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Aybal T, Buğdayci O, Aribal E, Kaya H, Uğurlu MÜ, Ilgin C. Evaluation of High-risk (B3) Breast Lesions on MRI: The Role of Diffusion-weighted Imaging and Texture Analysis Features in Predicting Upgrade to Malignancy. J Comput Assist Tomogr 2025:00004728-990000000-00437. [PMID: 40164962 DOI: 10.1097/rct.0000000000001745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 02/06/2025] [Indexed: 04/02/2025]
Abstract
OBJECTIVE This study aimed to investigate the potential malignancy associated with high-risk breast lesions using breast magnetic resonance imaging (MRI) characteristics, apparent diffusion coefficient (ADC) measurements, and texture analysis parameters. METHODS This retrospective study included 40 patients with 41 lesions diagnosed as high-risk lesions after needle biopsy. All the patients underwent surgery. Based on the histopathologic results of the surgical excision, the patients were divided into 2 groups: those diagnosed with malignancy and those who were not. The MRI characteristics of the lesions were recorded. The ADC values of the lesions were measured. Textural analysis of the lesions was also performed. RESULTS Fourteen lesions (34.1%) were upgraded to malignancy. The median ADCmean values in the malignant group were 1.114 × 10-3 versus 1.383×10-3 mm2/s in the nonmalignant group, which was statistically significant (P < 0.001). The cutoff value for the mean ADC was 1.163 ×10-3 mm2/s. The sensitivity and specificity were 71.4% and 85.2%, respectively. Among the texture analysis parameters, kurtosis values obtained from images on the ADC map and the first subtracted dynamic contrast-enhanced (DCE) series and contrast values obtained from images on the second subtracted DCE series were found to be statistically significant (P = 0.016, P = 0.019, and P = 0.045, respectively) between the malignant and nonmalignant groups. CONCLUSIONS ADC measurements and texture analysis parameters provide useful diagnostic information for determining which high-risk breast lesions will progress to malignancy.
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Affiliation(s)
- Tahsin Aybal
- Department of Radiology, Marmara University School of Medicine
| | - Onur Buğdayci
- Department of Radiology, Marmara University School of Medicine
| | - Erkin Aribal
- Department of Radiology, Acibadem University School of Medicine
| | | | | | - Can Ilgin
- Public Health, Marmara University School of Medicine, Istanbul, Turkey
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Jerosha S, Subramonian SG, Mohanakrishnan A, Ramakrishnan KK, Natarajan P. The Role of Diffusion-Weighted Imaging in Characterizing Benign and Malignant Breast Lesions: A Retrospective Study. Cureus 2024; 16:e66472. [PMID: 39252724 PMCID: PMC11382431 DOI: 10.7759/cureus.66472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 08/08/2024] [Indexed: 09/11/2024] Open
Abstract
Introduction Diffusion-weighted imaging (DWI) is a promising magnetic resonance imaging (MRI) technique for differentiating between benign and malignant breast lesions. This study set out to assess the diagnostic utility of DWI and apparent diffusion coefficient (ADC) values in the characterization of breast lesions. Materials and methods A retrospective analysis comprised 30 patients with breast lesions who had breast MRI with DWI. The histopathological findings, ADC readings, and conventional MRI features were all analyzed. The receiver operating characteristic (ROC) curve analysis method was utilized to assess the diagnostic accuracy of DWI. Results Out of the 30 lesions, 22 (73.3%) were benign and eight (26.7%) were malignant. Malignant lesions exhibited significantly lower ADC values (p < 0.001) compared to benign lesions. An ADC cutoff value of 1.1 × 10-3 mm2/s was optimal for differentiating benign from malignant lesions, yielding 90.81% sensitivity, 91.51% specificity, and 91.5% accuracy. Conclusion Combining DWI with quantitative ADC analysis is a helpful, non-invasive method for the characterization of breast lesions. It shows excellent diagnostic accuracy in identifying benign and malignant lesions, which may cut down on pointless biopsies and help with patient management.
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Affiliation(s)
- Stany Jerosha
- Radiodiagnosis, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Sakthi Ganesh Subramonian
- Radiodiagnosis, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Arunkumar Mohanakrishnan
- Radiodiagnosis, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Karthik Krishna Ramakrishnan
- Radiodiagnosis, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
| | - Paarthipan Natarajan
- Radiodiagnosis, Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IND
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Gül M, Russo GI, Kandil H, Boitrelle F, Saleh R, Chung E, Kavoussi P, Mostafa T, Shah R, Agarwal A. Male Infertility: New Developments, Current Challenges, and Future Directions. World J Mens Health 2024; 42:502-517. [PMID: 38164030 PMCID: PMC11216957 DOI: 10.5534/wjmh.230232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 08/27/2023] [Indexed: 01/03/2024] Open
Abstract
There have been many significant scientific advances in the diagnostics and treatment modalities in the field of male infertility in recent decades. Examples of these include assisted reproductive technologies, sperm selection techniques for intracytoplasmic sperm injection, surgical procedures for sperm retrieval, and novel tests of sperm function. However, there is certainly a need for new developments in this field. In this review, we discuss advances in the management of male infertility, such as seminal oxidative stress testing, sperm DNA fragmentation testing, genetic and epigenetic tests, genetic manipulations, artificial intelligence, personalized medicine, and telemedicine. The role of the reproductive urologist will continue to expand in future years to address different topzics related to diverse questions and controversies of pathophysiology, diagnosis, and therapy of male infertility, training researchers and physicians in medical and scientific research in reproductive urology/andrology, and further development of andrology as an independent specialty.
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Affiliation(s)
- Murat Gül
- Department of Urology, Selcuk University School of Medicine, Konya, Turkey
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Giorgio Ivan Russo
- Urology Section, University of Catania, Catania, Italy
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Hussein Kandil
- Fakih IVF Fertility Center, Abu Dhabi, UAE
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Florence Boitrelle
- Reproductive Biology, Fertility Preservation, Andrology, CECOS, Poissy Hospital, Poissy, France
- Paris Saclay University, UVSQ, INRAE, BREED, Jouy-en-Josas, France
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Ramadan Saleh
- Department of Dermatology, Venereology and Andrology, Faculty of Medicine, Sohag University, Sohag, Egypt
- Ajyal IVF Center, Ajyal Hospital, Sohag, Egypt
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Eric Chung
- Department of Urology, Princess Alexandra Hospital, University of Queensland, Brisbane, QLD, Australia
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Parviz Kavoussi
- Department of Reproductive Urology, Austin Fertility & Reproductive Medicine/Westlake IVF, Austin, TX, USA
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Taymour Mostafa
- Department of Andrology, Sexology and STIs, Faculty of Medicine, Cairo University, Cairo, Egypt
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Rupin Shah
- Department of Urology, Lilavati Hospital and Research Centre, Mumbai, India
- Well Women's Centre, Sir HN Reliance Foundation Hospital, Mumbai, India
- Global Andrology Forum, Moreland Hills, OH, USA
| | - Ashok Agarwal
- Global Andrology Forum, Moreland Hills, OH, USA
- Cleveland Clinic, Cleveland, OH, USA.
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Hesham Said A, Ragab A, Zohdy W, Ibrahim AS, Abd El Basset AS. Diffusion-weighted magnetic resonance imaging and magnetic resonance spectroscopy for non-invasive characterization of azoospermia: A prospective comparative single-center study. Andrology 2023; 11:1096-1106. [PMID: 36690593 DOI: 10.1111/andr.13392] [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: 10/07/2022] [Revised: 12/26/2022] [Accepted: 01/18/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND Azoospermia affects about 15% of childless males. The differential diagnosis between subtypes of azoospermia is the initial step in its management. OBJECTIVES To investigate the role of diffusion-weighted magnetic resonance imaging and proton magnetic resonance spectroscopy in distinguishing obstructive azoospermia from non-obstructive azoospermia and predicting sperm retrieval together with histological alterations in men with non-obstructive azoospermia. MATERIALS AND METHODS This prospective comparative study involved 60 men with obstructive azoospermia (group A) and 60 men with non-obstructive azoospermia (group B). Scrotal proton magnetic resonance spectroscopy and diffusion-weighted magnetic resonance imaging were conducted for all participants to respectively evaluate testicular metabolites and normalized apparent diffusion coefficient 1 week before sperm retrieval. RESULTS Apparent diffusion coefficient was significantly higher in group B as compared to group A (0.47 ± 0.11 vs. 0.29 ± 0.05; and 0.46 ± 0.14 vs. 0.28 ± 0.02) for the right and left testis, respectively. Conversely, testicular choline and lipids were significantly higher in group A as compared to group B. Normalized apparent diffusion coefficient, choline, and lipids at cut-off levels of 0.353, 0.31, and 0.725 could differentiate between obstructive azoospermia and non-obstructive azoospermia (area under the curve = 0.963; confidence interval = 0.939-0.986, area under the curve = 0.985; confidence interval = 0.974-0.997, and area under the curve = 0.970; confidence interval = 0.940-0.999, respectively). Regarding the prediction of sperm retrieval in the non-obstructive azoospermia group, choline levels had the highest area under the curve (0.923), and its cut-off level was 0.195. The normalized apparent diffusion coefficient was significantly lower in men with positive sperm retrieval as compared to men with unsuccessful retrieval. Finally, it was revealed that all magnetic resonance imaging parameters except creatine could independently predict testicular histology in men with non-obstructive azoospermia. The highest prediction was 95% in normal spermatogenesis, and the least prediction was 40% in spermatid arrest. Regression analysis was used to detect final predictors and extrapolate an equation that could be used to predict testicular pathology CONCLUSIONS: Normalized apparent diffusion coefficient and proton magnetic resonance spectroscopy are helpful in differentiating obstructive azoospermia from non-obstructive azoospermia and predicting sperm retrieval and related histological alterations in men with non-obstructive azoospermia.
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Affiliation(s)
- Ahmed Hesham Said
- Department of Radiology, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt
| | - Ahmed Ragab
- Department of Andrology, Sexology, and STDs, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt
| | - Wael Zohdy
- Department of Andrology, Sexology, and STDs, Faculty of Medicine, Cairo University, Cairo, Egypt
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Zhang J, Xing X, Wang Q, Chen Y, Yuan H, Lang N. Preliminary study of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted MRI and diffusion kurtosis imaging on differential diagnosis of spinal metastases and chordoma. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2022; 31:3130-3138. [PMID: 35648206 DOI: 10.1007/s00586-022-07269-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/03/2022] [Accepted: 05/15/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE Quantitative comparison of diffusion parameters from various models of diffusion-weighted (DWI) and diffusion kurtosis (DKI) imaging for distinguishing spinal metastases and chordomas. METHODS DWI and DKI examinations were performed in 31 and 13 cases of spinal metastases and chordomas, respectively. DWI derived apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), water molecular distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α). DKI derived mean diffusivity (MD) and mean kurtosis (MK). Independent sample t-testing compared statistical differences among parameters. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve were determined. Pearson correlation analysis evaluated the parameters' correlations. RESULTS ADC, D, f, DDC, α, and MD were significantly lower in spinal metastases than chordomas (all P < 0.05). MK was significantly higher in spinal metastases than chordomas (P < 0.05). D had the highest area under the ROC curve (AUC) of 0.886, greater than MD (AUC = 0.706) or DDC (AUC = 0.742) in differentiating the two tumors (both P < 0.05). Combining D with f and α statistically significantly increased the AUC for diagnosis (to 0.995) relative to D alone (P < 0.05). There was a certain correlation among DDC, ADC, and D (all P < 0.05). CONCLUSIONS Monoexponential, biexponential, and stretched-exponential models of DWI and DKI can potentially differentiate spinal metastases and chordomas. D combined with f and α performed best.
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Affiliation(s)
- Jiahui Zhang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Xiaoying Xing
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Qizheng Wang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Yongye Chen
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China
| | - Ning Lang
- Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, People's Republic of China.
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Obata T. EIC Remarks for a Special 20th Anniversary Issue of MRMS. Magn Reson Med Sci 2022; 21:1-5. [PMID: 35228486 PMCID: PMC9199973 DOI: 10.2463/mrms.e.2021-3000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- Takayuki Obata
- The Editorial Committee of Magnetic Resonance in Medical Sciences
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Cho E, Baek HJ, Szczepankiewicz F, An HJ, Jung EJ, Lee HJ, Lee J, Gho SM. Clinical experience of tensor-valued diffusion encoding for microstructure imaging by diffusional variance decomposition in patients with breast cancer. Quant Imaging Med Surg 2022; 12:2002-2017. [PMID: 35284250 PMCID: PMC8899958 DOI: 10.21037/qims-21-870] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/13/2021] [Indexed: 08/28/2023]
Abstract
BACKGROUND Diffusion-weighted imaging plays a key role in magnetic resonance imaging (MRI) of breast tumors. However, it remains unclear how to interpret single diffusion encoding with respect to its link with tissue microstructure. The purpose of this retrospective cross-sectional study was to use tensor-valued diffusion encoding to investigate the underlying microstructure of invasive ductal carcinoma (IDC) and evaluate its potential value in a clinical setting. METHODS We retrospectively reviewed biopsy-proven breast cancer patients who underwent preoperative breast MRI examination from July 2020 to March 2021. We reviewed the MRI of 29 patients with 30 IDCs, including analysis by diffusional variance decomposition enabled by tensor-valued diffusion encoding. The diffusion parameters of mean diffusivity (MD), total mean kurtosis (MKT), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), macroscopic fractional anisotropy (FA), and microscopic fractional anisotropy (µFA) were estimated. The parameter differences were compared between IDC and normal fibroglandular breast tissue (FGBT), as well as the association between the diffusion parameters and histopathologic items. RESULTS The mean value of MD in IDCs was significantly lower than that of normal FGBT (1.07±0.27 vs. 1.34±0.29, P<0.001); however, MKT, MKA, MKI, FA, and µFA were significantly higher (P<0.005). Among all the diffusion parameters, MKI was positively correlated with the tumor size on both MRI and pathological specimen (rs=0.38, P<0.05 vs. rs=0.54, P<0.01), whereas MKT had a positive correlation with the tumor size in the pathological specimen only (rs=0.47, P<0.02). In addition, the lymph node (LN) metastasis group had significantly higher MKT, MKA, and µFA compared to the metastasis negative group (P<0.05). CONCLUSIONS Tensor-valued diffusion encoding enables a useful non-invasive method for characterizing breast cancers with information on tissue microstructures. Particularly, µFA could be a potential imaging biomarker for evaluating breast cancers prior to surgery or chemotherapy.
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Affiliation(s)
- Eun Cho
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Hye Jin Baek
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
- Department of Radiology, Institute of Health Sciences, Gyeongsang National University School of Medicine, Jinju-daero, Jinju, Republic of Korea
| | - Filip Szczepankiewicz
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Klinikgatan, Sweden
| | - Hyo Jung An
- Department of Pathology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Seongsan-gu, Changwon, Republic of Korea
| | - Eun Jung Jung
- Department of Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-gu, Busan, Republic of Korea
| | | | - Sung-Min Gho
- MR Clinical Solutions & Research Collaborations, GE Healthcare, Seoul, Republic of Korea
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Ohno M, Ohno N, Miyati T, Kawashima H, Kozaka K, Matsuura Y, Gabata T, Kobayashi S. Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma. Magn Reson Med Sci 2021; 20:396-403. [PMID: 33563872 PMCID: PMC8922350 DOI: 10.2463/mrms.mp.2020-0103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Purpose To obtain detailed information in breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) using triexponential diffusion analysis. Methods Diffusion-weighted images (DWI) of the breast were obtained using single-shot diffusion echo-planar imaging with 15 b-values. Mean signal intensities at each b-value were measured in the DCIS and IDC lesions and fitted with the triexponential function based on a two-step approach: slow-restricted diffusion coefficient (Ds) was initially determined using a monoexponential function with b-values > 800 s/mm2. The diffusion coefficient of free water at 37°C was assigned to the fast-free diffusion coefficient (Df). Finally, the perfusion-related diffusion coefficient (Dp) was derived using all the b-values. Furthermore, biexponential analysis was performed to obtain the perfusion-related diffusion coefficient (D*) and the perfusion-independent diffusion coefficient (D). Monoexponential analysis was performed to obtain the apparent diffusion coefficient (ADC). The sensitivity and specificity of the aforementioned diffusion coefficients for distinguishing between DCIS and IDC were evaluated using the pathological results. Results The Ds, D, and ADC of DCIS were significantly higher than those of IDC (P < 0.01 for all). There was no significant correlation between Dp and Ds, but there was a weak correlation between D* and D. The combination of Dp and Ds showed higher sensitivity and specificity (85.9% and 71.4%, respectively), compared to the combination of D* and D (81.5% and 33.3%, respectively). Conclusion Triexponential analysis can provide detailed diffusion information for breast tumors that can be used to differentiate between DCIS and IDC.
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Affiliation(s)
- Masako Ohno
- Department of Radiological Technology, Kanazawa University Hospital
| | - Naoki Ohno
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
| | - Tosiaki Miyati
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
| | - Hiroko Kawashima
- Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University.,Department of Radiology, Kanazawa University Hospital
| | - Kazuto Kozaka
- Department of Radiology, Kanazawa University Hospital
| | | | | | - Satoshi Kobayashi
- Department of Radiological Technology, Kanazawa University Hospital.,Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University.,Department of Radiology, Kanazawa University Hospital
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Feng W, Gao Y, Lu XR, Xu YS, Guo ZZ, Lei JQ. Correlation between molecular prognostic factors and magnetic resonance imaging intravoxel incoherent motion histogram parameters in breast cancer. Magn Reson Imaging 2021; 85:262-270. [PMID: 34740800 DOI: 10.1016/j.mri.2021.10.027] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 07/26/2021] [Accepted: 10/17/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To explore the efficacy of the quantitative parameter histogram analysis of intravoxel incoherent motion (IVIM) for different molecular prognostic factors of breast cancer. MATERIALS AND METHODS A total of 72 patients with breast cancer who were confirmed by surgical pathology and underwent preoperative magnetic resonance imaging (MRI) were analyzed retrospectively. A region of interest (ROI) was drawn in each slice of the IVIM images. Whole-tumor histogram parameters were obtained with Firevoxel's software by accumulating all ROIs. Next, Kolmogorov-Smirnov test, Student's t-test, Mann-Whitney U test, receiver operating characteristic curve analysis and spearman rank correlation analysis were used to assess the relationship between histogram parameters and molecular prognostic factors of breast cancer. RESULTS Among estrogen receptor (ER)-negative ROCs, the apparent diffusion coefficient (ADC) 10th percentile had the highest ROC of 0.792, with a cut-off value of 0.788 × 10-3 mm2/s, and sensitivity and specificity of 0.714 and 0.867, respectively. The negative correlation between lymph node metastasis status and ADC standard deviation was significant (ρ = -0.44, the correlation coefficients was represented by ρ). Positive correlations were observed between hormonal expression of ER and progesterone receptor (PR) with heterogeneity metrics of ADC or perfusion fraction (f), such as ADC inhomogeneity (ρ = 0.37, ρ = 0.29) and f skewness (ρ = 0.32, ρ = 0.28). Negative correlations were observed with numerical metrics, such as the ADC median (ρ = -0.31, ρ = -0.34) and f 45th percentile (ρ = -0.35, ρ = -0.28). The positive correlations between human epidermal receptor factor-2 (HER2) and pseudo-diffusivity (Dp) numerical metrics, Ki-67 expression, and heterogeneity metrics of Dp were high. CONCLUSIONS The ADC 10th percentile had the largest area under the curve in the ER-negative ROC analysis, and the ADC standard deviation was the most valuable in the correlation analysis of lymph node metastasis. Whole-lesion quantitative histogram parameters of IVIM could, therefore, provide a scientific basis for radiomics to further guide clinical practice in the prognosis of breast cancer.
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Affiliation(s)
- Wen Feng
- The First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, Gansu, China; Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Ya Gao
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Xing-Ru Lu
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Yong-Sheng Xu
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China
| | - Zhuan-Zhuan Guo
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shanxi, China
| | - Jun-Qiang Lei
- Department of Radiology, the First hospital of Lanzhou University, Lanzhou 730000, Gansu, China.
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Santucci D, Faiella E, Calabrese A, Beomonte Zobel B, Ascione A, Cerbelli B, Iannello G, Soda P, de Felice C. On the Additional Information Provided by 3T-MRI ADC in Predicting Tumor Cellularity and Microscopic Behavior. Cancers (Basel) 2021; 13:cancers13205167. [PMID: 34680316 PMCID: PMC8534264 DOI: 10.3390/cancers13205167] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/11/2021] [Accepted: 10/13/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND to evaluate whether Apparent Diffusion Coefficient (ADC) values of invasive breast cancer, provided by 3T Diffusion Weighted-Images (DWI), may represent a non-invasive predictor of pathophysiologic tumor aggressiveness. METHODS 100 Patients with histologically proven invasive breast cancers who underwent a 3T-MRI examination were included in the study. All MRI examinations included dynamic contrast-enhanced and DWI/ADC sequences. ADC value were calculated for each lesion. Tumor grade was determined according to the Nottingham Grading System, and immuno-histochemical analysis was performed to assess molecular receptors, cellularity rate, on both biopsy and surgical specimens, and proliferation rate (Ki-67 index). Spearman's Rho test was used to correlate ADC values with histological (grading, Ki-67 index and cellularity) and MRI features. ADC values were compared among the different grading (G1, G2, G3), Ki-67 (<20% and >20%) and cellularity groups (<50%, 50-70% and >70%), using Mann-Whitney and Kruskal-Wallis tests. ROC curves were performed to demonstrate the accuracy of the ADC values in predicting the grading, Ki-67 index and cellularity groups. RESULTS ADC values correlated significantly with grading, ER receptor status, Ki-67 index and cellularity rates. ADC values were significantly higher for G1 compared with G2 and for G1 compared with G3 and for Ki-67 < 20% than Ki-67 > 20%. The Kruskal-Wallis test showed that ADC values were significantly different among the three grading groups, the three biopsy cellularity groups and the three surgical cellularity groups. The best ROC curves were obtained for the G3 group (AUC of 0.720), for G2 + G3 (AUC of 0.835), for Ki-67 > 20% (AUC of 0.679) and for surgical cellularity rate > 70% (AUC of 0.805). CONCLUSIONS 3T-DWI ADC is a direct predictor of cellular aggressiveness and proliferation in invasive breast carcinoma, and can be used as a supporting non-invasive factor to characterize macroscopic lesion behavior especially before surgery.
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Affiliation(s)
- Domiziana Santucci
- Department of Radiology, University of Rome “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy; (E.F.); (B.B.Z.)
- Correspondence: ; Tel.: +39-333-5376-594
| | - Eliodoro Faiella
- Department of Radiology, University of Rome “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy; (E.F.); (B.B.Z.)
| | - Alessandro Calabrese
- Department of Radiology, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome, Italy; (A.C.); (C.d.F.)
| | - Bruno Beomonte Zobel
- Department of Radiology, University of Rome “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy; (E.F.); (B.B.Z.)
| | - Andrea Ascione
- Department of Radiological, Oncological and Pathological Science, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome, Italy; (A.A.); (B.C.)
| | - Bruna Cerbelli
- Department of Radiological, Oncological and Pathological Science, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome, Italy; (A.A.); (B.C.)
| | - Giulio Iannello
- Unit of Computer Systems and Bioinformatics, Department of Engineering, University of Rome “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy; (G.I.); (P.S.)
| | - Paolo Soda
- Unit of Computer Systems and Bioinformatics, Department of Engineering, University of Rome “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy; (G.I.); (P.S.)
| | - Carlo de Felice
- Department of Radiology, University of Rome “Sapienza”, Viale del Policlinico 155, 00161 Rome, Italy; (A.C.); (C.d.F.)
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Cai W, Min X, Chen D, Fan C, Feng Z, Li B, Zhang P, You H, Xie J, Liu J, Wang L. Noninvasive Differentiation of Obstructive Azoospermia and Nonobstructive Azoospermia Using Multimodel Diffusion Weighted Imaging. Acad Radiol 2021; 28:1375-1382. [PMID: 32622745 DOI: 10.1016/j.acra.2020.05.039] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 05/13/2020] [Accepted: 05/30/2020] [Indexed: 10/23/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate the diagnostic performance of parameters derived from multimodel diffusion weighted imaging (monoexponential, stretched-exponential diffusion weighted imaging and diffusion kurtosis imaging [DKI]) from noninvasive magnetic resonance imaging in distinguishing obstructive azoospermia (OA) from nonobstructive azoospermia (NOA). MATERIALS AND METHODS Forty-six patients with azoospermia were prospectively enrolled and classified into two groups (21 OA patients and 25 NOA patients). The multimodel parameters of diffusion-weighted imaging (DWI; apparent diffusion coefficient [ADC], distributed diffusion coefficient [DDC], diffusion heterogeneity [α], diffusion kurtosis diffusivity [Dapp], and diffusion kurtosis coefficient [Kapp]) were derived. The diagnostic performance of these parameters for the differentiation of OA and NOA patients were evaluated using receiver operating characteristic analysis. The area under the curve (AUC) was calculated to evaluate the diagnostic accuracy of each parameter. RESULTS All the parameters (ADC, α, DDC, Dapp, and Kapp) values were significantly different between OA and NOA (P < 0.001 for all). For the differentiation of OA from NOA, Kapp showed the highest AUC value (0.965), followed by DDC (0.946), Dapp (0.933), ADC (0.922), and α (0.887). Kapp had a significantly higher AUC than the conventional ADC (P < 0.05). CONCLUSION Parameters derived from multimodels of DWI have the potential for the noninvasive differentiation of OA and NOA. The Kapp value derived from the DKI model might serve as a useful imaging marker for the differentiation of azoospermia.
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Ma W, Mao J, Wang T, Huang Y, Zhao ZH. Distinguishing between benign and malignant breast lesions using diffusion weighted imaging and intravoxel incoherent motion: A systematic review and meta-analysis. Eur J Radiol 2021; 141:109809. [PMID: 34116452 DOI: 10.1016/j.ejrad.2021.109809] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 05/27/2021] [Accepted: 05/31/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE We sought to evaluate the diagnostic performance of diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant breast tumors by performing a meta-analysis. METHODS We comprehensively searched the electronic databases PubMed and Embase from January 2000 to April 2020 for studies in English. Studies were included if they reported the sensitivity and specificity for identifying benign and malignant breast lesions using DWI or IVIM. Studies were reviewed according to QUADAS-2. The data inhomogeneity and publication bias were also assessed. In order to explore the influence of different field strengths and different b values on diagnostic efficiency, we conducted subgroup analysis. RESULTS We analyzed 79 studies, which included a total of 6294 patients with 4091 malignant lesions and 2793 benign lesions. Overall, the pooled sensitivity and specificity of ADC for detecting malignant breast tumors were 0.87 (0.86-0.88) and 0.80 (0.78-0.81), respectively. The PLR was 5.09 (4.16-6.24); the NLR was 0.15 (0.13-0.18); and the DOR was 38.95 (28.87-52.54). The AUC value was 0.9297. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity and specificity was 0.85 (0.82-0.88) and 0.87(0.83-0.90), respectively; the PLR was 5.65 (3.91-8.18); the NLR was 0.17 (0.12-0.26); and the DOR was 38.44 (23.57-62.69). The AUC value was 0.9265. Most of parameters demonstrated considerable statistically significant heterogeneity (P < 0.05, I2>50 %) except the pooled DOR, PLR of D and the pooled DOR and NLR of D*. CONCLUSIONS Our meta-analysis indicated that DWI and IVIM had high sensitivity and specificity in the differential diagnosis of breast lesions; and compared with DWI, IVIM could not further increase the diagnostic performance. There was no significant difference in diagnostic accuracy.
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Affiliation(s)
- Weili Ma
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Key Laboratory of Functional Molecular Imaging of Tumor and Interventional Diagnosis and Treatment of Shaoxing City, Shaoxing 312000, China
| | - Jiwei Mao
- Department of Radiation Oncology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Shaoxing 312000, China
| | - Ting Wang
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Key Laboratory of Functional Molecular Imaging of Tumor and Interventional Diagnosis and Treatment of Shaoxing City, Shaoxing 312000, China
| | - Yanan Huang
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Key Laboratory of Functional Molecular Imaging of Tumor and Interventional Diagnosis and Treatment of Shaoxing City, Shaoxing 312000, China
| | - Zhen Hua Zhao
- Department of Radiology, Shaoxing People's Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Key Laboratory of Functional Molecular Imaging of Tumor and Interventional Diagnosis and Treatment of Shaoxing City, Shaoxing 312000, China.
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Zhang C, Zhang S. Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2021; 43:1184-1196. [PMID: 31603812 DOI: 10.1109/tpami.2019.2946370] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Matrix decomposition is a popular and fundamental approach in machine learning and data mining. It has been successfully applied into various fields. Most matrix decomposition methods focus on decomposing a data matrix from one single source. However, it is common that data are from different sources with heterogeneous noise. A few of the matrix decomposition methods have been extended for such multi-view data integration and pattern discovery while only a few methods were designed to consider the heterogeneity of noise in such multi-view data for data integration explicitly. To this end, in this article, we propose a joint matrix decomposition framework (BJMD), which models the heterogeneity of noise by the Gaussian distribution in a Bayesian framework. We develop two algorithms to solve this model: one is a variational Bayesian inference algorithm, which makes full use of the posterior distribution; and another is a maximum a posterior algorithm, which is more scalable and can be easily paralleled. Extensive experiments on synthetic and real-world datasets demonstrate that BJMD is superior or competitive to the state-of-the-art methods.
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Azzam H, Mansour S, Salem N, El-Assaly H. Correlative study between ADC value and grading of invasive breast cancer. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [DOI: 10.1186/s43055-019-0124-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
AbstractBackgroundStudying breast carcinoma is of great importance as it is the commonest female malignancy. Accurate preoperative assessment of disease characteristics and prognosis would be of great help in the diagnosis and treatment planning of breast cancer. The aim of this study was to evaluate the role of the apparent diffusion coefficient (ADC) value in detecting the grading of invasive breast carcinoma prior to management.ResultsThere was a significant difference between the mean ADC value of tumors of grade I and III (p = 0.001) and between grade I and II (p = 0.002). However, there was no significant difference between grade II and III (p = 0.979). High ADC values were associated with low-grade tumors. The mean ADC value of 0.93 × 10–3 mm2/s showed sensitivity 98%, specificity 100%, PPV 100%, NPV 83.3%, accuracy 98.2%, AUC = 0.994, and 95% confidence interval of 0.978 to 1.000.ConclusionDWI is a contrast-free modality that allows for both morphological and quantitative analysis. ADC value may not be the proper modality to determine the prognosis of breast cancer due to overlap values, yet it could be a good discriminator between low- and high-grade tumors and hence predictor of breast cancer cells that would respond to chemotherapy.
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Atallah D, Moubarak M, Arab W, El Kassis N, Chahine G, Salem C. MRI‐based predictive factors of axillary lymph node status in breast cancer. Breast J 2020; 26:2177-2182. [DOI: 10.1111/tbj.14089] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 09/26/2020] [Accepted: 09/29/2020] [Indexed: 12/18/2022]
Affiliation(s)
- David Atallah
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Gynecology and Obstetrics Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
| | - Malak Moubarak
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Gynecology and Obstetrics Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
| | - Wissam Arab
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Gynecology and Obstetrics Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
| | - Nadine El Kassis
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Gynecology and Obstetrics Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
| | - Georges Chahine
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Oncology Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
| | - Christine Salem
- Faculty of Medicine Saint Joseph University Achrafieh Lebanon
- Department of Radiology Hôtel‐Dieu de France University Hospital Achrafieh Lebanon
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Correlation of Peri-Tumoral Edema Determined in T2 Weighted Imaging with Apparent Diffusion Coefficient of Peritumoral Area in Patients with Breast Carcinoma. IRANIAN JOURNAL OF RADIOLOGY 2020. [DOI: 10.5812/iranjradiol.97978] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Breast cancer may result in remodeling of adjacent normal appearing breast tissues. Magnetic resonance imaging (MRI) is increasingly used in the diagnosis and follow-up of breast cancer by means of diffusion weighted imaging, which is based on thermal motion of water molecules in the extracellular fluid. Objectives: We investigated the correlation of visual assessment of peri-tumoral edema with peri-tumoral and tumoral apparent diffusion coefficient (ADC) values. Patients and Methods: In this cross-sectional study, from 2016 to 2018, 78 patients with 89 malignant breast lesions (mean age, 47 years) were examined by 1.5-T breast MRI. The lesions were categorized based on the visual assessment of peri-tumoral edema on T2 weighted imaging (T2WI) into two groups: (A) with edema (36 lesions) and (B) without edema (53 lesions). Measuring ADC values in the contralateral normal breast tissue, peri-tumoral tissue and peri-tumoral-normal tissue ADC ratio were compared between the two groups for all lesions. Results: The number of in situ lesions was higher in group B (7.5% vs 2.7%) with the p value of 0.01. The mean of ADC values in the normal breast tissue was 1.76 × 10-3mm2/s. Tumor ADCs were significantly lower in group A compared to group B (0.95 × 10-3mm2/s vs. 1.11 × 10-3mm2/s) with the P value of 0.003. However, peri-tumoral ADCs were significantly higher in group A (1.82 × 10-3mm2/s vs. 1.53 × 10-3mm2/s) with the p value of 0.005. The peri-tumoral-normal tissue ADC ratio was 0.87 in group B and about 1 in group A. However, the difference between normal tissue ADCs and peri-tumoral ADCs was only significant (P value of 0.005) in group B. The cut-off point value for differentiating normal tissue ADCs and peri-tumoral ADCs was 1.61 × 10-3mm2/s with the sensitivity of 65% and specificity of 70%. Conclusion: Breast cancer with peri-tumoral edema has lower tumoral ADC values, higher peri-tumoral ADC values and lower prevalence of in situ lesions. Visual assessment of peri-tumoral edema on T2WI could predict the tumoral characteristic on diffusion-weighted imaging.
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Penn AI, Medved M, Dialani V, Pisano ED, Cole EB, Brousseau D, Karczmar GS, Gao G, Reich BD, Abe H. Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images. BMC Med Imaging 2020; 20:61. [PMID: 32517657 PMCID: PMC7282088 DOI: 10.1186/s12880-020-00458-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 05/20/2020] [Indexed: 12/03/2022] Open
Abstract
Background There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts. Methods We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm2 were excluded, resulting in analysis of 50 cases with 63 lesions (29 benign, 34 cancers). Spin-echo echo-planar imaging DWI was acquired at 1.5 T and 3 T. Data from three diffusion encoding gradient directions were exported and processed independently. Lesion ROIs were hand-drawn on DWI images by two radiologists. A region growing algorithm generated 3D lesion models on augmented apparent-diffusion coefficient (ADC) maps and defined lesion core and lesion periphery sub-ROIs. A lesion-core and a lesion-periphery feature were defined and combined into an overall classifier whose performance was compared to that of mean ADC using receiver operating characteristic (ROC) analysis. Inter-observer variability in ROI definition was measured using Dice Similarity Coefficient (DSC). Results The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p < 0.001) with substantial agreement (DSC > 0.8) in 46% vs 13% of cases, respectively (p < 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers). Conclusions A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx).
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Affiliation(s)
- Alan I Penn
- Alan Penn & Assoc., Inc., 14 Clemson Ct, Rockville, MD, 20810, USA.
| | - Milica Medved
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
| | - Vandana Dialani
- Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA, 02215, USA
| | - Etta D Pisano
- Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA, 02215, USA.,American College of Radiology, Two Liberty Place, Philadelphia, PA, 19102, USA
| | - Elodia B Cole
- American College of Radiology, Two Liberty Place, Philadelphia, PA, 19102, USA
| | - David Brousseau
- Providence Cedars-Sinai Tarzana Medical Center, 18321 Clark Street, Tarzana, CA, 91356, USA
| | - Gregory S Karczmar
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
| | - Guimin Gao
- Department of Public Health Sciences, The University of Chicago, 5841 S. Maryland Ave. MC 2000, Chicago, IL, 60637, USA
| | - Barry D Reich
- Alan Penn & Assoc., Inc., 14 Clemson Ct, Rockville, MD, 20810, USA
| | - Hiroyuki Abe
- Department of Radiology, The University of Chicago, 5841 S. Maryland Ave. MC 2026, Chicago, IL, 60637, USA
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Wielema M, Dorrius MD, Pijnappel RM, De Bock GH, Baltzer PAT, Oudkerk M, Sijens PE. Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis. PLoS One 2020; 15:e0232856. [PMID: 32374781 PMCID: PMC7202642 DOI: 10.1371/journal.pone.0232856] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/22/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ≥ 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.
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Affiliation(s)
- M. Wielema
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M. D. Dorrius
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - R. M. Pijnappel
- Department of Radiology, Utrecht University, University Medical Center Utrecht, Utrecht, The Netherlands
| | - G. H. De Bock
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P. A. T. Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - M. Oudkerk
- University of Groningen, Groningen, The Netherlands
- Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - P. E. Sijens
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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Pintican R, Duma M, Chiorean A, Fetica B, Badan M, Bura V, Szep M, Feier D, Dudea S. Mucinous versus medullary breast carcinoma: mammography, ultrasound, and MRI findings. Clin Radiol 2020; 75:483-496. [PMID: 32057415 DOI: 10.1016/j.crad.2019.12.024] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 12/31/2019] [Indexed: 12/26/2022]
Abstract
Mucinous and medullary breast cancers (BCs) have different histological substrates that manifest as different imaging features on mammography, ultrasound, and MRI. The aim of the present review is to demonstrate the differences between these two rare BC subtypes and to describe the microscopic features, review the imaging methods for detection of both cancer subtypes, illustrate the imaging findings and present useful pearls and pitfalls. Out of a total of 30 patients with mucinous BC and nine with medullary BC, we have selected typical and also unusual imaging features that best represent these cancers. The patients underwent a mammography and breast ultrasound followed by magnetic resonance imaging. We briefly exhibit histological characteristics for a better understanding of the imaging aspects.
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Affiliation(s)
- R Pintican
- Department of Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania; Radiology and Medical Imaging Department, University Hospital, Cluj-Napoca, Romania.
| | - M Duma
- Department of Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania; Micromedica Clinic, Piatra Neamt, Romania
| | - A Chiorean
- Department of Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania; Medimages Breast Center, Cluj-Napoca, Romania
| | - B Fetica
- Pathology Department, University Hospital, Cluj-Napoca, Romania
| | - M Badan
- Pathology Department, University Hospital, Cluj-Napoca, Romania
| | - V Bura
- Radiology and Medical Imaging Department, University Hospital, Cluj-Napoca, Romania
| | - M Szep
- Medimages Breast Center, Cluj-Napoca, Romania
| | - D Feier
- Department of Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania; Medimages Breast Center, Cluj-Napoca, Romania
| | - S Dudea
- Department of Radiology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania; Radiology and Medical Imaging Department, University Hospital, Cluj-Napoca, Romania
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Use of monoexponential diffusion-weighted imaging and diffusion kurtosis imaging and dynamic contrast-enhanced-MRI for the differentiation of spinal tumors. EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2020; 29:1112-1120. [DOI: 10.1007/s00586-020-06330-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 11/22/2019] [Accepted: 02/01/2020] [Indexed: 12/26/2022]
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Baxter GC, Graves MJ, Gilbert FJ, Patterson AJ. A Meta-analysis of the Diagnostic Performance of Diffusion MRI for Breast Lesion Characterization. Radiology 2019; 291:632-641. [PMID: 31012817 DOI: 10.1148/radiol.2019182510] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background Various techniques are available to assess diffusion properties of breast lesions as a marker of malignancy at MRI. The diagnostic performance of these diffusion markers has not been comprehensively assessed. Purpose To compare by meta-analysis the diagnostic performance of parameters from diffusion-weighted imaging (DWI), diffusion-tensor imaging (DTI), and intravoxel incoherent motion (IVIM) in the differential diagnosis of malignant and benign breast lesions. Materials and Methods PubMed and Embase databases were searched from January to March 2018 for studies in English that assessed the diagnostic performance of DWI, DTI, and IVIM in the breast. Studies were reviewed according to eligibility and exclusion criteria. Publication bias and heterogeneity between studies were assessed. Pooled summary estimates for sensitivity, specificity, and area under the curve were obtained for each parameter by using a bivariate model. A subanalysis investigated the effect of MRI parameters on diagnostic performance by using a Student t test or a one-way analysis of variance. Results From 73 eligible studies, 6791 lesions (3930 malignant and 2861 benign) were included. Publication bias was evident for studies that evaluated apparent diffusion coefficient (ADC). Significant heterogeneity (P < .05) was present for all parameters except the perfusion fraction (f). The pooled sensitivity, specificity, and area under the curve for ADC was 89%, 82%, and 0.92, respectively. The highest performing parameter for DTI was the prime diffusion coefficient (λ1), and pooled sensitivity, specificity, and area under the curve was 93%, 90%, and 0.94, respectively. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity, specificity, and area under the curve was 88%, 79%, and 0.90. Choice of MRI parameters had no significant effect on diagnostic performance. Conclusion Diffusion-weighted imaging, diffusion-tensor imaging, and intravoxel incoherent motion have comparable diagnostic accuracy with high sensitivity and specificity. Intravoxel incoherent motion is comparable to apparent diffusion coefficient. Diffusion-tensor imaging is potentially promising but to date the number of studies is limited. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Gabrielle C Baxter
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Martin J Graves
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Fiona J Gilbert
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
| | - Andrew J Patterson
- From the Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, England (G.C.B., F.J.G.); and Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England (M.J.G., A.J.P.)
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Onodera K, Hatakenaka M, Yama N, Onodera M, Saito T, Kwee TC, Takahara T. Repeatability analysis of ADC histogram metrics of the uterus. Acta Radiol 2019; 60:526-534. [PMID: 29969050 DOI: 10.1177/0284185118786062] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Recently, histogram analysis based on voxel-wise apparent diffusion coefficient (ADC) value distribution has been increasingly performed. However, few studies have been reported regarding its repeatability. PURPOSE To evaluate the repeatability of ADC histogram metrics of the uterus in clinical magnetic resonance imaging (MRI). MATERIAL AND METHODS Thirty-three female patients who underwent pelvic MRI including diffusion-weighted imaging (DWI) were prospectively included after providing informed consent. Two sequential DWI acquisitions with identical parameters and position were obtained. Regions of interest (ROIs) for histologically confirmed uterine lesions (five cervical and three endometrial cancers, and one endometrial hyperplasia) and normal appearing tissues (21 endometrium and 33 myometrium) were assigned on the first DWI dataset and then pasted onto the second DWI dataset. ADC histogram metrics within the ROIs were calculated and repeatability was evaluated by calculating within-subject coefficient of variance (%) (wCV (%)) and Bland-Altman plot (%). RESULTS ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy showed high repeatability (wCV (%) < 7, 95% limit of agreement in Bland-Altman plot (%) < ±20), followed by ADC minimum (wCV (%) = 8.12, 95% limit of agreement in Bland-Altman plot (%) < ±30). However, ADC skewness and kurtosis showed very low repeatability in all evaluations. CONCLUSION ADC histogram metrics like ADC 10%, 25%, median, 75%, 90%, maximum, mean, and entropy are robust biomarkers and could be applicable to clinical use. However, ADC skewness and kurtosis lack robustness. Radiologists should keep these characteristics and limitations in mind when interpreting quantitative DWI.
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Affiliation(s)
- Koichi Onodera
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | | | - Naoya Yama
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | - Maki Onodera
- Department of Diagnostic Radiology, Sapporo Medical University, Sapporo, Japan
| | - Tsuyoshi Saito
- Department of Obstetrics and Gynecology, Sapporo Medical University, Sapporo, Japan
| | - Thomas Christian Kwee
- Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Taro Takahara
- Department of Biomedical Engineering, School of Engineering, Tokai University, Hiratsuka, Japan
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Jin YN, Zhang Y, Cheng JL, Zheng DD, Hu Y. Monoexponential, Biexponential, and stretched-exponential models using diffusion-weighted imaging: A quantitative differentiation of breast lesions at 3.0T. J Magn Reson Imaging 2019; 50:1461-1467. [PMID: 30919518 DOI: 10.1002/jmri.26729] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2018] [Revised: 03/11/2019] [Accepted: 03/12/2019] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Diffusion-weighted imaging (DWI) plays an important role in the differentiation of malignant and benign breast lesions. PURPOSE To investigate the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched-exponential DWI models in the differential diagnosis of breast lesions. STUDY TYPE Prospective. POPULATION Sixty-one patients (age range: 25-68 years old; mean age: 46 years old) with 31 malignant lesions, 42 benign lesions, and 28 normal breast tissues diagnosed initially by clinical palpation, ultrasonography, or conventional mammography were enrolled in the study from January to September 2016. FIELD STRENGTH 3.0T MR scanner, T1 WI, T2 WI, DWI (conventional and multi-b values), dynamic contrast-enhanced. ASSESSMENT The apparent diffusion coefficient (ADC) was calculated by monoexponential analysis. The diffusion coefficient (ADCslow ), pseudodiffusion coefficient (ADCfast ), and perfusion fraction (f) were calculated using the biexponential model. The distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) were obtained using a stretched-exponential model. All parameters were compared for malignant tumors, benign tumors, and normal breast tissues. A receiver operating characteristic curve was used to compare the ability of these parameters, in order to differentiate benign and malignant breast lesions. STATISTICAL TESTS All statistical analyses were performed using statistical software (SPSS). RESULTS ADC, ADCslow , f, DDC, and α values were significantly lower in malignant tumors when compared with normal breast tissues and benign tumors (P < 0.05). However, ADC and f had higher area under the receiver operating characteristic curve (AUC) values (0.889 and 0.919, respectively). DATA CONCLUSION The parameters derived from the biexponential and stretched-exponential DWI could provide additional information for differentiating between benign and malignant breast tumors when compared with conventional diffusion parameters. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;50:1461-1467.
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Affiliation(s)
- Ya-Nan Jin
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Zhang
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing-Liang Cheng
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Ying Hu
- Department of Magnetic Resonance Imaging, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zaric O, Farr A, Poblador Rodriguez E, Mlynarik V, Bogner W, Gruber S, Asseryanis E, Singer CF, Trattnig S. 7T CEST MRI: A potential imaging tool for the assessment of tumor grade and cell proliferation in breast cancer. Magn Reson Imaging 2019; 59:77-87. [PMID: 30880110 DOI: 10.1016/j.mri.2019.03.004] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 03/03/2019] [Accepted: 03/04/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVES To investigate the feasibility of chemical exchange saturation transfer (CEST) MRI in patients with breast carcinomas and possible correlations between magnetization transfer asymmetry (MTRasym) values and histological features, such as tumor grade and the Ki-67 proliferation index. MATERIALS AND METHODS Nine healthy subjects and 18 female patients were enrolled for this study. The imaging protocol for the patients consisted of diffusion-weighted imaging (DWI), CEST imaging, and T1-weighted, contrast-enhanced (CE)-MRI. CEST was performed using a 3D gradient echo (GRE) sequence, employing eight pre-saturation pulses of a duration of 50 ms and a duty cycle (DC) of 80%, with a mean amplitude of the saturation pulse train of 1 μT. The Z-spectrum was plotted and MTRasym values calculated for the frequency of the maximum of MTRasym curve, were correlated with the Ki-67 proliferation index and apparent diffusion coefficient (ADC). Patient data were statistically assessed using the Games-Howell post-hoc and Pearson's correlation test. RESULTS Different tumor types had asymmetry peaks at different positions of Z-spectrum. MTRasym (mean ± SD) (%) calculated for G1 (3.0 ± 0.3; range: 2.70-3.50) was not significantly lower than for G2 (4.50 ± 1.30; range: 3.20-6.50; p = 0.066). In contrast, the increase in MTRasym between G1 and G3 (6.40 ± 1.70; range: 4.80-9.80) lesions was significant (p = 0.007). No significant difference was observed between G2 and G3 with regard to MTRasym (p = 0.089). There was a strong positive correlation between the MTRasym, and Ki-67 proliferation index (r = 0.890; p = 0.001), while there was a moderate negative correlation between MTRasym and ADC values (r = -0.506; p = 0.027). CONCLUSIONS Calculated MTRasym demonstrates a strong positive correlation with tumor proliferation and has the potential to become a valuable biomarker for breast tumor characterization.
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Affiliation(s)
- Olgica Zaric
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alex Farr
- Breast Health Centre, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria.
| | - Esau Poblador Rodriguez
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Vladimir Mlynarik
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Gesellschaft, St. Pölten, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ella Asseryanis
- Breast Health Centre, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - Christian F Singer
- Breast Health Centre, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Christian Doppler Forschungsgesellschaft, Vienna, Austria
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Cavallo Marincola B, Telesca M, Zaccagna F, Riemer F, Anzidei M, Catalano C, Pediconi F. Can unenhanced MRI of the breast replace contrast-enhanced MRI in assessing response to neoadjuvant chemotherapy? Acta Radiol 2019; 60:35-44. [PMID: 29742918 DOI: 10.1177/0284185118773512] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The goals of neoadjuvant chemotherapy (NAC) are to reduce tumor volume and to offer a prognostic indicator in assessing treatment response. Contrast-enhanced magnetic resonance imaging (CE-MRI) is an established method for evaluating response to NAC in patients with breast cancer. PURPOSE To validate the role of unenhanced MRI (ue-MRI) compared to CE-MRI for assessing response to NAC in women with breast cancer. MATERIAL AND METHODS Seventy-one patients with ongoing NAC for breast cancer underwent MRI before, during, and at the end of NAC. Ue-MRI was performed with T2-weighted sequences with iterative decomposition of water and fat and diffusion-weighted sequences. CE-MRI was performed using three-dimensional T1-weighted sequences before and after administration of gadobenate dimeglumine. Two blinded observers rated ue-MRI and CE-MRI for the evaluation of tumor response. Statistical analysis was performed to compare lesion size and ADC values changes during therapy, as well as inter-observer agreement. RESULTS There were no statistically significant differences between ue-MRI and CE-MRI sequences for evaluation of lesion size at baseline and after every cycle of treatment ( P > 0.05). The mean tumor ADC values at baseline and across the cycles of NAC were significantly different for the responder group. CONCLUSION Ue-MRI can achieve similar results to CE-MRI for the assessment of tumor response to NAC. ADC values can differentiate responders from non-responders.
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Affiliation(s)
- Beatrice Cavallo Marincola
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Marianna Telesca
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Fulvio Zaccagna
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Frank Riemer
- Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Michele Anzidei
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
| | - Federica Pediconi
- Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy
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Inglese M, Cavaliere C, Monti S, Forte E, Incoronato M, Nicolai E, Salvatore M, Aiello M. A multi-parametric PET/MRI study of breast cancer: Evaluation of DCE-MRI pharmacokinetic models and correlation with diffusion and functional parameters. NMR IN BIOMEDICINE 2019; 32:e4026. [PMID: 30379384 DOI: 10.1002/nbm.4026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Revised: 09/04/2018] [Accepted: 09/11/2018] [Indexed: 06/08/2023]
Abstract
46 patients with histologically confirmed breast cancer were enrolled and imaged with a 3T hybrid PET/MRI system, at staging. Diffusion, functional and perfusion parameters (measured by Tofts and shutter speed models) were compared. Results showed a good correlation between pharmacokinetic parameters and the SUV.
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Affiliation(s)
- Marianna Inglese
- IRCCS SDN, Naples, Italy
- Department of Computer, Control and Management Engineering Antonio Ruberti, University of Rome 'La Sapienza', Italy
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Gity M, Moradi B, Arami R, Arabkheradmand A, Kazemi MA. Two Different Methods of Region-of-Interest Placement for Differentiation of Benign and Malignant Breast Lesions by Apparent Diffusion Coefficient Value. Asian Pac J Cancer Prev 2018; 19:2765-2770. [PMID: 30360604 PMCID: PMC6291064 DOI: 10.22034/apjcp.2018.19.10.2765] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Purpose: We aimed to investigate the influence of different methods of region-of-interest (ROI) placement on apparent diffusion coefficient (ADC) values in breast tumours and their accuracy in differentiating benign versus malignant tumors in mass and nonmass lesions. Methods and Materials: In this prospective study, 79 patients with 98 breast lesions, from 2015 until 2017, were investigated by 1.5-T breast MRI. Histopathology evaluation were done for all malignant lesions and most of the benign ones. ADC values were measured in normal breast tissue and by two ways of ROI placement in the breast lesions (mass and non-mass): 1- ROI covering the whole lesion, 2- ROI in the highest part (most restricted area) of the lesion in DWI images. The accuracy of these two approaches were compared. Results: The age range was 17-68 years with mean age 43.3 ± 9.9 years. 49% of the lesions were benign and 51% of tumors were malignant. Our results revealed that the measured ADC values in normal breast tissue were higher than breast lesions (P≤0.01). Appropriate cut off determination in non-mass was not valid by both methods, but in mass in the first way was 1.45×10-3mm2/s and in the most restricted part was 1.16×10-3 mm2/s. ADC values differed significantly between the two ways of ROI placement in mass lesions (P<.001). Most restricted part ADC showed the best diagnostic performance in mass lesions with area under curve 0.88 versus 0.82. Conclusion: ROI placement has significant impact on the meseaured ADC values of breast lesions and ROIs in most restricted parts were more accurate than whole-lesion ROIs. Cut-off values differed significantly based on the methods of measurement.
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Affiliation(s)
- Masoumeh Gity
- Department of Radiology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
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Archer BJ, Uberruck T, Mack JJ, Youssef K, Jarenwattananon NN, Rall D, Wypysek D, Wiese M, Blumich B, Wessling M, Iruela-Arispe ML, Bouchard LS. Noninvasive Quantification of Cell Density in Three-Dimensional Gels by MRI. IEEE Trans Biomed Eng 2018; 66:821-830. [PMID: 30028689 DOI: 10.1109/tbme.2018.2857443] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
OBJECTIVE For tissue engineering, there is a need for quantitative methods to map cell density inside three-dimensional (3-D) bioreactors to assess tissue growth over time. The current cell mapping methods in 2-D cultures are based on optical microscopy. However, optical methods fail in 3-D due to increased opacity of the tissue. We present an approach for measuring the density of cells embedded in a hydrogel to generate quantitative maps of cell density in a living, 3-D tissue culture sample. METHODS Quantification of cell density was obtained by calibrating the 1H T2, magnetization transfer (MT) and diffusion-weighted nuclear magnetic resonance (NMR) signals to samples of known cell density. Maps of cell density were generated by weighting NMR images by these parameters post-calibration. RESULTS The highest sensitivity weighting arose from MT experiments, which yielded a limit of detection (LOD) of [Formula: see text] cells/mL/ √{Hz} in a 400 MHz (9.4 T) magnet. CONCLUSION This mapping technique provides a noninvasive means of visualizing cell growth within optically opaque bioreactors. SIGNIFICANCE We anticipate that such readouts of tissue culture growth will provide valuable feedback for controlled cell growth in bioreactors.
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Combined apparent diffusion coefficient value (ADC) and 1H magnetic resonance spectroscopy (MRS) in breast lesions: Benefits and limitations. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2017.11.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Shi RY, Yao QY, Wu LM, Xu JR. Breast Lesions: Diagnosis Using Diffusion Weighted Imaging at 1.5T and 3.0T—Systematic Review and Meta-analysis. Clin Breast Cancer 2018; 18:e305-e320. [DOI: 10.1016/j.clbc.2017.06.011] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 05/20/2017] [Accepted: 06/24/2017] [Indexed: 12/26/2022]
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Jiang X, Xie F, Liu L, Peng Y, Cai H, Li L. Discrimination of malignant and benign breast masses using automatic segmentation and features extracted from dynamic contrast-enhanced and diffusion-weighted MRI. Oncol Lett 2018; 16:1521-1528. [PMID: 30008832 PMCID: PMC6036451 DOI: 10.3892/ol.2018.8805] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 04/21/2017] [Indexed: 12/16/2022] Open
Abstract
Magnetic resonance imaging exhibits high sensitivity but low specificity for breast cancer. The present study aimed to investigate whether combining morphology, texture features and kinetic features with diffusion-weighted imaging using quantitative analysis improves the accuracy of discriminating malignant from benign breast masses. In total, 104 and 171 malignant lesions in 205 women were included. Additionally, 13 texture and 11 morphology features were computed from each lesion using a semi-automated segmentation method. To increase prediction accuracy, a newly designed classification model, difference-weighted local hyperplane, was used for statistical analysis of the combined effects of the features for predicting lesion type. The mean apparent diffusion coefficient (ADC) value for each lesion was calculated. Diagnostic performances of morphology and texture features, kinetic features and ADC alone and the combination of them were evaluated using receiver operating characteristics analysis. Malignant lesions had lower mean ADCs than benign lesions. By using 10-fold cross validation scheme, combined morphological and kinetic features achieved a diagnostic average accuracy of 0.87. Adding an ADC threshold of 1.37×10−3 mm2/sec increased the overall averaged accuracy to 0.90. A multivariate model combining ADC values with 6 morphological and kinetic parameters best discriminated malignant from benign lesions. Incorporating morphology and texture features, kinetic features and ADC into a multivariable diagnostic model improves the discriminatory power of breast lesions.
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Affiliation(s)
- Xinhua Jiang
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
| | - Fei Xie
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
| | - Lizhi Liu
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
| | - Yanxia Peng
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, P.R. China
| | - Hongmin Cai
- Department of Computer Science, School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong 510006, P.R. China
| | - Li Li
- Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
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Diagnostic Usefulness of Combination of Diffusion-weighted Imaging and T2WI, Including Apparent Diffusion Coefficient in Breast Lesions: Assessment of Histologic Grade. Acad Radiol 2018; 25:643-652. [PMID: 29339079 DOI: 10.1016/j.acra.2017.11.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Revised: 10/31/2017] [Accepted: 11/10/2017] [Indexed: 01/13/2023]
Abstract
PURPOSE This study aimed to compare the diagnostic values of a combination of diffusion-weighted imaging and T2-weighted imaging (DWI-T2WI) with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and to evaluate the correlation of DWI with the histologic grade in breast cancer. MATERIALS AND METHODS This study evaluated a total of 169 breast lesions from 136 patients who underwent both DCE-MRI and DWI (b value, 1000s/mm2). Morphologic and kinetic analyses for DCE-MRI were classified according to the Breast Imaging-Reporting and Data System. For the DWI-T2WI set, a DWI-T2WI score for lesion characterization that compared signal intensity of DWI and T2WI (benign: DWI-T2WI score of 1, 2; malignant: DWI-T2WI score of 3, 4, 5) was used. The diagnostic values of DCE-MRI, DWI-T2WI set, and combined assessment of DCE and DWI-T2WI were calculated. RESULTS Of 169 breast lesions, 48 were benign and 121 were malignant (89 invasive ductal carcinoma, 24 ductal carcinoma in situ, 4 invasive lobular carcinoma, 4 mucinous carcinoma). The mean apparent diffusion coefficient (ADC) of invasive ductal carcinoma (0.92 ± 0.19 × 10-3 mm2/s) and ductal carcinoma in situ (1.11 ± 0.13 × 10-3 mm2/s) was significantly lower than the value seen in benign lesions (1.36 ± 0.22 × 10-3 mm2/s). The specificity, positive predictive value (PPV), and accuracy of DWI-T2WI set and combined assessment of DCE and DWI-T2WI (specificity, 87.5% and 91.7%; PPV, 94.3% and 96.2%; accuracy, Az = 0.876 and 0.922) were significantly higher than those of the DCE-MRI (specificity, 45.8%; PPV, 81.7%; accuracy, Az = 0.854; P < .05). A low ADC value and the presence of rim enhancement were associated with a higher histologic grade cancer (P < .05). CONCLUSION Combining DWI, T2WI, and ADC values provides increased accuracy for differentiation between benign and malignant lesions, compared with DCE-MRI. A lower ADC value was associated with a higher histologic grade cancer.
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Kim SY, Shin J, Kim DH, Kim EK, Moon HJ, Yoon JH, You JK, Kim MJ. Correlation between electrical conductivity and apparent diffusion coefficient in breast cancer: effect of necrosis on magnetic resonance imaging. Eur Radiol 2018; 28:3204-3214. [DOI: 10.1007/s00330-017-5291-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 12/10/2017] [Accepted: 12/27/2017] [Indexed: 11/28/2022]
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Yilmaz R, Bayramoglu Z, Kartal MG, Çaliskan E, Salmaslıoglu A, Dursun M, Acunas G. Stromal fibrosis: imaging features with diagnostic contribution of diffusion-weighted MRI. Br J Radiol 2018; 91:20170706. [PMID: 29388800 DOI: 10.1259/bjr.20170706] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To describe magnetic resonance imaging (MRI) and ultrasonography findings of breast stromal fibrosis (SF) and compare apparent diffusion coefficient (ADC) stromal fibrosis values with breast cancer and normal parenchyma. METHODS 45 patients (ages 22‒74) with histopathologically proven SF who underwent MRI were included in this study. Their MRI and ultrasonography features were examined and categorized. The mean ADC values for SF, contralateral normal parenchyma, and breast malignancy of the control group values were calculated and compared among each other. RESULTS The vast majority of SF on sonography showed features suggestive of malignancy: (1) irregular in shape 25/45 (55%); (2) indistinct in margin 27/45 (60%); and (3) hypoechoic 39/45 (87%) with posterior acoustic shadowing 11/45 (24%). An SF MRI showed a mass in 12/45 (26%) and non-mass enhancement in 33/45 (74%), mostly with irregular (8/12; 67%) shape. Non-mass lesions showed heterogeneous (12/33), clumped (9/33), and homogenous (9/33) enhancement. The initial SF contrast uptake rate varied between slow (57%), rapid (22%), and medium (21%). Delayed SF enhancement may be persistent (66%) or plateau (34%). Small cysts were located around/near 21 (47%) of lesions. Ductal ectasia was found in 14 (31%) of all patients. Mean ADCs of parenchyma, SF, and malignancy were 1.32 ± 0.32, 1.23 ± 0.25, and 0.99 ± 0.24 × 10-3 mm2 sec-1, respectively. CONCLUSION SF often mimics breast carcinoma on imaging and leads the radiology‒pathology disagreement. In terms of distinguishing SF from malignancy, ADC could be a significant and promising value in diffusion-weighted MRI along with conventional sequences. Slow initial uptake with delayed persistent contrast enhancement in a non-mass lesion with relatively higher ADC values are very helpful for differentiating SF from malignancy. The presence of small cysts and ductal ectasia were common findings around/near the SF. Advances in knowledge: A quantitative analysis for measuring ADC values along with additional MRI features can be very helpful in distinguishing SF from malignant lesions.
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Affiliation(s)
- Ravza Yilmaz
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Zuhal Bayramoglu
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Merve Gulbiz Kartal
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Emine Çaliskan
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Artur Salmaslıoglu
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Memduh Dursun
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
| | - Gulden Acunas
- 1 Department of Radiology, Istanbul University, Istanbul Faculty of Medicine , Fatih, Istanbul , Turkey
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Yılmaz R, Bayramoğlu Z, Emirikçi S, Önder S, Salmaslıoğlu A, Dursun M, Acunaş G, Özmen V. MR Imaging Features of Tubular Carcinoma: Preliminary Experience in Twelve Masses. Eur J Breast Health 2018; 14:39-45. [PMID: 29322118 DOI: 10.5152/ejbh.2017.3543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 06/26/2017] [Indexed: 11/22/2022]
Abstract
Objective We retrospectively analyzed the magnetic resonance (MR) imaging features and diffusion-weighted imaging findings of the 12 masses of 10 patients with tubular carcinoma (TC), including mammography and sonography findings. Materials and Methods Mammographic, sonographic and magnetic resonance imaging features in 12 histopathologically confirmed masses diagnosed as TC of the breast within 10 patients were evaluated. Morphologic characteristics, enhancement features, apparent diffusion coefficient (ADC) values were reviewed. Results On mammography (n=5), TC appeared as high density masses with indistinct, spiculated or obscured margins. Sonographically, TC appeared as a hypoechoic appearance (n=12) with posterior acoustic shadowing in nine. On MR imaging, the margins of ten of twelve masses were irregular. Internal enhancement patterns were heterogeneous in 10 patients. Dynamic enhancement patterns illustrated plateau kinetics (n=8). On the T2-weighted images 4 masses were hypointense, and 8 were hyperintense; hypointense internal septation was found in seven of these. Tubular carcinoma appeared as hyperintense on diffusion-weighted imaging with ADC values of 0.85±0.16×10-3 mm2/s that was lower than the normal parenchyma of 1.25±0.25×10-3 mm2/s. Conclusion According to our study with a limited number of cases, tubular carcinomas can be described as hyperintense breast carcinomas with or without dark internal septation like appearance on T2-weighted images. Low ADC values from DW imaging can be used to differentiate TC from hyperintense benign breast lesions.
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Affiliation(s)
- Ravza Yılmaz
- Department of Radiology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Zuhal Bayramoğlu
- Department of Radiology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Selman Emirikçi
- Department of General Surgery, İstanbul University School of Medicine, İstanbul, Turkey
| | - Semen Önder
- Department of Pathology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Artur Salmaslıoğlu
- Department of Radiology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Memduh Dursun
- Department of Radiology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Gülden Acunaş
- Department of Radiology, İstanbul University School of Medicine, İstanbul, Turkey
| | - Vahit Özmen
- Department of General Surgery, İstanbul University School of Medicine, İstanbul, Turkey
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Chu W, Jin W, Liu D, Wang J, Geng C, Chen L, Huang X. Diffusion-weighted imaging in identifying breast cancer pathological response to neoadjuvant chemotherapy: A meta-analysis. Oncotarget 2017; 9:7088-7100. [PMID: 29467952 PMCID: PMC5805538 DOI: 10.18632/oncotarget.23195] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 12/01/2017] [Indexed: 12/20/2022] Open
Abstract
Background Diffusion-weighted imaging (DWI) is increasingly used to identify pathological complete responses (pCRs) to neoadjuvant chemotherapy (NAC) in breast cancer. The aim of the present study was to assess the utility of DWI using a pooled analysis. Materials and Methods Literature databases were searched prior to July 2017. Fifteen studies with a total of 1181 patients were included. The data were extracted to perform pooled analysis, heterogeneity testing, threshold effect testing, sensitivity analysis, publication bias analysis and subgroup analyses. Result The methodological quality was moderate. Remarkable heterogeneity was detected, primarily due to a threshold effect. The pooled weighted values were a sensitivity of 0.88 (95% confidence interval (CI): 0.81, 0.92), a specificity of 0.79 (95% CI: 0.70, 0.86), a positive likelihood ratio of 4.1 (95% CI: 2.9, 5.9), a negative likelihood ratio of 0.16 (95% CI: 0.10, 0.24), and a diagnostic odds ratio of 26 (95% CI: 15, 46). The area under the receiver operator characteristic curve was 0.91 (95% CI: 0.88, 0.93). In the subgroup analysis, the pooled specificity of change in the apparent diffusion coefficient (ADC) subgroup was higher than that in the pre-treatment ADC subgroup (0.80 [95% CI: 0.71, 087] vs. 0.63 [95% CI: 0.52, 0.73], P = 0.027). Conclusions DWI may be an accurate and nonradioactive imaging technique for identifying pCRs to NAC in breast cancer. Nonetheless, there are a variety of issues when assessing DWI techniques for estimating breast cancer responses to NAC, and large scale and well-designed clinical trials are needed to assess the technique's diagnostic value.
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Affiliation(s)
- Wei Chu
- Department of Radiology, Wuxi Huishan District People's Hospital, Jiangsu Province, 214187, China
| | - Weiwei Jin
- Department of Radiology, Wuxi Second Traditional Chinese Medicine Hospital, Jiangsu Province, 214121, China
| | - Daihong Liu
- Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
| | - Chengjun Geng
- Department of Radiology, PLA No.101 Hospital, Wuxi, Jiangsu Province, 214044, China
| | - Lihua Chen
- Department of Radiology, PLA No.101 Hospital, Wuxi, Jiangsu Province, 214044, China
| | - Xuequan Huang
- Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China
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Zhang L, Zhuang L, Shi C, Miao Y, Zhang W, Song Q, Kang J, Lang Z, Xin X, Liu A, Hu J. A pilot evaluation of magnetic resonance imaging characteristics seen with solid papillary carcinomas of the breast in 4 patients. BMC Cancer 2017; 17:525. [PMID: 28784112 PMCID: PMC5547522 DOI: 10.1186/s12885-017-3518-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 08/01/2017] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Solid papillary carcinoma (SPC) is a rare variant of breast papillary carcinoma with unique pathological morphology and biological behavior. There is only one case report on T1-MRI of SPC. In this study, we report our findings on this new category of papillary carcinoma to fill the gap in MRI characterization of SPC. METHODS This retrospective study included four pathology-confirmed in situ SPC patients. Conventional MRI, diffusion weighted imaging (DWI), and magnetic resonance spectroscopy (MRS) were performed with a 1.5 T whole-body MR scanner before surgical operation. The following characteristics of each lesion were recorded: signal intensity on T2WI/STIR and T1FSPGR, morphology, maximum lesion size, and time intensity curve (TIC) on dynamic contrast enhancement MRI (DCE-MRI), apparent diffusion coefficient (ADC) value from DWI, and Cho peak from MRS. RESULTS Signal intensities of all lesions were heterogenous on T2WI/STIR and T1FSPGR. Mass enhancements were observed for all lesions with either oval or irregular shapes on DCE-MRI. The maximum lesion size ranged from 0.8 cm to 3.2 cm. All lesion margins were circumscribed, and internal enhancements were homogeneous or heterogeneous from DCE-MRI. TIC appeared with a rapid increase in initial contrast phases of all lesions. All lesions on DWI (b = 1000s/mm2) were slightly hyperintense with an ADC value range of 1.3 × 10-3 mm2/s to 1.9 × 10-3 mm2/s. Cho peak was absent at 3.2 ppm for all lesions. CONCLUSIONS MRI characteristics of SPC include heterogeneous signal intensity within the lesion on T2WI/STIR and T1FSPGR, mass enhancement with circumscribed margins, either oval or irregular shapes, and a rapid initial enhancement of TIC on DCE-MRI. ADC values and the absence of Cho peak may provide valuable information to distinguish SPC from other invasive breast carcinomas.
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Affiliation(s)
- Lina Zhang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Ling Zhuang
- Department of Oncology, Wayne State University School of Medicine, Detroit, USA
| | - Chang Shi
- Department of Pathology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Weisheng Zhang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Jianyun Kang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Zhijin Lang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Xuegang Xin
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Ailian Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China.
| | - Jiani Hu
- Department of Radiology, Wayne State University, Detroit, USA.
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Choi BB, Kim SH, Park CS, Jung NY. Correlation of Prognostic Factors of Invasive Lobular Carcinoma with ADC Value of DWI and SUVMax of FDG-PET. Chonnam Med J 2017; 53:133-139. [PMID: 28584792 PMCID: PMC5457948 DOI: 10.4068/cmj.2017.53.2.133] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 04/06/2017] [Accepted: 04/13/2017] [Indexed: 12/24/2022] Open
Abstract
Invasive lobular carcinoma (ILC) is the second most common kind of breast cancer. Diffusion weighted imaging (DWI) and positron emission tomography/computed tomography (PET/CT) are functional modalities for presenting the biological characteristics of breast cancer. The purpose of this article is to study the relationship between DWI or PET/CT and ILC's prognostic factors. The relationship between the apparent diffusion coefficient (ADC) values, standard uptake value (SUV)max and prognostic factors of ILC were statistically evaluated. The ADC values were lower in mass types of ILC. SUVmax was statistically higher in grade 3 and 4 background parenchymal enhancement and positive lymph node metastasis. ADC values of DWI and SUVmax of PET/CT can be helpful in the prediction of the prognosis of ILC.
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Affiliation(s)
- Bo Bae Choi
- Department of Radiology, Chungnam University Hospital, Daejeon, Korea
| | - Sung Hun Kim
- Department of Radiology, Seoul St. Mary' Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Chang Suk Park
- Department of Radiology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Incheon, Korea
| | - Na Young Jung
- Department of Radiology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Bucheon, Korea
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Surov A, Meyer HJ, Wienke A. Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget 2017; 8:59492-59499. [PMID: 28938652 PMCID: PMC5601748 DOI: 10.18632/oncotarget.17752] [Citation(s) in RCA: 234] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 04/27/2017] [Indexed: 01/29/2023] Open
Abstract
The purpose of this meta-analysis was to provide clinical evidence regarding relationship between ADC and cellularity in different tumors based on large patient data. Medline library was screened for associations between ADC and cell count in different tumors up to September 2016. Only publications in English were extracted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) was used for the research. Overall, 39 publications with 1530 patients were included into the analysis. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. The pooled correlation coefficient for all studies was ρ = -0.56 (95 % CI = [−0.62; −0.50]),. Correlation coefficients ranged from ρ =−0.25 (95 % CI = [−0.63; 0.12]) in lymphoma to ρ=−0.66 (95 % CI = [−0.85; −0.47]) in glioma. Other coefficients were as follows: ovarian cancer, ρ = −0.64 (95% CI = [−0.76; −0.52]); lung cancer, ρ = −0.63 (95 % CI = [−0.78; −0.48]); uterine cervical cancer, ρ = −0.57 (95 % CI = [−0.80; −0.34]); prostatic cancer, ρ = −0.56 (95 % CI = [−0.69; −0.42]); renal cell carcinoma, ρ = −0.53 (95 % CI = [−0.93; −0.13]); head and neck squamous cell carcinoma, ρ = −0.53 (95 % CI = [-0.74; −0.32]); breast cancer, ρ = −0.48 (95 % CI = [−0.74; −0.23]); and meningioma, ρ = -0.45 (95 % CI = [−0.73; −0.17]).
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Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany
| | - Andreas Wienke
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
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Durur-Subasi I, Durur-Karakaya A, Karaman A, Seker M, Demirci E, Alper F. Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions? Br J Radiol 2017; 90:20160803. [PMID: 28339285 DOI: 10.1259/bjr.20160803] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE To determine whether the necrosis/wall apparent diffusion coefficient (ADC) ratio is useful for the malignant-benign differentiation of necrotic breast lesions. METHODS Breast MRI was performed using a 3-T system. In this retrospective study, calculation of the necrosis/wall ADC ratio was based on ADC values measured from the necrosis and from the wall of malignant and benign breast lesions by diffusion-weighted imaging (DWI). By synchronizing post-contrast T1 weighted images, the separate parts of wall and necrosis were maintained. All the diagnoses were pathologically confirmed. Statistical analyses were conducted using an independent sample t-test and receiver operating characteristic analysis. The intraclass and interclass correlations were evaluated. RESULTS A total of 66 female patients were enrolled, 38 of whom had necrotic breast carcinomas and 28 of whom had breast abscesses. The ADC values were obtained from both the wall and necrosis. The mean necrosis/wall ADC ratio (± standard deviation) was 1.61 ± 0.51 in carcinomas, and it was 0.65 ± 0.33 in abscesses. The area under the curve values for necrosis ADC, wall ADC and the necrosis/wall ADC ratio were 0.680, 0.068 and 0.942, respectively. A wall/necrosis ADC ratio cut-off value of 1.18 demonstrated a sensitivity of 97%, specificity of 93%, a positive-predictive value of 95%, a negative-predictive value of 96% and an accuracy of 95% in determining the malignant nature of necrotic breast lesions. There was a good intra- and interclass reliability for the ADC values of both necrosis and wall. CONCLUSION The necrosis/wall ADC ratio appears to be a reliable and promising tool for discriminating breast carcinomas from abscesses using DWI. Advances in knowledge: ADC values of the necrosis obtained by DWI are valuable for malignant-benign differentiation in necrotic breast lesions. The necrosis/wall ADC ratio appears to be a reliable and promising tool in the breast imaging field.
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Affiliation(s)
- Irmak Durur-Subasi
- 1 Department of Radiology, Diskapi Yildirim Beyazit Training and Research Hospital, Ankara, Turkey
| | - Afak Durur-Karakaya
- 2 Department of Radiology, Faculty of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Adem Karaman
- 3 Department of Radiology, Faculty of Medicine, Ataturk University, Erzurum, Turkey
| | - Mehmet Seker
- 2 Department of Radiology, Faculty of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Elif Demirci
- 4 Department of Pathology, Faculty of Medicine, Ataturk University, Erzurum, Turkey
| | - Fatih Alper
- 3 Department of Radiology, Faculty of Medicine, Ataturk University, Erzurum, Turkey
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Bailey C, Siow B, Panagiotaki E, Hipwell JH, Mertzanidou T, Owen J, Gazinska P, Pinder SE, Alexander DC, Hawkes DJ. Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study. NMR IN BIOMEDICINE 2017; 30:e3679. [PMID: 28000292 PMCID: PMC5244665 DOI: 10.1002/nbm.3679] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 11/06/2016] [Accepted: 11/07/2016] [Indexed: 05/17/2023]
Abstract
The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.
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Affiliation(s)
- Colleen Bailey
- University College LondonCentre for Medical Image ComputingLondonUK
| | - Bernard Siow
- University College LondonCentre for Advanced Biomedical ImagingLondonUK
| | | | - John H. Hipwell
- University College LondonCentre for Medical Image ComputingLondonUK
| | | | - Julie Owen
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | - Patrycja Gazinska
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | - Sarah E. Pinder
- King's College LondonGuy's Hospital, Breast ResearchPathologyLondonUK
| | | | - David J. Hawkes
- University College LondonCentre for Medical Image ComputingLondonUK
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Wilmes LJ, Li W, Shin HJ, Newitt DC, Proctor E, Harnish R, Hylton NM. Diffusion Tensor Imaging for Assessment of Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer. ACTA ACUST UNITED AC 2016. [PMID: 29527574 PMCID: PMC5844277 DOI: 10.18383/j.tom.2016.00271] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before treatment and after 3 cycles of taxane-based therapy (early treatment). Tumor fractional anisotropy (FA), principal eigenvalues (λ1, λ2, and λ3), and apparent diffusion coefficient (ADC) were estimated for tumor regions of interest drawn on DTI data. The association between DTI metrics and final tumor volume change was evaluated with Spearman rank correlation. DTI metrics were investigated as predictors of pathological complete response (pCR) by calculating the area under the receiver operating characteristic curve (AUC). Early changes in tumor FA and ADC significantly correlated with final tumor volume change post therapy (ρ = -0.38, P = .03 and ρ = -0.71, P < .001, respectively). Pretreatment tumor ADC was significantly lower in the pCR than in the non-pCR group (P = .04). At early treatment, patients with pCR had significantly higher percent changes of tumor λ1, λ2, λ3, and ADC than those without pCR. The AUCs for early percent changes in tumor FA and ADC were 0.60 and 0.83, respectively. The early percent changes in tumor eigenvalues and ADC were the strongest DTI-derived predictors of pCR. Although early percent change in tumor FA had a weak association with pCR, the significant correlation with final tumor volume change suggests that this metric changes with therapy and may merit further evaluation.
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Affiliation(s)
- Lisa J Wilmes
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Medical Imaging Laboratory, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
| | - David C Newitt
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Evelyn Proctor
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Roy Harnish
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California
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Lee YJ, Kim SH, Kang BJ, Kang YJ, Yoo H, Yoo J, Lee J, Son YH, Grimm R. Intravoxel incoherent motion (IVIM)‐derived parameters in diffusion‐weighted MRI: Associations with prognostic factors in invasive ductal carcinoma. J Magn Reson Imaging 2016; 45:1394-1406. [DOI: 10.1002/jmri.25514] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 10/05/2016] [Indexed: 12/26/2022] Open
Affiliation(s)
- Youn Joo Lee
- Department of RadiologyDaejeon St. Mary's HospitalSeoul Republic of Korea
| | - Sung Hun Kim
- Seoul St. Mary's HospitalSeoul Republic of Korea
| | | | - Young Jee Kang
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Heesoo Yoo
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Jaewan Yoo
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
| | - Jaeun Lee
- College of MedicineThe Catholic University of KoreaSeoul Republic of Korea
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Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer. Eur Radiol 2016; 27:1901-1911. [PMID: 27651141 PMCID: PMC5374186 DOI: 10.1007/s00330-016-4565-2] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Accepted: 08/11/2016] [Indexed: 12/27/2022]
Abstract
Objective To explore the predictive value of parameters derived from diffusion-weighted imaging (DWI) and contrast-enhanced (CE)-MRI at different time-points during neoadjuvant chemotherapy (NACT) in breast cancer. Methods Institutional review board approval and written, informed consent from 42 breast cancer patients were obtained. The patients were investigated before and at three different time-points during neoadjuvant chemotherapy (NACT) using tumour diameter and volume from CE-MRI and ADC values obtained from drawn 2D and segmented 3D regions of interest. Prediction of pathologic complete response (pCR) was evaluated using the area under the curve (AUC) of receiver operating characteristic analysis. Results There was no significant difference between pathologic complete response and non-pCR in baseline size measures (p > 0.39). Diameter change was significantly different in pCR (p < 0.02) before the mid-therapy point. The best predictor was lesion diameter change observed before mid-therapy (AUC = 0.93). Segmented volume was not able to differentiate between pCR and non-pCR at any time-point. The ADC values from 3D-ROI were not significantly different from 2D data (p = 0.06). The best AUC (0.79) for pCR prediction using DWI was median ADC measured before mid-therapy of NACT. Conclusions The results of this study should be considered in NACT monitoring planning, especially in MRI protocol designing and time point selection. Key Points • Mid-therapy diameter changes are the best predictors of pCR in neoadjuvant chemotherapy. • Volumetric measures are not strictly superior in therapy monitoring to lesion diameter. • Size measures perform as a better predictor than ADC values.
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Bickel H, Pinker K, Polanec S, Magometschnigg H, Wengert G, Spick C, Bogner W, Bago-Horvath Z, Helbich TH, Baltzer P. Diffusion-weighted imaging of breast lesions: Region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values. Eur Radiol 2016; 27:1883-1892. [DOI: 10.1007/s00330-016-4564-3] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 08/11/2016] [Indexed: 01/01/2023]
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46
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Magnetic resonance imaging features of idiopathic granulomatous mastitis: is there any contribution of diffusion-weighted imaging in the differential diagnosis? Radiol Med 2016; 121:857-866. [DOI: 10.1007/s11547-016-0666-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2016] [Accepted: 06/22/2016] [Indexed: 10/21/2022]
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47
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Hahn SY, Ko ES, Han BK, Lim Y, Gu S, Ko EY. Analysis of factors influencing the degree of detectability on diffusion-weighted MRI and diffusion background signals in patients with invasive breast cancer. Medicine (Baltimore) 2016; 95:e4086. [PMID: 27399100 PMCID: PMC5058829 DOI: 10.1097/md.0000000000004086] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
To determine the factors influencing the degree of detectability of lesions and diffusion background signals on magnetic resonance diffusion-weighted imaging (DWI) in invasive breast cancer.Institutional review board approval was obtained and patient consent was waived. Patients with newly diagnosed invasive ductal carcinoma, who underwent preoperative breast magnetic resonance imaging with DWI were included in this study (n = 167). Lesion detectability on DWI and contrast-enhanced subtracted T1-weighted images, the degree of background parenchymal enhancement (BPE), and diffusion background signal were qualitatively rated. Detectability of lesions on DWI was compared with clinicopathological findings including menopausal status, mammographic density, and molecular subtype of breast cancer. Multivariate linear regression analysis was performed to determine variables independently associated with detectability of lesions on DWI and diffusion background signals.Univariate analysis showed that the detectability of lesions on DWI was significantly associated with lesion size (P = 0.001), diffuse background signal (P < 0.0001), and higher detectability scores for contrast-enhanced T1-weighted subtraction images (P = 0.000). The degree of diffusion background signal was significantly affected by age (P < 0.0001), BPE (P < 0.0001), mammographic density (P = 0.002), and menopausal status (P < 0.0001). On multivariate analysis, the diffusion background signal (P < 0.0001) and histologic grade (P < 0.0001) were correlated with the detectability on DWI of invasive breast cancer. Only BPE was correlated with the amount of diffusion background signal on DWI (P < 0.0001).For invasive breast cancers, detectability on DWI was significantly affected by the diffusion background signal. BPE, menopausal status, menstrual cycle, or mammographic density did not show statistically significant correlation with the diffusion detectability of lesions on DWI.
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Affiliation(s)
- Soo Yeon Hahn
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Eun Sook Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Boo-Kyung Han
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
| | - Yaeji Lim
- Department of Statistics, Pukyong National University, Busan
| | - Seonhye Gu
- Biostatistics and Clinical Epidemiology Center, Samsung Medical Center, Seoul, Korea
| | - Eun Young Ko
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul
- Correspondence: Eun Sook Ko, Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea (e-mail: )
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Akın Y, Uğurlu MÜ, Kaya H, Arıbal E. Diagnostic Value of Diffusion-weighted Imaging and Apparent Diffusion Coefficient Values in the Differentiation of Breast Lesions, Histpathologic Subgroups and Correlatıon with Prognostıc Factors using 3.0 Tesla MR. THE JOURNAL OF BREAST HEALTH 2016; 12:123-132. [PMID: 28331748 DOI: 10.5152/tjbh.2016.2897] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 02/09/2016] [Indexed: 11/22/2022]
Abstract
OBJECTIVE The aim of this study was to evaluate the effect of the apparent diffusion coefficient (ADC) and diffusion-weighted imaging in differentiating benign from malignant breast lesions, histopathologic subtypes of breast tumors, and to find a correlation with prognostic factors using 3T MR. MATERIALS AND METHODS A total of 165 patients aged between 16 and 78 years with 181 histopathologically-verifed breast lesions were enrolled in this study. A 3T MR system and bilateral phased array breast coil was used. Diffusion-weighted imaging was performed with spin echo "echo planar" with "b" values: 50, 400, and 800 seconds/mm2. ADC values were calculated for normal fibroglandular tissue and breast lesions. ADC values of independent groups were compared using Student's t-test. ROC analysis was used to find a threshold ADC value in the differentiation of lesions. RESULTS The mean ADC values were 1.35±0.16 × 10-3 mm2/s for normal fibroglandular tissue, 1.41±0.24 × 10-3 mm2/s for benign breast lesions and 0.83±0.19 × 10-3 mm2/s for malignant breast lesions. The AUC with ROC analysis was 0.945 and the threshold for ADC was 1.08 × 10-3 mm2/s with a sensitivity and specificity of 92% and 92%, respectively. The threshold value for ADC ratio was 0.9 with 96% sensitivity and 89% specificity. The mean ADC of malignant breast lesions was statistically lower for benign lesions (p<0.01). We found no correlation between the mean ADC values and ER-PR receptor, Her2, and Ki-67 values. CONCLUSION Diffusion-weighted imaging has high diagnostic value with high sensitivity and specificity in differentiating malignant and benign breast lesions.
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Affiliation(s)
- Yasin Akın
- Department of Radiology, Marmara University School of Medicine, İstanbul, Turkey
| | - M Ümit Uğurlu
- Department of General Surgery, Marmara University School of Medicine, İstanbul, Turkey
| | - Handan Kaya
- Department of Pathology, Marmara University School of Medicine, istanbul, Turkey
| | - Erkin Arıbal
- Department of Radiology, Marmara University School of Medicine, İstanbul, Turkey
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Jiang R, Ma Z, Dong H, Sun S, Zeng X, Li X. Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity. Br J Radiol 2016; 89:20160076. [PMID: 27302492 DOI: 10.1259/bjr.20160076] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To investigate the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) measured by diffusion tensor imaging (DTI), tissue cellularity and their relationship in breast malignant/benign lesions. METHODS 88 patients with 88 breast lesions who underwent DTI and dynamic contrast-enhanced MR scanning between November 2013 and December 2014 were retrospectively analyzed. The diagnosis was confirmed pathologically. ADC and FA values as well as histopathological cellularity of different pathological types of lesions were analyzed and compared statistically. The Pearson's correlation between cellularity and ADC and FA was calculated. RESULTS There were 59 cases of breast cancer and 29 cases of benign lesions included in the study. ADC values of breast cancers were statistically lower than that of benign lesions (p < 0.001). FA and cellularity were higher in cancers than in benign lesions with statistical significance (p < 0.05 and p < 0.001, respectively). The mean FA values in the patients with invasive ductal carcinoma (IDC) were higher than that in the patients with ductal carcinoma in situ (DCIS) without statistical difference (p > 0.05). The ADC and the cellularity in the IDC of grade III were statistically lower (p < 0.05) and higher (p < 0.05) than that in the DCIS and IDC of grade I-II, respectively. ADC was negatively correlated to cellularity (r = -0.8319, p < 0.001) and FA was positively correlated to cellularity (r = 0.4231, p < 0.001). CONCLUSION ADC and FA values were statistically different between benign and malignant breast lesions and were significantly correlated to tissue cellularity. ADC and FA may help to discriminate malignant from benign breast lesions and to predict cellularity. ADC is helpful in the prediction of the grade of breast cancer. ADVANCES IN KNOWLEDGE ADC and FA values were statistically different between benign and malignant breast lesions and were significantly correlated to tissue cellularity.
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Affiliation(s)
- Ruisheng Jiang
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Zhijun Ma
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Haixia Dong
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Shihang Sun
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Xiangmin Zeng
- 1 Department of Computer Tomography and Magnetic Resonance Imaging, Weifang Medical College Affiliated Yidu Central Hospital, Weifang, China
| | - Xiao Li
- 2 Medical Imaging Center, Linyi People's Hospital, Linyi, China
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Sharma U, Sah RG, Agarwal K, Parshad R, Seenu V, Mathur SR, Hari S, Jagannathan NR. Potential of Diffusion-Weighted Imaging in the Characterization of Malignant, Benign, and Healthy Breast Tissues and Molecular Subtypes of Breast Cancer. Front Oncol 2016; 6:126. [PMID: 27242965 PMCID: PMC4876309 DOI: 10.3389/fonc.2016.00126] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 05/09/2016] [Indexed: 12/26/2022] Open
Abstract
The role of apparent diffusion coefficient (ADC) in the diagnosis of breast cancer and its association with molecular biomarkers was investigated in 259 patients with breast cancer, 67 with benign pathology, and 54 healthy volunteers using diffusion-weighted imaging (DWI) at 1.5 T. In 59 breast cancer patients, dynamic contrast-enhanced MRI (DCEMRI) was also acquired. Mean ADC of malignant lesions was significantly lower (1.02 ± 0.17 × 10−3 mm2/s) compared to benign (1.57 ± 0.26 × 10−3 mm2/s) and healthy (1.78 ± 0.13 × 10−3 mm2/s) breast tissues. A cutoff ADC value of 1.23 × 10−3 mm2/s (sensitivity 92.5%; specificity 91.1%; area under the curve 0.96) to differentiate malignant from benign diseases was arrived by receiver operating curve analysis. In 10/59 breast cancer patients, indeterminate DCE curve was seen, while their ADC value was indicative of malignancy, implying the potential of the addition of DWI in increasing the specificity of DCEMRI data. Further, the association of ADC with tumor volume, stage, hormonal receptors [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor (HER2)], and menopausal status was investigated. A significant difference was seen in tumor volume between breast cancer patients of stages IIA and IIIA, IIB and IIIA, and IIB and III (B + C), respectively (P < 0.05). Patients with early breast cancer (n = 52) had significantly lower ADC and tumor volume than those with locally advanced breast cancer (n = 207). No association was found in ADC and tumor volume with the menopausal status. Breast cancers with ER−, PR−, and triple-negative (TN) status showed a significantly larger tumor volume compared to ER+, PR+, and non-triple-negative (nTN) cancers, respectively. Also, TN tumors showed a significantly higher ADC compared to ER+, PR+, and nTN cancers. Patients with ER− and TN cancers were younger than those with ER+ and nTN cancers. The present study demonstrated that ADC may increase the diagnostic specificity of DCEMRI and be useful for treatment management in clinical setting. Additionally, it provides an insight into characterization of molecular types of breast cancer and may serve as an indicator of metabolic reprograming underlying tumor proliferation.
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Affiliation(s)
- Uma Sharma
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences , New Delhi , India
| | - Rani G Sah
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences , New Delhi , India
| | - Khushbu Agarwal
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences , New Delhi , India
| | - Rajinder Parshad
- Department of Surgical Disciplines, All India Institute of Medical Sciences , New Delhi , India
| | - Vurthaluru Seenu
- Department of Surgical Disciplines, All India Institute of Medical Sciences , New Delhi , India
| | - Sandeep R Mathur
- Department of Pathology, All India Institute of Medical Sciences , New Delhi , India
| | - Smriti Hari
- Department of Radiodiagnosis, All India Institute of Medical Sciences , New Delhi , India
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