., Tel Hashomer, 5265601, Ramat Gan, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Liran Domachevsky
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Institute of Nuclear Medicine, Sheba Medical Center, Ramat Gan, Israel
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Nissan N, Allweis T, Menes T, Brodsky A, Paluch-Shimon S, Haas I, Golan O, Miller Y, Barlev H, Carmon E, Brodsky M, Anaby D, Lawson P, Halshtok-Neiman O, Shalmon A, Gotlieb M, Faermann R, Konen E, Sklair-Levy M. Breast MRI during lactation: effects on tumor conspicuity using dynamic contrast-enhanced (DCE) in comparison with diffusion tensor imaging (DTI) parametric maps. Eur Radiol 2019; 30:767-777. [DOI: 10.1007/s00330-019-06435-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 07/12/2019] [Accepted: 08/27/2019] [Indexed: 12/18/2022]
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You C, Li J, Zhi W, Chen Y, Yang W, Gu Y, Peng W. The volumetric-tumour histogram-based analysis of intravoxel incoherent motion and non-Gaussian diffusion MRI: association with prognostic factors in HER2-positive breast cancer. J Transl Med 2019; 17:182. [PMID: 31262334 PMCID: PMC6604303 DOI: 10.1186/s12967-019-1911-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 05/08/2019] [Indexed: 12/27/2022] Open
Abstract
Background To evaluate the imaging biomarkers of human epidermal growth factor receptor 2 (HER2) positive breast cancer in comparison to other molecular subtypes and to determine the feasibility of identifying hormone receptor (HR) status and lymph node metastasis status using volumetric-tumour histogram-based analysis through intravoxel incoherent motion (IVIM) and non-Gaussian diffusion. Methods This study included 145 breast cancer patients with 148 lesions between January and November in 2018. Among the 148 lesions, 74 were confirmed to be HER2-positive. The volumetric-tumour histogram-based features were extracted from the combined IVIM and non-Gaussian diffusion model. IVIM and non-Gaussian diffusion parameters obtained from images of the subjects with different molecular prognostic biomarker statuses were compared by Student’s t test or the Mann–Whitney U test. The area under the curve (AUC), sensitivity, and specificity at the best cut-off point were reported. The Spearman correlation coefficient was calculated to analyse the correlations of clinical tumor nodule metastasis (TNM) stage and Ki67 with the IVIM and non-Gaussian diffusion parameters. Results The entropy of mean kurtosis (MK) was significantly higher in the HER2-positive group than in the HER2-negative group (p = 0.015), with an AUC of 0.629 (95% CI 0.546, 0.707), a sensitivity of 62.6%, and a specificity of 66.2%. For HR status, the MD 5th percentile was higher in the HR-positive group of HER2-positive breast cancer (p = 0.041), with an AUC of 0.643 (95% CI 0.523, 0.751), while for lymph node status, the entropy of mean diffusivity (MK) was lower in the lymph node positive group (p = 0.040), with an AUC of 0.587 (95% CI 0.504, 0.668). The clinical TNM stage and Ki67 index were correlated with several histogram parameters. Conclusion Volumetric-lesion histogram analysis of IVIM and the non-Gaussian diffusion model can be used to provide prognostic information about HER2-positive breast cancers and potentially contribute to individualized anti-HER2 targeted therapy plans . Electronic supplementary material The online version of this article (10.1186/s12967-019-1911-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Chao You
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China
| | - Jianwei Li
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Wenxiang Zhi
- Department of Ultrasound, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Yanqiong Chen
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China
| | - Wentao Yang
- Department of Pathology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University Shanghai, Shanghai, People's Republic of China
| | - Yajia Gu
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China.
| | - Weijun Peng
- Department of Radiology, Fudan University Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dongan Road, Shanghai, 200032, People's Republic of China.
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