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Daboudi M, Papadaki E, Vakis A, Chlouverakis G, Makrakis D, Karageorgou D, Simos P, Koukouraki S. Brain SPECT and perfusion MRI: do they provide complementary information about the tumour lesion and its grading? Clin Radiol 2019; 74:652.e1-652.e9. [PMID: 31164195 DOI: 10.1016/j.crad.2019.03.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 03/22/2019] [Indexed: 10/26/2022]
Abstract
AIM To evaluate the relative and combined utility of 99mTc-tetrofosmin (99mTc-TF) brain single-photon-emission computed tomography (SPECT) and dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) in grading brain gliomas. MATERIALS AND METHODS Thirty-six patients with clinically suspected brain tumours were assessed by 99mTc-TF SPECT and DSC-MRI. Brain tumour malignancy was confirmed in all patients at histopathology. On both techniques brain lesions were evaluated via visual and semi-quantitative analysis methods (deriving tetrofosmin index [T-index] and relative cerebral blood volume [rCBV] ratios, respectively). RESULTS 99mTc-TF SPECT showed abnormally elevated tracer uptake in 31/36 patients whereas MRI detected the brain tumour in all patients. Optimal cut-off values of each index for discriminating between low- and high-grade gliomas were obtained through receiver operating characteristic (ROC) analyses. A T-index cut-off of 6.35 ensured 82% sensitivity and 71% specificity for discriminating between high- and low-grade gliomas, whereas a relative rCBV ratio cut-off of 1.80 achieved 91% sensitivity and 100% specificity. Requiring a positive result on either technique to characterise a high-grade glioma was associated with similar specificity and slightly increased sensitivity. CONCLUSION Both imaging techniques, 99mTF SPECT and DSC MRI, may provide complementary indices of tumour grade and have an independent diagnostic value for high-risk tumours.
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Affiliation(s)
- M Daboudi
- Department of Nuclear Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece.
| | - E Papadaki
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece; Institute of Computer Science, Foundation of Research and Technology, Heraklion, Crete, Greece
| | - A Vakis
- Department of Neurosurgery, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - G Chlouverakis
- Biostatistics Lab., Department of Social and Family Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - D Makrakis
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - D Karageorgou
- Department of Radiology, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - P Simos
- Institute of Computer Science, Foundation of Research and Technology, Heraklion, Crete, Greece; Department of Psychiatry, School of Medicine, University of Crete, Heraklion, Crete, Greece
| | - S Koukouraki
- Department of Nuclear Medicine, School of Medicine, University of Crete, Heraklion, Crete, Greece
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Lund KV, Simonsen TG, Kristensen GB, Rofstad EK. Pharmacokinetic analysis of DCE-MRI data of locally advanced cervical carcinoma with the Brix model. Acta Oncol 2019; 58:828-837. [PMID: 30810443 DOI: 10.1080/0284186x.2019.1580386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background: There is significant evidence that DCE-MRI may have the potential to provide clinically useful biomarkers of the outcome of locally advanced cervical carcinoma. However, there is no consensus on how to analyze DCE-MRI data to arrive at the most powerful biomarkers. The purpose of this study was to analyze DCE-MRI data of cervical cancer patients by using the Brix pharmacokinetic model and to compare the biomarkers derived from the Brix analysis with biomarkers determined by non-model-based analysis [i.e., low-enhancing tumor volume (LETV) and tumor volume with increasing signal (TVIS)] of the same patient cohort. Material and methods: DCE-MRI recordings of 80 patients (FIGO stage IB-IVA) treated with concurrent cisplatin-based chemoradiotherapy were analyzed voxel-by-voxel, and frequency distributions of the three parameters of the Brix model (ABrix, kep, and kel) were determined. Moreover, risk volumes were calculated from the Brix parameters and termed RV-ABrix, RV-kep, and RV-kel, where the RVs represent the tumor volume with voxel values below a threshold value determined by ROC analysis. Disease-free survival (DFS) and overall survival (OS) were used as measures of treatment outcome. Results: Significant associations between the median value or any other percentile value of ABrix, kep, or kel and treatment outcome were not found. However, RV-ABrix, RV-kep, and RV-kel correlated with DFS and OS. Multivariate analysis revealed that the prognostic power of RV-ABrix, RV-kep, and RV-kel was independent of well-established clinical prognostic factors. RV-ABrix, RV-kep, and RV-kel correlated with each other as well as with LETV and TVIS. Conclusion: Strong biomarkers of the outcome of locally advanced cervical carcinoma can be provided by subjecting DCE-MRI series to pharmacokinetic analysis using the Brix model. The prognostic power of these biomarkers is not necessarily superior to that of biomarkers identified by non-model-based analyses.
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Affiliation(s)
- Kjersti V. Lund
- Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Trude G. Simonsen
- Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Gunnar B. Kristensen
- Department of Gynecological Cancer, Oslo University Hospital, Oslo, Norway
- Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway
| | - Einar K. Rofstad
- Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
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Arasu VA, Miglioretti DL, Sprague BL, Alsheik NH, Buist DS, Henderson LM, Herschorn SD, Lee JM, Onega T, Rauscher GH, Wernli KJ, Lehman CD, Kerlikowske K. Population-Based Assessment of the Association Between Magnetic Resonance Imaging Background Parenchymal Enhancement and Future Primary Breast Cancer Risk. J Clin Oncol 2019; 37:954-963. [PMID: 30625040 PMCID: PMC6494266 DOI: 10.1200/jco.18.00378] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
PURPOSE To evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk. PATIENTS AND METHODS We examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression. RESULTS Among 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80% v 66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio [HR], 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (P = .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05). CONCLUSION BPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.
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Affiliation(s)
- Vignesh A. Arasu
- Kaiser Permanente Medical Center, Vallejo, CA
- University of California, San Francisco, San Francisco, CA
| | - Diana L. Miglioretti
- University of California, Davis, Davis, CA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
| | - Brian L. Sprague
- University of Vermont Cancer Center, University of Vermont, Burlington, VT
| | | | - Diana S.M. Buist
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
| | | | - Sally D. Herschorn
- University of Vermont Cancer Center, University of Vermont, Burlington, VT
| | - Janie M. Lee
- University of Washington, and Seattle Cancer Care Alliance, Seattle, WA
| | - Tracy Onega
- Norris Cotton Cancer Center and Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Garth H. Rauscher
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL
| | - Karen J. Wernli
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA
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Song SE, Cho KR, Seo BK, Woo OH, Jung SP, Sung DJ. Kinetic Features of Invasive Breast Cancers on Computer-Aided Diagnosis Using 3T MRI Data: Correlation with Clinical and Pathologic Prognostic Factors. Korean J Radiol 2019; 20:411-421. [PMID: 30799572 PMCID: PMC6389817 DOI: 10.3348/kjr.2018.0587] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 11/30/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate the correlation of kinetic features of breast cancers on computer-aided diagnosis (CAD) of preoperative 3T magnetic resonance imaging (MRI) data and clinical-pathologic factors in breast cancer patients. MATERIALS AND METHODS Between July 2016 and March 2017, 85 patients (mean age, 54 years; age range, 35-81 years) with invasive breast cancers (mean, 1.8 cm; range, 0.8-4.8 cm) who had undergone MRI and surgery were retrospectively enrolled. All magnetic resonance images were processed using CAD, and kinetic features of tumors were acquired. The relationships between kinetic features and clinical-pathologic factors were assessed using Spearman correlation test and binary logistic regression analysis. RESULTS Peak enhancement and angio-volume were significantly correlated with histologic grade, Ki-67 index, and tumor size: r = 0.355 (p = 0.001), r = 0.330 (p = 0.002), and r = 0.231 (p = 0.033) for peak enhancement, r = 0.410 (p = 0.005), r = 0.341 (p < 0.001), and r = 0.505 (p < 0.001) for angio-volume. Delayed-plateau component was correlated with Ki-67 (r = 0.255 [p = 0.019]). In regression analysis, higher peak enhancement was associated with higher histologic grade (odds ratio [OR] = 1.004; 95% confidence interval [CI]: 1.001-1.008; p = 0.024), and higher delayed-plateau component and angio-volume were associated with higher Ki-67 (Or = 1.051; 95% CI: 1.011-1.094; p = 0.013 for delayed-plateau component, OR = 1.178; 95% CI: 1.023-1.356; p = 0.023 for angio-volume). CONCLUSION Of the CAD-assessed kinetic features, higher peak enhancement may correlate with higher histologic grade, and higher delayed-plateau component and angio-volume correlate with higher Ki-67 index. These results support the clinical application of kinetic features in prognosis assessment.
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Affiliation(s)
- Sung Eun Song
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Kyu Ran Cho
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea.
| | - Bo Kyoung Seo
- Department of Radiology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Ok Hee Woo
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Seung Pil Jung
- Department of Surgery, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Deuk Jae Sung
- Department of Radiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
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Toxicity Evaluation of a Novel Magnetic Resonance Imaging Marker, CoCl2-N-Acetylcysteine, in Rats. J Toxicol 2019; 2018:9173452. [PMID: 30631353 PMCID: PMC6304599 DOI: 10.1155/2018/9173452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 08/31/2018] [Accepted: 10/16/2018] [Indexed: 11/18/2022] Open
Abstract
C4 (cobalt dichloride-N-acetylcysteine [1% CoCl2:2% NAC]) is a novel magnetic resonance imaging contrast marker that facilitates visualization of implanted radioactive seeds in cancer brachytherapy. We evaluated the toxicity of C4. Rats were assigned to control (0% CoCl2:NAC), low-dose (0.1% CoCl2:2% NAC), reference-dose (C4), and high-dose (10% CoCl2:2% NAC) groups. Agent was injected into the left quadriceps femoris muscle of the rats. Endpoints were organ and body weights, hematology, and serum chemistry and histopathologic changes of tissues at 48 hours and 28 and 63 days after dosing. Student's t tests were used. No abnormalities in clinical signs, terminal body and organ weights, or hematologic and serum chemistry were noted, and no gross or histopathologic lesions of systemic tissue toxicity were found in any treatment group at any time point studied. At the site of injection, concentration-dependent acute responses were observed in all treatment groups at 48 hours after dosing and were recovered by 28 days. No myofiber degeneration or necrosis was observed at 28 or 63 days in any group. In conclusion, a single intramuscular dose of C4 produced no acute or chronic systemic toxicity or inflammation in rats, suggesting that C4 may be toxicologically safe for clinical use in cancer brachytherapy.
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Kim S, Lee HJ, Ko KH, Park AY, Koh J, Jung HK. New Doppler imaging technique for assessing angiogenesis in breast tumors: correlation with immunohistochemically analyzed microvessels density. Acta Radiol 2018; 59:1414-1421. [PMID: 29667882 DOI: 10.1177/0284185118769690] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Microvessel density (MVD) is associated with grade and prognosis in breast tumors. However, conventional color Doppler flow (CDF) imaging has been limited to represent MVD of breast tumors. PURPOSE To evaluate whether a new Doppler imaging technique (AngioPLUS) can represent MVD of breast tumors. MATERIAL AND METHODS The institutional review board approved this retrospective study, and patients' informed consent was waived. CDF and AngioPLUS were available in pathologically confirmed 55 breast tumors of 53 women. For each lesion, vascular flow patterns (distribution and amount) of both Doppler images were retrospectively reviewed, and MVD was measured using immunohistochemical analysis of the biopsied tissue sections. MVD was subcategorized as low or high group with reference to the median. The associations between the Doppler features and MVD were evaluated using Fisher's exact test and Student's t test. RESULTS Of the 55 masses, 28 (50.9%) were benign and 27 (49.1%) were malignant. Vascular flow distribution and amount of both Doppler imaging were different between the benign and malignant lesions (CDF, P = 0.020 and P = 0.010; AngioPLUS, P = 0.002 and P = 0.005). MVD had no significant relationships with CDF features, but vascular flow distribution on AngioPLUS showed significant differences between the lesions with low and high MVD ( P = 0.020); Combined distribution was more frequent in the high MVD lesions than in the low MVD lesions (17/28, 60.7% vs. 6/27, 22.2%). CONCLUSION Our data confirmed the correlation between a new Doppler imaging technique, AngioPLUS, and MVD. We suggest that AngioPLUS can be used for assessing MVD in breast tumors.
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Affiliation(s)
- Sewha Kim
- Department of Pathology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
| | - Hye Jin Lee
- Department of Pathology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
| | - Kyung Hee Ko
- Department of Radiology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
| | - Ah Young Park
- Department of Radiology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
| | - Jieun Koh
- Department of Radiology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
| | - Hae Kyoung Jung
- Department of Radiology, CHA Bundang Medical Center, CHA University, Seongnam-si, Republic of Korea
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Gallego-Ortiz C, Martel AL. A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions. Med Image Anal 2018; 51:116-124. [PMID: 30412826 DOI: 10.1016/j.media.2018.10.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 09/28/2018] [Accepted: 10/30/2018] [Indexed: 10/27/2022]
Abstract
Nonmass-like enhancements are a common but diagnostically challenging finding in breast MRI. Nonmass-like lesions can be described as clusters of spatially and temporally inter-connected regions of enhancements, so they can be modeled as networks and their properties characterized via network-based connectivity. In this work, we represented nonmass lesions as graphs using a link formation energy model that favors linkages between regions of similar enhancement and closer spatial proximity. However, adding graph features to an existing computer-aided diagnosis (CAD) pipeline incurs an increase of feature space dimensionality, which poses additional challenges to traditional supervised machine learning techniques due to the inability to increase accordingly the number of training datasets. We propose the combination of unsupervised dimensionality reduction and embedded space clustering followed by a supervised classifier to improve the performance of a CAD system for nonmass-like lesions in breast MRI. Our work extends a previoulsy proposed framework for deep embedded unsupervised clustering (DEC) to embedding space classification, with the joint optimization of objective functions for DEC and supervised multi-layered perceptron (MLP) classification. The strength of the method lies in the ability to learn and further optimize an embedded feature representation of lower dimensionality that maximizes the diagnostic accuracy of a CAD lesion classifier to discriminate between benign and malignant lesions. We identified 792 nonmass-like enhancements (267 benign, 110 malignant and 415 unknown) in 411 patients undergoing breast MRI at our institution. The diagnostic performance of the proposed method was evaluated and compared to the performance of a conventional supervised MLP classifier in original feature space. A statistically significant increase in diagnostic area under the ROC curve (AUC) was achieved. Generalization AUC increased from 0.67 ± 0.08 to 0.81 ± 0.10 (21% increase, p-value=4.2×10-8) with the proposed graph-based lesion characterization and deep embedding framework.
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Affiliation(s)
- Cristina Gallego-Ortiz
- Department of Medical Biophysics, University of Toronto, Canada; Department of Imaging Research, Sunnybrook Research Institute, Toronto, Canada.
| | - Anne L Martel
- Department of Medical Biophysics, University of Toronto, Canada; Department of Imaging Research, Sunnybrook Research Institute, Toronto, Canada
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Dynamic Contrast-Enhanced Imaging as a Prognostic Tool in Early Diagnosis of Prostate Cancer: Correlation with PSA and Clinical Stage. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:3181258. [PMID: 30327584 PMCID: PMC6169212 DOI: 10.1155/2018/3181258] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 07/22/2018] [Indexed: 02/08/2023]
Abstract
Background and Purpose Although several methods have been developed to predict the outcome of patients with prostate cancer, early diagnosis of individual patient remains challenging. The aim of the present study was to correlate tumor perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical prognostic factors and further to explore the diagnostic value of DCE-MRI parameters in early stage prostate cancer. Patients and Methods Sixty-two newly diagnosed patients with histologically proven prostate adenocarcinoma were enrolled in our prospective study. Transrectal ultrasound-guided biopsy (12 cores, 6 on each lobe) was performed in each patient. Pathology was reviewed and graded according to the Gleason system. DCE-MRI was performed and analyzed using a two-compartmental model; quantitative parameters including volume transfer constant (Ktrans), reflux constant (Kep), and initial area under curve (iAUC) were calculated from the tumors and correlated with prostate-specific antigen (PSA), Gleason score, and clinical stage. Results Ktrans (0.11 ± 0.02 min−1 versus 0.16 ± 0.06 min−1; p < 0.05), Kep (0.38 ± 0.08 min−1 versus 0.60 ± 0.23 min−1; p < 0.01), and iAUC (14.33 ± 2.66 mmoL/L/min versus 17.40 ± 5.97 mmoL/L/min; p < 0.05) were all lower in the clinical stage T1c tumors (tumor number, n=11) than that of tumors in clinical stage T2 (n=58). Serum PSA correlated with both tumor Ktrans (r=0.304, p < 0.05) and iAUC (r=0.258, p < 0.05). Conclusions Our study has confirmed that DCE-MRI is a promising biomarker that reflects the microcirculation of prostate cancer. DCE-MRI in combination with clinical prognostic factors may provide an effective new tool for the basis of early diagnosis and treatment decisions.
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Goldenberg JM, Pagel MD, Cárdenas-Rodríguez J. Characterization of D-maltose as a T 2 -exchange contrast agent for dynamic contrast-enhanced MRI. Magn Reson Med 2018; 80:1158-1164. [PMID: 29369407 PMCID: PMC6010162 DOI: 10.1002/mrm.27082] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 12/15/2017] [Accepted: 12/18/2017] [Indexed: 01/14/2023]
Abstract
Purpose We sought to investigate the potential of D-maltose, D-sorbitol, and D-mannitol as T2 exchange magnetic resonance imaging (MRI) contrast agents. We also sought to compare the in vivo pharmacokinetics of D-maltose with D-glucose with dynamic contrast enhancement (DCE) MRI. Methods T1 and T2 relaxation time constants of the saccharides were measured using eight pH values and nine concentrations. The effect of echo spacing in a multiecho acquisition sequence used for the T2 measurement was evaluated for all samples. Finally, performances of D-maltose and D-glucose during T2-weighted DCE-MRI were compared in vivo. Results Estimated T2 relaxivities (r2) of D-glucose and D-maltose were highly and nonlinearly dependent on pH and echo spacing, reaching their maximum at pH=7.0 (~0.08mM−1 s−1). The r2 values of D-sorbitol and D-mannitol were estimated to be ~0.02mM−1 s−1 and were invariant to pH and echo spacing for pH ≤7.0. The change in T2 in tumor and muscle tissues remained constant after administration of D-maltose, whereas the change in T2 decreased in tumor and muscle after administration of D-glucose. Therefore, D-maltose has a longer time window for T2-weighted DCE-MRI in tumors. Conclusion We have demonstrated that D-maltose can be used as a T2 exchange MRI contrast agent. The larger, sustained T2-weighted contrast from D-maltose relative to D-glucose has practical advantages for tumor diagnoses during T2-weighted DCE-MRI.
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Affiliation(s)
- Joshua M. Goldenberg
- Department of Pharmaceutical Sciences, University of Arizona, Tucson, Arizona, USA
- Department of Cancer Systems Imaging, University of Texas M.D., Anderson Cancer Center, Houston, Texas, USA
| | - Mark D. Pagel
- Department of Cancer Systems Imaging, University of Texas M.D., Anderson Cancer Center, Houston, Texas, USA
| | - Julio Cárdenas-Rodríguez
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
- University of Arizona Cancer Center, University of Arizona, Tucson, Arizona, USA
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Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients. Eur Radiol 2018; 28:4705-4716. [PMID: 29736850 PMCID: PMC6182741 DOI: 10.1007/s00330-018-5470-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 03/19/2018] [Accepted: 04/10/2018] [Indexed: 10/24/2022]
Abstract
OBJECTIVES To assess whether contralateral parenchymal enhancement reproduces as an independent biomarker for patient survival in an independent patient cohort from a different cancer institution. METHODS This is a HIPAA-compliant IRB approved retrospective study. Patients with ER-positive/HER2-negative operable invasive ductal carcinoma and preoperative dynamic contrast-enhanced MRI were consecutively included between 2005 and 2009. The parenchyma of the breast contralateral to known cancer was segmented automatically on MRI and contralateral parenchymal enhancement (CPE) was calculated. CPE was split into tertiles and tested for association with invasive disease-free survival (IDFS) and overall survival (OS). Propensity score analysis with inverse probability weighting (IPW) was used to adjust CPE for patient and tumour characteristics as well as systemic therapy. RESULTS Three hundred and two patients were included. The median age at diagnosis was 48 years (interquartile range, 42-57). Median follow-up was 88 months (interquartile range, 76-102); 15/302 (5%) patients died and 37/302 (13%) had a recurrence or died. In context of multivariable analysis, IPW-adjusted CPE was associated with IDFS [hazard ratio (HR) = 0.27, 95% confidence interval (CI) = 0.05-0.68, p = 0.004] and OS (HR = 0.22, 95% CI = 0.00-0.83, p = 0.032). CONCLUSIONS Contralateral parenchymal enhancement on pre-treatment dynamic contrast-enhanced MRI as an independent biomarker of survival in patients with ER-positive/HER2-negative breast cancer has been upheld in this study. These findings are a promising next step towards a practical and inexpensive test for risk stratification of ER-positive/HER2-negative breast cancer. KEY POINTS • High parenchymal-enhancement in the disease-free contralateral breast reproduces as biomarker for survival. • This is in patients with ER-positive/HER2-negative breast cancer from an independent cancer centre. • This is independent of patient and pathology parameters and systemic therapy.
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Wu J, Cao G, Sun X, Lee J, Rubin DL, Napel S, Kurian AW, Daniel BL, Li R. Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy. Radiology 2018; 288:26-35. [PMID: 29714680 DOI: 10.1148/radiol.2018172462] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Purpose To characterize intratumoral spatial heterogeneity at perfusion magnetic resonance (MR) imaging and investigate intratumoral heterogeneity as a predictor of recurrence-free survival (RFS) in breast cancer. Materials and Methods In this retrospective study, a discovery cohort (n = 60) and a multicenter validation cohort (n = 186) were analyzed. Each tumor was divided into multiple spatially segregated, phenotypically consistent subregions on the basis of perfusion MR imaging parameters. The authors first defined a multiregional spatial interaction (MSI) matrix and then, based on this matrix, calculated 22 image features. A network strategy was used to integrate all image features and classify patients into different risk groups. The prognostic value of imaging-based stratification was evaluated in relation to clinical-pathologic factors with multivariable Cox regression. Results Three intratumoral subregions with high, intermediate, and low MR perfusion were identified and showed high consistency between the two cohorts. Patients in both cohorts were stratified according to network analysis of multiregional image features regarding RFS (log-rank test, P = .002 for both). Aggressive tumors were associated with a larger volume of the poorly perfused subregion as well as interaction between poorly and moderately perfused subregions and surrounding parenchyma. At multivariable analysis, the proposed MSI-based marker was independently associated with RFS (hazard ratio: 3.42; 95% confidence interval: 1.55, 7.57; P = .002) adjusting for age, estrogen receptor (ER) status, progesterone receptor status, human epidermal growth factor receptor type 2 (HER2) status, tumor volume, and pathologic complete response (pCR). Furthermore, imaging helped stratify patients for RFS within the ER-positive and HER2-positive subgroups (log-rank test, P = .007 and .004) and among patients without pCR after neoadjuvant chemotherapy (log-rank test, P = .003). Conclusion Breast cancer consists of multiple spatially distinct subregions. Imaging heterogeneity is an independent prognostic factor beyond traditional risk predictors.
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Affiliation(s)
- Jia Wu
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Guohong Cao
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Xiaoli Sun
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Juheon Lee
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Daniel L Rubin
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Sandy Napel
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Allison W Kurian
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Bruce L Daniel
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
| | - Ruijiang Li
- From the Departments of Radiation Oncology (J.W., J.L., R.L.), Radiology (D.L.R., S.N., B.L.D.), Biomedical Data Science and Medicine (Biomedical Informatics Research) (D.L.R.), Medicine (A.W.K.), and Health Research and Policy (A.W.K.) and the Stanford Cancer Institute (A.W.K., R.L.), Stanford University School of Medicine, 1070 Arastradero Rd, Palo Alto, CA 94304; Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China (G.C.); and Department of Radiation Therapy, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China (X.S.)
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Monti S, Aiello M, Incoronato M, Grimaldi AM, Moscarino M, Mirabelli P, Ferbo U, Cavaliere C, Salvatore M. DCE-MRI Pharmacokinetic-Based Phenotyping of Invasive Ductal Carcinoma: A Radiomic Study for Prediction of Histological Outcomes. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:5076269. [PMID: 29581709 PMCID: PMC5822818 DOI: 10.1155/2018/5076269] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 11/20/2017] [Accepted: 12/18/2017] [Indexed: 12/23/2022]
Abstract
Breast cancer is a disease affecting an increasing number of women worldwide. Several efforts have been made in the last years to identify imaging biomarker and to develop noninvasive diagnostic tools for breast tumor characterization and monitoring, which could help in patients' stratification, outcome prediction, and treatment personalization. In particular, radiomic approaches have paved the way to the study of the cancer imaging phenotypes. In this work, a group of 49 patients with diagnosis of invasive ductal carcinoma was studied. The purpose of this study was to select radiomic features extracted from a DCE-MRI pharmacokinetic protocol, including quantitative maps of ktrans, kep, ve, iAUC, and R1 and to construct predictive models for the discrimination of molecular receptor status (ER+/ER-, PR+/PR-, and HER2+/HER2-), triple negative (TN)/non-triple negative (NTN), ki67 levels, and tumor grade. A total of 163 features were obtained and, after feature set reduction step, followed by feature selection and prediction performance estimations, the predictive model coefficients were computed for each classification task. The AUC values obtained were 0.826 ± 0.006 for ER+/ER-, 0.875 ± 0.009 for PR+/PR-, 0.838 ± 0.006 for HER2+/HER2-, 0.876 ± 0.007 for TN/NTN, 0.811 ± 0.005 for ki67+/ki67-, and 0.895 ± 0.006 for lowGrade/highGrade. In conclusion, DCE-MRI pharmacokinetic-based phenotyping shows promising for discrimination of the histological outcomes.
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Affiliation(s)
| | | | | | | | | | | | - Umberto Ferbo
- Department of Pathology, Ospedale Moscati, Avellino, Italy
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63
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Lewis H, Ghasabeh M, Khoshpouri P, Kamel I, Pawlik T. Functional hepatic imaging as a biomarker of primary and secondary tumor response to loco-regional therapies. Surg Oncol 2017; 26:411-422. [DOI: 10.1016/j.suronc.2017.08.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 08/21/2017] [Indexed: 02/06/2023]
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64
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Banerjee I, Malladi S, Lee D, Depeursinge A, Telli M, Lipson J, Golden D, Rubin DL. Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging. J Med Imaging (Bellingham) 2017; 5:011008. [PMID: 29134191 DOI: 10.1117/1.jmi.5.1.011008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 10/16/2017] [Indexed: 12/31/2022] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.
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Affiliation(s)
- Imon Banerjee
- Stanford University, Department of Radiology, Stanford, California, United States
| | - Sadhika Malladi
- Massachusetts Institute of Technology, Department of Mathematics, Cambridge, Massachusetts, United States
| | - Daniela Lee
- Yale University, Department of Ecology and Evolutionary Biology, New Haven, Connecticut, United States
| | - Adrien Depeursinge
- University of Applied Sciences Western Switzerland (HES-SO), Department Institute of Information Systems, Sierre, Switzerland
| | - Melinda Telli
- Stanford University, Department of Medicine (Oncology), Stanford, California, United States
| | - Jafi Lipson
- Stanford University, Department of Radiology, Stanford, California, United States
| | - Daniel Golden
- Arterys Inc., San Francisco, California, United States
| | - Daniel L Rubin
- Stanford University, Department of Radiology, Stanford, California, United States
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65
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Molecular imaging in drug development: Update and challenges for radiolabeled antibodies and nanotechnology. Methods 2017; 130:23-35. [DOI: 10.1016/j.ymeth.2017.07.018] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Revised: 06/08/2017] [Accepted: 07/18/2017] [Indexed: 01/01/2023] Open
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66
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Renard Y, Hossu G, Chen B, Krebs M, Labrousse M, Perez M. A guide for effective anatomical vascularization studies: useful ex vivo methods for both CT and MRI imaging before dissection. J Anat 2017; 232:15-25. [PMID: 29023687 DOI: 10.1111/joa.12718] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2017] [Indexed: 01/10/2023] Open
Abstract
The objective of this study was to develop a simple and useful injection protocol for imaging cadaveric vascularization and dissection. Mixtures of contrast agent and cast product should provide adequate contrast for two types of ex vivo imaging (MRI and CT) and should harden to allow gross dissection of the injected structures. We tested the most popular contrast agents and cast products, and selected the optimal mixture composition based on their availability and ease of use. All mixtures were first tested in vitro to adjust dilution parameters of each contrast agent and to fine-tune MR imaging acquisition sequences. Mixtures were then injected in 24 pig livers and one human pancreas for MR and computed tomography (CT) imaging before anatomical dissection. Colorized latex, gadobutrol and barite mixture met the above objective. Mixtures composed of copper sulfate (CuSO4 ) gadoxetic acid (for MRI) and iodine (for CT) gave an inhomogeneous signal or extravasation of the contrast agent. Agar did not harden sufficiently for gross dissection but appears useful for CT and magnetic resonance imaging (MRI) studies without dissection. Silicone was very hard to inject but achieved the goals of the study. Resin is particularly difficult to use but could replace latex as an alternative for corrosion instead of dissection. This injection protocol allows CT and MRI images to be obtained of cadaveric vascularization and anatomical casts in the same anatomic specimen. Post-imaging processing software allow easy 3D reconstruction of complex anatomical structures using this technique. Applications are numerous, e.g. surgical training, teaching methods, postmortem anatomic studies, pathologic studies, and forensic diagnoses.
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Affiliation(s)
- Yohann Renard
- Department of Anatomy, Faculty of Medicine and University Hospital, University of Lorraine, Nancy, France.,Department of Anatomy, Faculty of Medicine and University Hospital, University of Reims Champagne-Ardenne, Reims, France.,IADI, INSERM U947, University of Lorraine, Nancy, France
| | - Gabriela Hossu
- IADI, INSERM U947, University of Lorraine, Nancy, France.,INSERM CIT1433, CIC-IT, University Hospital of Nancy, Nancy, France
| | - Bailiang Chen
- IADI, INSERM U947, University of Lorraine, Nancy, France.,INSERM CIT1433, CIC-IT, University Hospital of Nancy, Nancy, France
| | - Marine Krebs
- Department of Anatomy, Faculty of Medicine and University Hospital, University of Lorraine, Nancy, France
| | - Marc Labrousse
- Department of Anatomy, Faculty of Medicine and University Hospital, University of Reims Champagne-Ardenne, Reims, France
| | - Manuela Perez
- Department of Anatomy, Faculty of Medicine and University Hospital, University of Lorraine, Nancy, France.,IADI, INSERM U947, University of Lorraine, Nancy, France
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Schmitz AMT, Veldhuis WB, Menke-Pluijmers MBE, van der Kemp WJM, van der Velden TA, Viergever MA, Mali WPTM, Kock MCJM, Westenend PJ, Klomp DWJ, Gilhuijs KGA. Preoperative indication for systemic therapy extended to patients with early-stage breast cancer using multiparametric 7-tesla breast MRI. PLoS One 2017; 12:e0183855. [PMID: 28949967 PMCID: PMC5614529 DOI: 10.1371/journal.pone.0183855] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 08/11/2017] [Indexed: 11/19/2022] Open
Abstract
Purpose To establish a preoperative decision model for accurate indication of systemic therapy in early-stage breast cancer using multiparametric MRI at 7-tesla field strength. Materials and methods Patients eligible for breast-conserving therapy were consecutively included. Patients underwent conventional diagnostic workup and one preoperative multiparametric 7-tesla breast MRI. The postoperative (gold standard) indication for systemic therapy was established from resected tumor and lymph-node tissue, based on 10-year risk-estimates of breast cancer mortality and relapse using Adjuvant! Online. Preoperative indication was estimated using similar guidelines, but from conventional diagnostic workup. Agreement was established between preoperative and postoperative indication, and MRI-characteristics used to improve agreement. MRI-characteristics included phospomonoester/phosphodiester (PME/PDE) ratio on 31-phosphorus spectroscopy (31P-MRS), apparent diffusion coefficients on diffusion-weighted imaging, and tumor size on dynamic contrast-enhanced (DCE)-MRI. A decision model was built to estimate the postoperative indication from preoperatively available data. Results We included 46 women (age: 43-74yrs) with 48 invasive carcinomas. Postoperatively, 20 patients (43%) had positive, and 26 patients (57%) negative indication for systemic therapy. Using conventional workup, positive preoperative indication agreed excellently with positive postoperative indication (N = 8/8; 100%). Negative preoperative indication was correct in only 26/38 (68%) patients. However, 31P-MRS score (p = 0.030) and tumor size (p = 0.002) were associated with the postoperative indication. The decision model shows that negative indication is correct in 21/22 (96%) patients when exempting tumors larger than 2.0cm on DCE-MRI or with PME>PDE ratios at 31P-MRS. Conclusions Preoperatively, positive indication for systemic therapy is highly accurate. Negative indication is highly accurate (96%) for tumors sized ≤2,0cm on DCE-MRI and with PME≤PDE ratios on 31P-MRS.
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Affiliation(s)
- A. M. T. Schmitz
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
- * E-mail:
| | - W. B. Veldhuis
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - W. J. M. van der Kemp
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - T. A. van der Velden
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - M. A. Viergever
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - W. P. T. M. Mali
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - M. C. J. M. Kock
- Department of Radiology, Albert Schweitzer Hospital, Dordrecht, the Netherlands
| | - P. J. Westenend
- Department of Pathology, Albert Schweitzer Hospital, Dordrecht, the Netherlands
| | - D. W. J. Klomp
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - K. G. A. Gilhuijs
- Department of Radiology / Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
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van der Velden BHM, Elias SG, Bismeijer T, Loo CE, Viergever MA, Wessels LFA, Gilhuijs KGA. Complementary Value of Contralateral Parenchymal Enhancement on DCE-MRI to Prognostic Models and Molecular Assays in High-risk ER +/HER2 - Breast Cancer. Clin Cancer Res 2017; 23:6505-6515. [PMID: 28790119 DOI: 10.1158/1078-0432.ccr-17-0176] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Revised: 04/05/2017] [Accepted: 07/27/2017] [Indexed: 11/16/2022]
Abstract
Purpose: To determine whether markers of healthy breast stroma are able to select a subgroup of patients at low risk of death or metastasis from patients considered at high risk according to routine markers of the tumor.Experimental Design: Patients with ER+/HER2- breast cancer were consecutively included for retrospective analysis. The contralateral parenchyma was segmented automatically on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), where upon the average of the top-10% late enhancement was calculated. This contralateral parenchymal enhancement (CPE) was analyzed with respect to routine prognostic models and molecular assays (Nottingham Prognostic Index, Dutch clinical chemotherapy-selection guidelines, 70-gene signature, and 21-gene recurrence score). CPE was split in tertiles and tested for overall and distant disease-free survival. CPE was adjusted for patient and tumor characteristics, as well as systemic therapy, using inverse probability weighting (IPW). Subanalyses were performed in patients at high risk according to prognostic models and molecular assays.Results: Four-hundred-and-fifteen patients were included, constituting the same group in which the association between CPE and survival was discovered. Median follow-up was 85 months, 34/415(8%) patients succumbed. After IPW-adjustment for patient and tumor characteristics, patients with high CPE had significantly better overall survival than those with low CPE in groups at high risk according to the Nottingham Prognostic Index [HR (95% CI): 0.08 (0.00-0.40), P < 0.001]; Dutch clinical guidelines [HR (95% CI): 0.22 (0.00-0.81), P = 0.021]; and 21-gene recurrence score [HR (95% CI): 0.14 (0.00-0.84), P = 0.030]. One group showed a trend [70-gene signature: HR (95% CI): 0.25 (0.00-1.02), P = 0.054].Conclusions: In patients at high risk based on the tumor, subgroups at relatively low risk were identified using pretreatment enhancement of the stroma on breast DCE-MRI. Clin Cancer Res; 23(21); 6505-15. ©2017 AACR.
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Affiliation(s)
| | - Sjoerd G Elias
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tycho Bismeijer
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Claudette E Loo
- Department of Radiology, the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Max A Viergever
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lodewyk F A Wessels
- Division of Molecular Carcinogenesis, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Kenneth G A Gilhuijs
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands.
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69
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Chen B, Duan J, Chabot-Lecoanet AC, Lu H, Tonnelet R, Morel O, Beaumont M. Ex vivo magnetic resonance angiography to explore placental vascular anatomy. Placenta 2017; 58:40-45. [PMID: 28962694 DOI: 10.1016/j.placenta.2017.08.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Revised: 06/23/2017] [Accepted: 08/01/2017] [Indexed: 11/19/2022]
Abstract
INTRODUCTION A normal placenta development is crucial for a successful pregnancy. In case of major obstetric complications such as intra-uterine growth restriction, the placental vascularization morphological alteration at macroscopic level is less known than that at microscopic scale. Ex vivo MRA has the potential to visualize whole fresh human placental vasculature fast and efficiently but can be hampered by contrast agent extravasation problem. This study aimed to provide an optimized ex vivo MRA protocol to acquire understanding of global human placenta vasculature morphology. METHODS Six fresh normal human placentas were imaged with two contrast agents (i.e. Gd-chelate and pump oil) using different imaging parameters on a 3T clinical MR scanner (GE). The contrast to noise ratio, signal to noise ratio and enhancement efficiency were assessed in order to decide which contrast agent and imaging protocol was better. In the end, morphology indices were measured based on the 3D vasculature models reconstructed from the placentas imaged with the optimized protocol. RESULTS With the same imaging parameters, the CNR and the enhancement efficiency of images enhanced with pump oil were superior to those using Gd-chelate. Enhanced by pump oil, an optimized ex vivo MRA protocol was determined, leading to a clear 3D visualization and reconstruction of human placenta vascularization. DISCUSSION The proposed ex vivo MRA method is easy to manipulate, and can be used to investigate the human placental vasculature morphology. The acquired data are of good quality and can be used for characterization of placenta vascularization morphology.
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Affiliation(s)
- Bailiang Chen
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France; CIC-IT Nancy, Inserm CIC1433, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France
| | - Jie Duan
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France; Regional Maternity of University of Nancy, 10 Rue Heydenreich, 54000, Nancy, France
| | - Anne-Claire Chabot-Lecoanet
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France; Regional Maternity of University of Nancy, 10 Rue Heydenreich, 54000, Nancy, France
| | - Huanrong Lu
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France
| | - Romain Tonnelet
- The Neurointerventional Department, CHRU of Nancy, 54000, Nancy, France
| | - Oliver Morel
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France; Regional Maternity of University of Nancy, 10 Rue Heydenreich, 54000, Nancy, France
| | - Marine Beaumont
- IADI Inserm U947, Lorraine University, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France; CIC-IT Nancy, Inserm CIC1433, 4 Rue Du Morvan, 54500, Vandoeuvre lès Nancy, France.
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70
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Han S, Stoyanova R, Lee H, Carlin SD, Koutcher JA, Cho H, Ackerstaff E. Automation of pattern recognition analysis of dynamic contrast-enhanced MRI data to characterize intratumoral vascular heterogeneity. Magn Reson Med 2017; 79:1736-1744. [PMID: 28727185 DOI: 10.1002/mrm.26822] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 05/14/2017] [Accepted: 06/12/2017] [Indexed: 12/20/2022]
Abstract
PURPOSE To automate dynamic contrast-enhanced MRI (DCE-MRI) data analysis by unsupervised pattern recognition (PR) to enable spatial mapping of intratumoral vascular heterogeneity. METHODS Three steps were automated. First, the arrival time of the contrast agent at the tumor was determined, including a calculation of the precontrast signal. Second, four criteria-based algorithms for the slice-specific selection of number of patterns (NP) were validated using 109 tumor slices from subcutaneous flank tumors of five different tumor models. The criteria were: half area under the curve, standard deviation thresholding, percent signal enhancement, and signal-to-noise ratio (SNR). The performance of these criteria was assessed by comparing the calculated NP with the visually determined NP. Third, spatial assignment of single patterns and/or pattern mixtures was obtained by way of constrained nonnegative matrix factorization. RESULTS The determination of the contrast agent arrival time at the tumor slice was successfully automated. For the determination of NP, the SNR-based approach outperformed other selection criteria by agreeing >97% with visual assessment. The spatial localization of single patterns and pattern mixtures, the latter inferring tumor vascular heterogeneity at subpixel spatial resolution, was established successfully by automated assignment from DCE-MRI signal-versus-time curves. CONCLUSION The PR-based DCE-MRI analysis was successfully automated to spatially map intratumoral vascular heterogeneity. Magn Reson Med 79:1736-1744, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- SoHyun Han
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea.,Currently at: Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, South Korea
| | - Radka Stoyanova
- Department of Radiation Oncology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Hansol Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sean D Carlin
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Currently at: Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jason A Koutcher
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Sloan Kettering Institute Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Weill Cornell Medical College, Cornell University, New York, New York, USA
| | - HyungJoon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Ellen Ackerstaff
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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Wu J, Cui Y, Sun X, Cao G, Li B, Ikeda DM, Kurian AW, Li R. Unsupervised Clustering of Quantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular Pathways. Clin Cancer Res 2017; 23:3334-3342. [PMID: 28073839 PMCID: PMC5496801 DOI: 10.1158/1078-0432.ccr-16-2415] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 12/29/2016] [Accepted: 01/03/2017] [Indexed: 01/28/2023]
Abstract
Purpose: To identify novel breast cancer subtypes by extracting quantitative imaging phenotypes of the tumor and surrounding parenchyma and to elucidate the underlying biologic underpinnings and evaluate the prognostic capacity for predicting recurrence-free survival (RFS).Experimental Design: We retrospectively analyzed dynamic contrast-enhanced MRI data of patients from a single-center discovery cohort (n = 60) and an independent multicenter validation cohort (n = 96). Quantitative image features were extracted to characterize tumor morphology, intratumor heterogeneity of contrast agent wash-in/wash-out patterns, and tumor-surrounding parenchyma enhancement. On the basis of these image features, we used unsupervised consensus clustering to identify robust imaging subtypes and evaluated their clinical and biologic relevance. We built a gene expression-based classifier of imaging subtypes and tested their prognostic significance in five additional cohorts with publically available gene expression data but without imaging data (n = 1,160).Results: Three distinct imaging subtypes, that is, homogeneous intratumoral enhancing, minimal parenchymal enhancing, and prominent parenchymal enhancing, were identified and validated. In the discovery cohort, imaging subtypes stratified patients with significantly different 5-year RFS rates of 79.6%, 65.2%, 52.5% (log-rank P = 0.025) and remained as an independent predictor after adjusting for clinicopathologic factors (HR, 2.79; P = 0.016). The prognostic value of imaging subtypes was further validated in five independent gene expression cohorts, with average 5-year RFS rates of 88.1%, 74.0%, 59.5% (log-rank P from <0.0001 to 0.008). Each imaging subtype was associated with specific dysregulated molecular pathways that can be therapeutically targeted.Conclusions: Imaging subtypes provide complimentary value to established histopathologic or molecular subtypes and may help stratify patients with breast cancer. Clin Cancer Res; 23(13); 3334-42. ©2017 AACR.
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Affiliation(s)
- Jia Wu
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
| | - Yi Cui
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
- Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Proton Beam Therapy Center, Sapporo, Hokkaido, Japan
| | - Xiaoli Sun
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
- Radiotherapy Department, the First Affiliated Hospital of Zhejiang University, Hangzhou, Zhejiang, China
| | - Guohong Cao
- Department of Radiology, International Hospital of Zhejiang University, Hangzhou, Zhejiang, China
| | - Bailiang Li
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California
| | - Debra M Ikeda
- Department of Radiology, Stanford University School of Medicine, Advanced Medicine Center, Stanford, California
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California
| | - Allison W Kurian
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California
- Department of Medicine, Stanford University School of Medicine, Stanford, California
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California
| | - Ruijiang Li
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California
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72
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Wu S, Zuley ML, Berg WA, Kurland BF, Jankowitz RC, Sumkin JH, Gur D. DCE-MRI Background Parenchymal Enhancement Quantified from an Early versus Delayed Post-contrast Sequence: Association with Breast Cancer Presence. Sci Rep 2017; 7:2115. [PMID: 28522877 PMCID: PMC5437095 DOI: 10.1038/s41598-017-02341-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 04/10/2017] [Indexed: 12/23/2022] Open
Abstract
We investigated automated quantitative measures of background parenchymal enhancement (BPE) derived from an early versus delayed post-contrast sequence in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for association with breast cancer presence in a case-control study. DCE-MRIs were retrospectively analyzed for 51 cancer cases and 51 controls with biopsy-proven benign lesions, matched by age and year-of-MRI. BPE was quantified using fully-automated validated computer algorithms, separately from three sequential DCE-MRI post-contrast-subtracted sequences (SUB1, SUB2, and SUB3). The association of BPE computed from the three SUBs and other known factors with breast cancer were assessed in terms of odds ratio (OR) and area under the receiver operating characteristic curve (AUC). The OR of breast cancer for the percentage BPE measure (BPE%) quantified from SUB1 was 3.5 (95% Confidence Interval: 1.3, 9.8; p = 0.015) for 20% increments. Slightly lower and statistically significant ORs were also obtained for BPE quantified from SUB2 and SUB3. There was no significant difference (p > 0.2) in AUC for BPE quantified from the three post-contrast sequences and their combination. Our study showed that quantitative measures of BPE are associated with breast cancer presence and the association was similar across three breast DCE-MRI post-contrast sequences.
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Affiliation(s)
- Shandong Wu
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.
| | - Margarita L Zuley
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
| | - Wendie A Berg
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
| | - Brenda F Kurland
- University of Pittsburgh Cancer Institute, Department of Biostatistics, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Rachel C Jankowitz
- Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA.,Department of Medicine, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Jules H Sumkin
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
| | - David Gur
- Departments of Radiology, Biomedical Informatics, and Bioengineering, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
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73
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Kumar KA, Peck KK, Karimi S, Lis E, Holodny AI, Bilsky MH, Yamada Y. A Pilot Study Evaluating the Use of Dynamic Contrast-Enhanced Perfusion MRI to Predict Local Recurrence After Radiosurgery on Spinal Metastases. Technol Cancer Res Treat 2017; 16:857-865. [PMID: 28449626 PMCID: PMC5762041 DOI: 10.1177/1533034617705715] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Purpose: Dynamic contrast-enhanced magnetic resonance imaging offers noninvasive characterization of the vascular microenvironment and hemodynamics. Stereotactic radiosurgery, or stereotactic body radiation therapy, engages a vascular component of the tumor response which may be detectable using dynamic contrast-enhanced magnetic resonance imaging. The purpose of this study is to examine whether dynamic contrast-enhanced magnetic resonance imaging can be used to predict local tumor recurrence in patients with spinal bone metastases who undergo high-dose radiotherapy with stereotactic radiosurgery. Materials and Methods: We conducted a study of 30 patients with spinal metastases who underwent dynamic contrast-enhanced magnetic resonance imaging before and after radiotherapy. Twenty patients received single-fraction stereotactic radiosurgery (24 Gy), while 10 received hypofractionated stereotactic radiosurgery (3-5 fractions, 27-30 Gy total). Kaplan-Meier analysis was used to estimate the actuarial local recurrence rates. Two perfusion parameters (Ktrans: permeability and Vp: plasma volume) were measured for each metastasis. Percentage change in parameter values from pre- to posttreatment was calculated and compared. Results: At 20-month median follow-up, 5 of the 30 patients had pathological evidence of local recurrence. One- and 3-year actuarial local recurrence rates were 24% and 44% for the hypofractionated stereotactic radiosurgery cohort versus 5% and 16% for the single-fraction stereotactic radiosurgery cohort (P = .20). The average change in Vp and Ktrans for patients without local recurrence versus those with local recurrence was −76% and −66% versus +28% and −14% (P < .01 for both). With a cutoff point of −20%, Vp had a sensitivity, specificity, positive predictive value, and negative predictive value of 100%, 98%, 91%, and 100%, respectively, for the detection of local recurrence following high-dose radiotherapy. Using this definition, dynamic contrast-enhanced magnetic resonance imaging identified local recurrence up to 18 months (mean [standard deviation], 6.6 [6.8] months) earlier than standard magnetic resonance imaging. Conclusions: We demonstrated that changes in perfusion parameters, particularly Vp, after high-dose radiotherapy to spinal bone metastases were predictive of local tumor recurrence. These changes predicted local recurrence on average >6 months earlier than standard imaging did.
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Affiliation(s)
- Kiran A Kumar
- Department of Radiation Oncology, Stanford University, Stanford, CA, USA
| | - Kyung K Peck
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sasan Karimi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Eric Lis
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mark H Bilsky
- Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yoshiya Yamada
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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74
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Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:7064120. [PMID: 29097933 PMCID: PMC5612612 DOI: 10.1155/2017/7064120] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/23/2017] [Indexed: 01/12/2023]
Abstract
Gliomas possess complex and heterogeneous vasculatures with abnormal hemodynamics. Despite considerable advances in diagnostic and therapeutic techniques for improving tumor management and patient care in recent years, the prognosis of malignant gliomas remains dismal. Perfusion-weighted magnetic resonance imaging techniques that could noninvasively provide superior information on vascular functionality have attracted much attention for evaluating brain tumors. However, nonconsensus imaging protocols and postprocessing analysis among different institutions impede their integration into standard-of-care imaging in clinic. And there have been very few studies providing a comprehensive evidence-based and systematic summary. This review first outlines the status of glioma theranostics and tumor-associated vascular pathology and then presents an overview of the principles of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), with emphasis on their recent clinical applications in gliomas including tumor grading, identification of molecular characteristics, differentiation of glioma from other brain tumors, treatment response assessment, and predicting prognosis. Current challenges and future perspectives are also highlighted.
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75
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Fan M, Li H, Wang S, Zheng B, Zhang J, Li L. Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer. PLoS One 2017; 12:e0171683. [PMID: 28166261 PMCID: PMC5293281 DOI: 10.1371/journal.pone.0171683] [Citation(s) in RCA: 100] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2016] [Accepted: 01/24/2017] [Indexed: 12/15/2022] Open
Abstract
The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case. In total, 90 features were obtained, including 88 imaging features related to morphology and texture as well as dynamic features from tumor and background parenchymal enhancement (BPE) and 2 clinical information-based parameters, namely, age and menopausal status. An evolutionary algorithm was used to select an optimal subset of features for classification. Using these features, we trained a multi-class logistic regression classifier that calculated the area under the receiver operating characteristic curve (AUC). The results of a prediction model using 24 selected features showed high overall classification performance, with an AUC value of 0.869. The predictive model discriminated among the luminal A, luminal B, HER2 and basal-like subtypes, with AUC values of 0.867, 0.786, 0.888 and 0.923, respectively. An additional independent dataset with 36 patients was utilized to validate the results. A similar classification analysis of the validation dataset showed an AUC of 0.872 using 15 image features, 10 of which were identical to those from the first cohort. We identified clinical information and 3D imaging features from DCE-MRI as candidate biomarkers for discriminating among four molecular subtypes of breast cancer.
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Affiliation(s)
- Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Hui Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Shijian Wang
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
| | - Bin Zheng
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Juan Zhang
- Zhejiang Cancer Hospital, Zhejiang Hangzhou, China
- * E-mail: (JZ); (LL)
| | - Lihua Li
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China
- * E-mail: (JZ); (LL)
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76
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Longo DL, Stefania R, Callari C, De Rose F, Rolle R, Conti L, Consolino L, Arena F, Aime S. Water Soluble Melanin Derivatives for Dynamic Contrast Enhanced Photoacoustic Imaging of Tumor Vasculature and Response to Antiangiogenic Therapy. Adv Healthc Mater 2017; 6. [PMID: 27782375 DOI: 10.1002/adhm.201600550] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 08/22/2016] [Indexed: 12/17/2022]
Abstract
A dynamic contrast enhanced (DCE) approach for tumor photoacoustic (PA) imaging is described. Novel water soluble melanin-based derivatives are synthesized that exhibit good PA properties, stability, safety and accumulation in tumor bearing mice. This melanin derivative is capable to characterize tumor vasculature and to monitor vessel permeability changes upon antiangiogenic treatment. DCE-PA imaging can assess functional response to cancer treatments.
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Affiliation(s)
- Dario L. Longo
- Institute of Biostructure and Bioimaging (CNR) c/o Molecular Biotechnology Center; Via Nizza 52 10126 Torino Italy
| | - Rachele Stefania
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Chiara Callari
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Francesco De Rose
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Riccardo Rolle
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Laura Conti
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Lorena Consolino
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Francesca Arena
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
| | - Silvio Aime
- Department of Molecular Biotechnology and Health Sciences; University of Torino; Via Nizza 52 10126 Torino Italy
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77
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Comparison between perfusion computed tomography and dynamic contrast-enhanced magnetic resonance imaging in assessing glioblastoma microvasculature. Eur J Radiol 2016; 87:120-124. [PMID: 28034567 DOI: 10.1016/j.ejrad.2016.12.016] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Revised: 12/15/2016] [Accepted: 12/17/2016] [Indexed: 12/15/2022]
Abstract
PURPOSE Perfusion computed tomography (PCT) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide independent measurements of biomarkers related to tumor perfusion. The aim of this study was to compare the two techniques in assessing glioblastoma microvasculature. MATERIALS AND METHODS Twenty-five patients diagnosed with glioblastoma (14 males and 11 females; 51±11years old, ranging from 33 to 70 years) were includede in this prospective study. All patients underwent both PCT and DCE-MRI. Imaging was performed on a 256-slice CT scanner and a 3-T MRI system. PCT yielded permeability surface-area product (PS) using deconvolution physiological models; meanwhile, DCE-MRI determined volume transfer constant (Ktrans) using the Tofts-Kermode compartment model. All cases were submitted to surgical intervention, and CD105-microvascular density (CD105-MVD) was measured in each glioblastoma specimen. Then, Spearman's correlation coefficients and Bland-Altman plots were obtained for PS, Ktrans and CD105-MVD. P<0.05 was considered statistically significant. RESULTS Tumor PS and Ktrans values were correlated with CD105-MVD (r=0.644, P<0.001; r=0.683, P<0.001). In addition, PS was correlated with Ktrans in glioblastoma (r=0.931, P<0.001). Finally, Bland-Altman plots showed no significant differences between PS and Ktrans (P=0.063). CONCLUSION PCT and DCE-MRI measurements of glioblastoma perfusion biomarkers have similar results, suggesting that both techniques may have comparable utility. Therefore, PCT may serve as an alternative modality to DCE-MRI for the in vivo evaluation of glioblastoma microvasculature.
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78
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Kim WH, Li M, Han W, Ryu HS, Moon WK. The Spatial Relationship of Malignant and Benign Breast Lesions with Respect to the Fat-Gland Interface on Magnetic Resonance Imaging. Sci Rep 2016; 6:39085. [PMID: 27966625 PMCID: PMC5155434 DOI: 10.1038/srep39085] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Accepted: 11/17/2016] [Indexed: 11/20/2022] Open
Abstract
The fat-gland interface in the breast is noteworthy in that major vessels and lymphatic channels supplying the breast are located there; however, the relationship between breast lesion formation and the fat-gland interface is poorly understood. Here we evaluate the location of malignant and benign breast lesions with respect to the fat-gland interface in 881 women 50 years of age and younger, utilizing MR imaging. We find that most breast lesions are located in or near the interface in qualitative (89.7%) and quantitative (90.0%, 1 cm within the interface) analyses. This propensity for the fat-gland interface is not accounted for by breast anatomy, whereby 12.3% and 55.7% of breast volume is within 2 mm and 1 cm of the interface, respectively. Malignant lesions were located in or near the interface in significantly higher proportions than benign lesions in qualitative (94.3% vs. 67.3%, P < 0.001) and quantitative (49.7% vs. 34.5%, P < 0.001, 2 mm within the interface) analyses. This phenomenon may reflect a biological importance of the fat-gland interface in breast cancer development and progression.
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Affiliation(s)
- Won Hwa Kim
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Kyungpook National University Medical Center, Daegu, Korea
| | - MuLan Li
- International Radiology Imaging System, ShenZhen Mindray Bio-Medical Electronics Co., LTD., Shenzhen 518057, China
| | - Wonshik Han
- Department of Surgery, Seoul National University College of Medicine, Seoul, Korea
| | - Han Suk Ryu
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
| | - Woo Kyung Moon
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Korea
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79
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Wang C, Subashi E, Yin FF, Chang Z. Dynamic fractal signature dissimilarity analysis for therapeutic response assessment using dynamic contrast-enhanced MRI. Med Phys 2016; 43:1335-47. [PMID: 26936718 DOI: 10.1118/1.4941739] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
PURPOSE To develop a dynamic fractal signature dissimilarity (FSD) method as a novel image texture analysis technique for the quantification of tumor heterogeneity information for better therapeutic response assessment with dynamic contrast-enhanced (DCE)-MRI. METHODS A small animal antiangiogenesis drug treatment experiment was used to demonstrate the proposed method. Sixteen LS-174T implanted mice were randomly assigned into treatment and control groups (n = 8/group). All mice received bevacizumab (treatment) or saline (control) three times in two weeks, and one pretreatment and two post-treatment DCE-MRI scans were performed. In the proposed dynamic FSD method, a dynamic FSD curve was generated to characterize the heterogeneity evolution during the contrast agent uptake, and the area under FSD curve (AUCFSD) and the maximum enhancement (MEFSD) were selected as representative parameters. As for comparison, the pharmacokinetic parameter K(trans) map and area under MR intensity enhancement curve AUCMR map were calculated. Besides the tumor's mean value and coefficient of variation, the kurtosis, skewness, and classic Rényi dimensions d1 and d2 of K(trans) and AUCMR maps were evaluated for heterogeneity assessment for comparison. For post-treatment scans, the Mann-Whitney U-test was used to assess the differences of the investigated parameters between treatment/control groups. The support vector machine (SVM) was applied to classify treatment/control groups using the investigated parameters at each post-treatment scan day. RESULTS The tumor mean K(trans) and its heterogeneity measurements d1 and d2 values showed significant differences between treatment/control groups in the second post-treatment scan. In contrast, the relative values (in reference to the pretreatment value) of AUCFSD and MEFSD in both post-treatment scans showed significant differences between treatment/control groups. When using AUCFSD and MEFSD as SVM input for treatment/control classification, the achieved accuracies were 93.8% and 93.8% at first and second post-treatment scan days, respectively. In comparison, the classification accuracies using d1 and d2 of K(trans) map were 87.5% and 100% at first and second post-treatment scan days, respectively. CONCLUSIONS As quantitative metrics of tumor contrast agent uptake heterogeneity, the selected parameters from the dynamic FSD method accurately captured the therapeutic response in the experiment. The potential application of the proposed method is promising, and its addition to the existing DCE-MRI techniques could improve DCE-MRI performance in early assessment of treatment response.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710
| | - Ergys Subashi
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710
| | - Fang-Fang Yin
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710
| | - Zheng Chang
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710
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80
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Ting-Fang Shih T. Angiogenesis in hematological malignancy – Evaluated by dynamic contrast-enhanced MRI. JOURNAL OF CANCER RESEARCH AND PRACTICE 2016. [DOI: 10.1016/j.jcrpr.2016.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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81
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Teruel JR, Goa PE, Sjøbakk TE, Østlie A, Fjøsne HE, Bathen TF. A Simplified Approach to Measure the Effect of the Microvasculature in Diffusion-weighted MR Imaging Applied to Breast Tumors: Preliminary Results. Radiology 2016; 281:373-381. [DOI: 10.1148/radiol.2016151630] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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82
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Wang CJ, Huang CC, Yip HK, Yang YJ. Dosage effects of extracorporeal shockwave therapy in early hip necrosis. Int J Surg 2016; 35:179-186. [DOI: 10.1016/j.ijsu.2016.09.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 08/11/2016] [Accepted: 09/11/2016] [Indexed: 11/26/2022]
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83
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Wang C, Horton JK, Yin FF, Chang Z. Assessment of Treatment Response With Diffusion-Weighted MRI and Dynamic Contrast-Enhanced MRI in Patients With Early-Stage Breast Cancer Treated With Single-Dose Preoperative Radiotherapy: Initial Results. Technol Cancer Res Treat 2016; 15:651-60. [PMID: 26134438 PMCID: PMC4914478 DOI: 10.1177/1533034615593191] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Accepted: 05/28/2015] [Indexed: 11/16/2022] Open
Abstract
Single-dose preoperative stereotactic body radiotherapy is a novel radiotherapy technique for the early-stage breast cancer, and the treatment response pattern of this technique needs to be investigated on a quantitative basis. In this work, dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging were used to study the treatment response pattern in a unique cohort of patients with early-stage breast cancer treated with preoperative radiation. Fifteen female qualified patients received single-dose preoperative radiotherapy with 1 of the 3 prescription doses: 15 Gy, 18 Gy, and 21 Gy. Magnetic resonance imaging scans including both diffusion-weighted magnetic resonance imaging and dynamic contrast-enhanced magnetic resonance imaging were acquired before radiotherapy for planning and after radiotherapy but before surgical resection. In diffusion-weighted magnetic resonance imaging, the regional averaged apparent diffusion coefficient was calculated. In dynamic contrast-enhanced magnetic resonance imaging, quantitative parameters K (trans) and v e were evaluated using the standard Tofts model based on the average contrast agent concentration within the region of interest, and the semiquantitative initial area under the concentration curve (iAUC6min) was also recorded. These parameters' relative changes after radiotherapy were calculated for gross tumor volume, clinical target volume, and planning target volume. The initial results showed that after radiotherapy, initial area under the concentration curve significantly increased in planning target volume (P < .006) and clinical target volume (P < .006), and v e significantly increased in planning target volume (P < .05) and clinical target volume (P < .05). Statistical studies suggested that linear correlations between treatment dose and the observed parameter changes exist in most examined tests, and among these tests, the change in gross tumor volume regional averaged apparent diffusion coefficient (P < .012) and between treatment dose and planning target volume K (trans) (P < .029) were found to be statistically significant. Although it is still preliminary, this pilot study may be useful to provide insights for future works.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Janet K Horton
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Fang-Fang Yin
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Zheng Chang
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
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84
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Ream JM, Doshi AM, Dunst D, Parikh N, Kong MX, Babb JS, Taneja SS, Rosenkrantz AB. Dynamic contrast-enhanced MRI of the prostate: An intraindividual assessment of the effect of temporal resolution on qualitative detection and quantitative analysis of histopathologically proven prostate cancer. J Magn Reson Imaging 2016; 45:1464-1475. [PMID: 27649481 DOI: 10.1002/jmri.25451] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 08/17/2016] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To assess the effects of temporal resolution (RT ) in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on qualitative tumor detection and quantitative pharmacokinetic parameters in prostate cancer. MATERIALS AND METHODS This retrospective Institutional Review Board (IRB)-approved study included 58 men (64 ± 7 years). They underwent 3T prostate MRI showing dominant peripheral zone (PZ) tumors (24 with Gleason ≥ 4 + 3), prior to prostatectomy. Continuously acquired DCE utilizing GRASP (Golden-angle RAdial Sparse Parallel) was retrospectively reconstructed at RT of 1.4 sec, 3.7 sec, 6.0 sec, 9.7 sec, and 14.9 sec. A reader placed volumes-of-interest on dominant tumors and benign PZ, generating quantitative pharmacokinetic parameters (ktrans , ve ) at each RT . Two blinded readers assessed each RT for lesion presence, location, conspicuity, and reader confidence on a 5-point scale. Data were assessed by mixed-model analysis of variance (ANOVA), generalized estimating equation (GEE), and receiver operating characteristic (ROC) analysis. RESULTS RT did not affect sensitivity (R1all : 69.0%-72.4%, all Padj = 1.000; R1GS≥4 + 3 : 83.3-91.7%, all Padj = 1.000; R2all : 60.3-69.0%, all Padj = 1.000; R2GS≥4 + 3 : 58.3%-79.2%, all Padj = 1.000). R1 reported greater conspicuity of GS ≥ 4 + 3 tumors at RT of 1.4 sec vs. 14.9 sec (4.29 ± 1.23 vs. 3.46 ± 1.44; Padj = 0.029). No other tumor conspicuity pairwise comparison reached significance (R1all : 2.98-3.43, all Padj ≥ 0.205; R2all : 2.57-3.19, all Padj ≥ 0.059; R1GS≥4 + 3 : 3.46-4.29, all other Padj ≥ 0.156; R2GS≥4 + 3 : 2.92-3.71, all Padj ≥ 0.439). There was no effect of RT on reader confidence (R1all : 3.17-3.34, all Padj = 1.000; R2all : 2.83-3.19, all Padj ≥ 0.801; R1GS≥4 + 3 : 3.79-4.21, all Padj = 1.000; R2GS≥4 + 3 : 3.13-3.79, all Padj = 1.000). ktrans and ve of tumor and benign tissue did not differ across RT (all adjusted P values [Padj ] = 1.000). RT did not significantly affect area under the curve (AUC) of Ktrans or ve for differentiating tumor from benign (all Padj = 1.000). CONCLUSION Current PI-RADS recommendations for RT of 10 seconds may be sufficient, with further reduction to the stated PI-RADS preference of RT ≤ 7 seconds offering no benefit in tumor detection or quantitative analysis. LEVEL OF EVIDENCE 3 J. MAGN. RESON. IMAGING 2017;45:1464-1475.
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Affiliation(s)
- Justin M Ream
- Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Ankur M Doshi
- Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Diane Dunst
- Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Nainesh Parikh
- Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Max X Kong
- Department of Pathology, NYU Langone Medical Center, New York, New York, USA
| | - James S Babb
- Department of Radiology, NYU Langone Medical Center, New York, New York, USA
| | - Samir S Taneja
- Department of Urology, NYU Langone Medical Center, New York, New York, USA
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85
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MRI-CEST assessment of tumour perfusion using X-ray iodinated agents: comparison with a conventional Gd-based agent. Eur Radiol 2016; 27:2170-2179. [DOI: 10.1007/s00330-016-4552-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 07/08/2016] [Accepted: 08/09/2016] [Indexed: 12/28/2022]
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86
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Wu S, Berg WA, Zuley ML, Kurland BF, Jankowitz RC, Nishikawa R, Gur D, Sumkin JH. Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer. Breast Cancer Res 2016; 18:76. [PMID: 27449059 PMCID: PMC4957890 DOI: 10.1186/s13058-016-0734-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 05/04/2016] [Indexed: 12/22/2022] Open
Abstract
Background We investigated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) contrast enhancement kinetic variables quantified from normal breast parenchyma for association with presence of breast cancer, in a case-control study. Methods Under a Health Insurance Portability and Accountability Act compliant and Institutional Review Board-approved protocol, DCE-MRI scans of the contralateral breasts of 51 patients with cancer and 51 controls (matched by age and year of MRI) with biopsy-proven benign lesions were retrospectively analyzed. Applying fully automated computer algorithms on pre-contrast and multiple post-contrast MR sequences, two contrast enhancement kinetic variables, wash-in slope and signal enhancement ratio, were quantified from normal parenchyma of the contralateral breasts of both patients with cancer and controls. Conditional logistic regression was employed to assess association between these two measures and presence of breast cancer, with adjustment for other imaging factors including mammographic breast density and MRI background parenchymal enhancement (BPE). The area under the receiver operating characteristic curve (AUC) was used to assess the ability of the kinetic measures to distinguish patients with cancer from controls. Results When both kinetic measures were included in conditional logistic regression analysis, the odds ratio for breast cancer was 1.7 (95 % CI 1.1, 2.8; p = 0.017) for wash-in slope variance and 3.5 (95 % CI 1.2, 9.9; p = 0.019) for signal enhancement ratio volume, respectively. These odds ratios were similar on respective univariate analysis, and remained significant after adjustment for menopausal status, family history, and mammographic density. While percent BPE was associated with an odds ratio of 3.1 (95 % CI 1.2, 7.9; p = 0.018), in multivariable analysis of the three measures, percent BPE was non-significant (p = 0.897) and the two kinetics measures remained significant. For the differentiation of patients with cancer and controls, the unadjusted AUC was 0.71 using a combination of the two measures, which significantly (p = 0.005) outperformed either measure alone (AUC = 0.65 for wash-in slope variance and 0.63 for signal enhancement ratio volume). Conclusions Kinetic measures of wash-in slope and signal enhancement ratio quantified from normal parenchyma in DCE-MRI are jointly associated with presence of breast cancer, even after adjustment for mammographic density and BPE.
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Affiliation(s)
- Shandong Wu
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA. .,, 3362 Fifth Avenue, Pittsburgh, PA, 15213, USA.
| | - Wendie A Berg
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
| | - Margarita L Zuley
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
| | - Brenda F Kurland
- University of Pittsburgh Cancer Institute, Department of Biostatistics, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Rachel C Jankowitz
- Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA.,Department of Medicine, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Robert Nishikawa
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - David Gur
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA
| | - Jules H Sumkin
- Department of Radiology, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA, 15260, USA.,Magee-Womens Hospital of University of Pittsburgh Medical Center, 300 Halket St, Pittsburgh, PA, 15213, USA
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87
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Chen BB, Lu YS, Lin CH, Chen WW, Wu PF, Hsu CY, Yu CW, Wei SY, Cheng AL, Shih TTF. A pilot study to determine the timing and effect of bevacizumab on vascular normalization of metastatic brain tumors in breast cancer. BMC Cancer 2016; 16:466. [PMID: 27412562 PMCID: PMC4944505 DOI: 10.1186/s12885-016-2494-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 06/28/2016] [Indexed: 12/19/2022] Open
Abstract
Background To determine the appropriate time of concomitant chemotherapy administration after antiangiogenic treatment, we investigated the timing and effect of bevacizumab administration on vascular normalization of metastatic brain tumors in breast cancer patients. Methods Eight patients who participated in a phase II trial for breast cancer-induced refractory brain metastases were enrolled and subjected to 4 dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations that evaluated Peak, Slope, iAUC60, and Ktrans before and after treatment. The treatment comprised bevacizumab on Day 1, etoposide on Days 2–4, and cisplatin on Day 2 in a 21-day cycle for a maximum of 6 cycles. DCE-MRI was performed before treatment and at 1 h, 24 h, and 21 days after bevacizumab administration. Results Values of the 4 DCE-MRI parameters reduced after bevacizumab administration. Compared with baseline values, the mean reductions at 1 and 24 h were −12.8 and −24.7 % for Peak, −46.6 and −65.8 % for Slope, −27.9 and −55.5 % for iAUC60, and −46.6 and −63.9 % for Ktrans, respectively (all P < .05). The differences in the 1 and 24 h mean reductions were significant (all P < .05) for all the parameters. The generalized estimating equation linear regression analyses of the 4 DCE-MRI parameters revealed that vascular normalization peaked 24 h after bevacizumab administration. Conclusion Bevacizumab induced vascular normalization of brain metastases in humans at 1 and 24 h after administration, and the effect was significantly higher at 24 h than at 1 h. Trial registration ClinicalTrials.gov, identifier NCT01281696, registered prospectively on December 24, 2010
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Affiliation(s)
- Bang-Bin Chen
- Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Yen-Shen Lu
- Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Ching-Hung Lin
- Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Wei-Wu Chen
- Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Pei-Fang Wu
- Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Chao-Yu Hsu
- Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan.,Department of Radiology, Taipei Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan
| | - Chih-Wei Yu
- Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Shwu-Yuan Wei
- Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Ann-Lii Cheng
- Department of Oncology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan
| | - Tiffany Ting-Fang Shih
- Department of Medical Imaging and Radiology, National Taiwan University College of Medicine and Hospital, Taipei City, Taiwan. .,Department of Medical Imaging, Taipei City Hospital, Taipei City, Taiwan.
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88
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Wang C, Subashi E, Liang X, Yin FF, Chang Z. Evaluation of the effect of transcytolemmal water exchange analysis for therapeutic response assessment using DCE-MRI: a comparison study. Phys Med Biol 2016; 61:4763-80. [PMID: 27272391 DOI: 10.1088/0031-9155/61/13/4763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
This study compares the shutter-speed (SS) and the Tofts models as used in assessing therapeutic response in a longitudinal DCE-MRI experiment. Sixteen nu/nu mice with implanted colorectal adenocarcinoma cell line (LS-174T) were randomly assigned into treatment/control groups (n = 8/group) and received bevacizumab/saline twice weekly (Day1/Day4/Day8). All mice were scanned at one pre- (Day0) and two post-treatment (Day2/Day9) time points using a high spatiotemporal resolution DCE-MRI pulse sequence. The CA extravasation rate constant [Formula: see text] from the Tofts/SS model and the mean intracellular water residence time [Formula: see text] from the SS model were analyzed. A biological subvolume (BV) within the tumor was identified based on the [Formula: see text] intensity distribution, and the SS model parameters within the BV ([Formula: see text] and [Formula: see text]) were analyzed. It is found that [Formula: see text] and [Formula: see text] have a similar spatial distribution in the tumor volume. The Bayesian information criterion results show that the SS model was a better fit for all scans. At Day9, the treatment group had significantly higher tumor mean [Formula: see text] (p = 0.021), [Formula: see text] (p = 0.021) and [Formula: see text] (p = 0.045). When BV from transcytolemmal water exchange analysis was adopted, the treatment group had higher mean [Formula: see text] at both Day2 (p = 0.038) and Day9 (p = 0.007). Additionally, at Day9, the treatment group had higher mean [Formula: see text] (p = 0.045) and higher [Formula: see text] spatial heterogeneity indices (Rényi dimensions) d 1 (p = 0.010) and d 2 (p = 0.021). When mean [Formula: see text] and its coefficient of variation (CV) were used to separate treatment/control group samples using supporting vector machine, the accuracy of treatment/control classification was 68.8% at Day2 and 87.5% at Day9; in contrast, the Day2/Day9 accuracy were 62.5%/87.5% using tumor mean [Formula: see text] and its CV and were 50.0%/87.5% using tumor mean [Formula: see text] and its CV, respectively. These results suggest that the SS model parameters outperformed the Tofts model parameters in terms of capturing bevacizumab therapeutic effect in this longitudinal experiment.
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Affiliation(s)
- Chunhao Wang
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC 27710, USA
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89
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Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study. Technol Cancer Res Treat 2016; 16:446-460. [PMID: 27215931 DOI: 10.1177/1533034616649294] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. METHODS Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant Ktrans in the extended Tofts model and blood flow FB and blood volume VB from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. RESULTS The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. CONCLUSION With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.
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90
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Aryal MP, Chenevert TL, Cao Y. Impact of uncertainty in longitudinal T1 measurements on quantification of dynamic contrast-enhanced MRI. NMR IN BIOMEDICINE 2016; 29:411-419. [PMID: 27358934 PMCID: PMC4929815 DOI: 10.1002/nbm.3482] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
The objective of this study was to assess the uncertainty in T1 measurement, by estimating the repeatability coefficient (RC) from two repeated scans, in normal appearing brain tissues employing two different T1 mapping methods. All brain MRI scans were performed on a 3 T MR scanner in 10 patients who had low grade/benign tumors and partial brain radiation therapy (RT) without chemotherapy, at pre-RT, 3 weeks into RT, end RT (6 weeks) and 11, 33, and 85 weeks after RT. T1-weighted images were acquired using (1) a spoiled gradient echo sequence with two flip angles (2FA: 5° and 15°) and (2) a progressive saturation recovery sequence (pSR) with five different TR values (100-2000 ms). Manually drawn volumes of interest (VOIs) included left and right normal putamen and thalamus in gray matter, and frontal and parietal white matter, which were distant from tumors and received a total of accumulated radiation doses less than 5 Gy at 3 weeks. No significant changes or even trends in mean T1 from pre-RT to 3 weeks into RT in these VOIs (p ≥ 0.11, Wilcoxon sign test) allowed us to calculate the repeatability statistics of between-subject means of squares, within-subject means of squares, F-score, and RC. The 2FA method produced RCs in the range of (9.7-11.7)% in gray matter and (12.2-14.5)% in white matter; while the pSR method led to RCs ranging from 10.9 to 17.9% in gray matter and 7.5 to 10.3% in white matter. The overall mean (±SD) RCs produced by the two methods, 12.0 (±1.6)% for 2FA and 12.0 (±3.8)% for pSR, were not significantly different (p = 0.97). A similar repeatability in T1 measurement produced by the time efficient 2FA method compared with the time consuming pSR method demonstrates that the 2FA method is desirable to integrate into dynamic contrast-enhanced MRI for rapid acquisition.
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Affiliation(s)
- Madhava P. Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
| | | | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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91
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Xie C, Gleeson F. The pleura. IMAGING 2016. [DOI: 10.1183/2312508x.10006715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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92
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Lo WC, Li W, Jones EF, Newitt DC, Kornak J, Wilmes LJ, Esserman LJ, Hylton NM. Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes. PLoS One 2016; 11:e0142047. [PMID: 26886725 PMCID: PMC4757528 DOI: 10.1371/journal.pone.0142047] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Accepted: 10/17/2015] [Indexed: 12/14/2022] Open
Abstract
The purpose of this study is to evaluate the predictive performance of magnetic resonance imaging (MRI) markers in breast cancer patients by subtype. Sixty-four patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this study. Each patient received a dynamic contrast-enhanced (DCE-MRI) at baseline, after 1 cycle of chemotherapy and before surgery. Functional tumor volume (FTV), the imaging marker measured by DCE-MRI, was computed at various thresholds of percent enhancement (PEt) and signal-enhancement ratio (SERt). Final FTV before surgery and percent changes of FTVs at the early and final treatment time points were used to predict patients’ recurrence-free survival. The full cohort and each subtype defined by the status of hormone receptor and human epidermal growth factor receptor 2 (HR+/HER2-, HER2+, triple negative) were analyzed. Predictions were evaluated using the Cox proportional hazard model when PEt changed from 30% to 200% in steps of 10% and SERt changed from 0 to 2 in steps of 0.2. Predictions with high hazard ratios and low p-values were considered as strong. Different profiles of FTV as predictors for recurrence-free survival were observed in each breast cancer subtype and strong associations with survival were observed at different PEt/SERt combinations that resulted in different FTVs. Findings from this retrospective study suggest that the predictive performance of imaging markers based on FTV may be improved with enhancement thresholds being optimized separately for clinically-relevant subtypes defined by HR and HER2 receptor expression.
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Affiliation(s)
- Wei-Ching Lo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Wen Li
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Ella F Jones
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - David C Newitt
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Lisa J Wilmes
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
| | - Laura J Esserman
- Department of Surgery and Radiology, University of California San Francisco, San Francisco, California, United States of America
| | - Nola M Hylton
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America
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93
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Shen FU, Lu J, Chen L, Wang Z, Chen Y. Diagnostic value of dynamic contrast-enhanced magnetic resonance imaging in rectal cancer and its correlation with tumor differentiation. Mol Clin Oncol 2016; 4:500-506. [PMID: 27073650 DOI: 10.3892/mco.2016.762] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 01/22/2016] [Indexed: 12/12/2022] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a novel imaging modality that can be used to reflect the microcirculation, although its value in diagnosing rectal cancer is unknown. The present study aimed to explore the clinical application of DCE-MRI in the preoperative diagnosis of rectal cancer, and its correlation with tumor differentiation. To achieve this, 40 pathologically confirmed patients with rectal cancer and 15 controls were scanned using DCE-MRI. The Tofts model was applied to obtain the perfusion parameters, including the plasma to extravascular volume transfer (Ktrans), the extravascular to plasma volume transfer (Kep), the extravascular fluid volume (Ve) and the initial area under the enhancement curve (iAUC). Receiver-operating characteristic (ROC) curves were plotted to determine the diagnostic value. The results demonstrated that the time-signal intensity curve of the rectal cancer lesion exhibited an outflow pattern. The Ktrans, Kep, Ve, and iAUC values were higher in the cancer patients compared with controls (P<0.05). The intraclass correlation coefficients of Ktrans, Kep, Ve and iAUC, as measured by two independent radiologists, were 0.991, 0.988, 0.972 and 0.984, respectively (all P<0.001), indicating a good consistency. The areas under the ROC curves for Ktrans and iAUC were both >0.9, resulting in a sensitivity and specificity of 100% and 93.3% for Ktrans, and of 92.5%, and 93.3% or 100%, for iAUC, respectively. In the 40 rectal cancer cases, there was a moderate correlation between Ktrans and iAUC, and pathological differentiation (0.3<r<0.8, all P<0.05). In conclusion, Ktrans and iAUC were associated with the presence of rectal cancer and differentiation, and therefore may provide novel insights into the preoperative diagnosis of rectal cancer.
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Affiliation(s)
- F U Shen
- Department of Radiology, Changhai Hospital, Shanghai 200433, P.R. China
| | - Jianping Lu
- Department of Radiology, Changhai Hospital, Shanghai 200433, P.R. China
| | - Luguang Chen
- Department of Radiology, Changhai Hospital, Shanghai 200433, P.R. China
| | - Zhen Wang
- Department of Radiology, Changhai Hospital, Shanghai 200433, P.R. China
| | - Yukun Chen
- Department of Radiology, Changhai Hospital, Shanghai 200433, P.R. China
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94
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Yuan Y, Shi H, Tao X. Head and neck paragangliomas: diffusion weighted and dynamic contrast enhanced magnetic resonance imaging characteristics. BMC Med Imaging 2016; 16:12. [PMID: 26833065 PMCID: PMC4736670 DOI: 10.1186/s12880-016-0114-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Accepted: 01/22/2016] [Indexed: 12/20/2022] Open
Abstract
Background To determine the feature values of head and neck paragangliomas on diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI). Methods Patients with primary head and neck paraganglioma who underwent both DWI and DCE-MRI before treatment between January 2010 and June 2013 were identified. Two radiologists assessed apparent diffusion coefficient (ADC) values on DWI and kinetic characteristics on DCE-MRI. The time intensity curves (TICs) and dynamic parameters, including peak height (PH), maximum enhancement ratio (ERmax), time to peak enhancement (Tpeak) and maximum rise slope (Slopemax), were generated and evaluated. Results Ten patients with head and neck paraganglioma were retrospectively analyzed. On conventional MRI, the tumors demonstrated as well-circumscribed, strongly enhanced lesions. Mean ADC value of the lesions was 1.12 ± 0.15 × 10−3 mm2/s. The TICs demonstrated washout pattern (type-III) in all lesions. The mean PH, ERmax, Tpeak and Slopemax value was 121.24 ± 63.99, 193.79 ± 67.18, 8.16 ± 3.29 and 25.42 ± 7.91, respectively. Conclusions Head and neck paragangliomas demonstrate distinctive DWI and DCE-MRI results than for other benign tumors which should be taken into account in further evaluation of MRI on head and neck lesions.
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Affiliation(s)
- Ying Yuan
- Department of Radiology, Shanghai Ninth People's Hospital, Affiliated to JiaoTong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, China.
| | - Huimin Shi
- Department of Radiology, Shanghai Ninth People's Hospital, Affiliated to JiaoTong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, China.
| | - Xiaofeng Tao
- Department of Radiology, Shanghai Ninth People's Hospital, Affiliated to JiaoTong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, China.
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95
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Jansen JFA, Lu Y, Gupta G, Lee NY, Stambuk HE, Mazaheri Y, Deasy JO, Shukla-Dave A. Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer. World J Radiol 2016; 8:90-97. [PMID: 26834947 PMCID: PMC4731352 DOI: 10.4329/wjr.v8.i1.90] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Revised: 09/24/2015] [Accepted: 11/25/2015] [Indexed: 02/06/2023] Open
Abstract
AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC).
METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (Ktrans) and volume fraction of the extravascular extracellular space (ve). Image texture analysis was then employed on maps of Ktrans and ve, generating two texture measures: Energy (E) and homogeneity.
RESULTS: No significant changes were found for the mean and standard deviation for Ktrans and ve between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of ve was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04).
CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.
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96
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Beuzit L, Eliat PA, Brun V, Ferré JC, Gandon Y, Bannier E, Saint-Jalmes H. Dynamic contrast-enhanced MRI: Study of inter-software accuracy and reproducibility using simulated and clinical data. J Magn Reson Imaging 2015; 43:1288-300. [PMID: 26687041 DOI: 10.1002/jmri.25101] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Accepted: 11/05/2015] [Indexed: 12/16/2022] Open
Abstract
PURPOSE To test the reproducibility and accuracy of pharmacokinetic parameter measurements on five analysis software packages (SPs) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), using simulated and clinical data. MATERIALS AND METHODS This retrospective study was Institutional Review Board-approved. Simulated tissues consisted of pixel clusters of calculated dynamic signal changes for combinations of Tofts model pharmacokinetic parameters (volume transfer constant [K(trans) ], extravascular extracellular volume fraction [ve ]), longitudinal relaxation time (T1 ). The clinical group comprised 27 patients treated for rectal cancer, with 36 3T DCE-MR scans performed between November 2012 and February 2014, including dual-flip-angle T1 mapping and a dynamic postcontrast T1 -weighted, 3D spoiled gradient-echo sequence. The clinical and simulated images were postprocessed with five SPs to measure K(trans) , ve , and the initial area under the gadolinium curve (iAUGC). Modified Bland-Altman analysis was conducted, intraclass correlation coefficients (ICCs) and within-subject coefficients of variation were calculated. RESULTS Thirty-one examinations from 23 patients were of sufficient technical quality and postprocessed. Measurement errors were observed on the simulated data for all the pharmacokinetic parameters and SPs, with a bias ranging from -0.19 min(-1) to 0.09 min(-1) for K(trans) , -0.15 to 0.01 for ve , and -0.65 to 1.66 mmol.L(-1) .min for iAUGC. The ICC between SPs revealed moderate agreement for the simulated data (K(trans) : 0.50; ve : 0.67; iAUGC: 0.77) and very poor agreement for the clinical data (K(trans) : 0.10; ve : 0.16; iAUGC: 0.21). CONCLUSION Significant errors were found in the calculated DCE-MRI pharmacokinetic parameters for the perfusion analysis SPs, resulting in poor inter-software reproducibility. J. Magn. Reson. Imaging 2016;43:1288-1300.
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Affiliation(s)
- Luc Beuzit
- Department of Radiology, CHU Rennes, France
| | | | | | - Jean-Christophe Ferré
- Department of Radiology, CHU Rennes, France.,Neurinfo MR Imaging Platform, University of Rennes 1, France
| | | | - Elise Bannier
- Department of Radiology, CHU Rennes, France.,Neurinfo MR Imaging Platform, University of Rennes 1, France
| | - Hervé Saint-Jalmes
- LTSI, UMR 1099, INSERM, University of Rennes 1, France.,Eugène Marquis Cancer Institute, Rennes, France
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97
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Cheng L, Tunariu N, Collins DJ, Blackledge MD, Riddell AM, Leach MO, Popat S, Koh DM. Response evaluation in mesothelioma: Beyond RECIST. Lung Cancer 2015; 90:433-41. [PMID: 26443279 DOI: 10.1016/j.lungcan.2015.08.012] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Revised: 07/05/2015] [Accepted: 08/17/2015] [Indexed: 12/12/2022]
Abstract
Malignant pleural mesothelioma (MPM) typically demonstrates a non-spherical growth pattern, so it is often difficult to accurately categorize change in tumour burden using size-based tumour response criteria (e.g., WHO (World Health Organisation), RECIST (Response Evaluation Criteria in Solid Tumours) and modified RECIST). Functional imaging techniques are applied to derive quantitative measurements of tumours, which reflect particular aspects of the tumour pathophysiology. By quantifying how these measurements change with treatment, it is possible to observe treatment effects. In this review, we survey the existing roles of CT and MRI for the management of MPM, including the currently applied size measurement criteria for the assessment of treatment response. New functional imaging techniques, such as positron emission tomography (PET), diffusion-weighted MRI (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) that may potentially improve the assessment of treatment response will be highlighted and discussed.
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Affiliation(s)
- Lin Cheng
- EPSRC-CR UK Cancer Imaging Centre, Institute of Cancer Research, UK
| | - Nina Tunariu
- EPSRC-CR UK Cancer Imaging Centre, Institute of Cancer Research, UK; Department of Radiology, Royal Marsden Hospital, UK
| | - David J Collins
- EPSRC-CR UK Cancer Imaging Centre, Institute of Cancer Research, UK
| | | | | | - Martin O Leach
- EPSRC-CR UK Cancer Imaging Centre, Institute of Cancer Research, UK
| | - Sanjay Popat
- Department of Medical Oncology, Royal Marsden Hospital, UK
| | - Dow-Mu Koh
- EPSRC-CR UK Cancer Imaging Centre, Institute of Cancer Research, UK; Department of Radiology, Royal Marsden Hospital, UK.
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Mehrabian H, Da Rosa M, Haider MA, Martel AL. Pharmacokinetic analysis of prostate cancer using independent component analysis. Magn Reson Imaging 2015; 33:1236-1245. [DOI: 10.1016/j.mri.2015.08.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Revised: 08/12/2015] [Accepted: 08/17/2015] [Indexed: 10/23/2022]
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99
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Multiparametric MRI With Dynamic Contrast Enhancement, Diffusion-Weighted Imaging, and 31-Phosphorus Spectroscopy at 7 T for Characterization of Breast Cancer. Invest Radiol 2015; 50:766-71. [DOI: 10.1097/rli.0000000000000183] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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100
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Han M, Kim SY, Lee SJ, Choi JW. The Correlations Between MRI Perfusion, Diffusion Parameters, and 18F-FDG PET Metabolic Parameters in Primary Head-and-Neck Cancer: A Cross-Sectional Analysis in Single Institute. Medicine (Baltimore) 2015; 94:e2141. [PMID: 26632740 PMCID: PMC5059009 DOI: 10.1097/md.0000000000002141] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
This study aimed to investigate the relationships among parameters from dynamic contrast-enhanced (DCE) MRI, diffusion-weighted MRI (DWI), and F-fluorodeoxyglucose (F-FDG) PET in patients with primary head-and-neck squamous cell carcinoma (HNSCC).A total of 34 patients with primary HNSCC underwent DCE-MRI, DWI, and F-FDG PET before treatment. The perfusion parameters (Ktrans, Ktransmax, Kep, Ve, Vp, and AUC60) from DCE-MRI and ADC (ADCmean, ADCmin) values from DWI were calculated within the manually placed ROI around the main tumor. Standardized uptake value (SUVmax, SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG = SUVmean × MTV) were calculated with thresholds of 3.0 SUV. The associations between parameters were evaluated by Pearson correlation analysis.Significant correlations were identified between Ktrans and Kep (r = 0.631), Ktrans and Ve (r = 0.603), Ktrans and ADCmean (r = 0.438), Ktransmax and Kep (r = 0.667), Ktransmax and Vp (r = 0.351), Ve and AUC60 (r = 0.364), Ve and ADCmean (r = 0.590), and Ve and ADCmin (r = 0.361). ADCmin was reversely correlated with TLG (r = -0.347). Tumor volume was significantly associated with Ktransmax (r = 0.348).The demonstrated relationships among parameters from DCE, DWI, and F-FDG PET suggest complex interactions among tumor biologic characteristics. Each diagnostic technique may provide complementary information for HNSCC.
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Affiliation(s)
- Miran Han
- From the Department of Radiology (MH, SYK, JWC), and Nuclear Medicine (SJL), Ajou University School of Medicine, Ajou University Medical Center, Suwon, Republic of Korea
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