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Ultrasonography |
1 From the Departments of Diagnostic Imaging and Nuclear Medicine (A.L., T.H., T.S., K.T.), Otolaryngology–Head and Neck Surgery (R.A., S.T., J.I.), and Therapeutic Radiology and Oncology (M.H.), Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan; Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana, Ill (M.F.I.); and Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tenn (A.B.B.). Received December 13, 2005; revision requested January 25, 2006; revision received March 22; accepted April 20; final version accepted July 17. Supported by grant-in-aid #17659366 from the Ministry of Education, Culture, Sports, Science and Technology of Japan. Address correspondence to A.L., Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, CCC-1118 MCN, 1161 21st Ave, South Nashville, TN 37232-2675 (e-mail: Andrej.lyshchik{at}vanderbilt.edu).
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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Materials and Methods: The study protocol was approved by the hospital review board; each patient gave written informed consent. One hundred forty-one peripheral neck LNs (60 metastatic, 81 metastasis free) in 43 consecutive patients (22 men, 21 women; mean age, 58 years ± 13 [standard deviation]) were examined. Patients referred for surgical treatment of suspected thyroid or hypopharyngeal cancer were examined with gray-scale ultrasonography (US), power Doppler US, and sonoelastography. At gray-scale and power Doppler US, the following LN characteristics were evaluated: short-axis diameter, short-to-long-axis diameter ratio, echogenicity, calcifications, and vascularity. A four-point rating scale was used to evaluate the US elastograms for LN visibility, relative brightness, margin regularity, and margin definition. In addition, strains of LN and surrounding neck muscles were measured on elastograms, and the muscle-to-LN strain ratio—that is, the strain index—was calculated. The diagnostic potential of the examined criteria for metastatic involvement was evaluated with univariate analysis and multivariate generalized estimating equation (GEE) regression. P < .05 indicated statistical significance.
Results: A strain index greater than 1.5 had high utility in metastatic LN classification, with 98% specificity, 85% sensitivity, and 92% overall accuracy. These results were significantly better than those obtained by using the best gray-scale criterion—that is, a short-to-long-axis diameter ratio greater than 0.5—which had 81% specificity, 75% sensitivity, and 79% overall accuracy.
Conclusion: Sonoelastography had high accuracy (92%) in the differentiation of benign and metastatic cervical LNs in patients suspected of having thyroid or hypopharyngeal cancer.
© RSNA, 2007
Evaluation of cervical lymph nodes is an important procedure for patients with thyroid or hypopharyngeal cancers because the results influence the prognosis and the choice of therapy (1–3). In these patients, ultrasonography (US) can be used to assess the location, number, size, internal characteristics, and vascularity of cervical lymph nodes. However, the US criteria for metastatic lymph nodes are controversial (4,5).
Sonoelastography is an imaging modality used to map the elastic properties of examined soft tissues (6). Because the elasticity of biologic tissues cannot be measured directly, the majority of the proposed elastographic techniques involve an indirect approach to estimating tissue stiffness. Briefly, mechanical stimuli of some kind (compression or vibration) are propagated into the tissue, and the resultant strain distribution is detected and characterized by using a conventional imaging technique such as US (7,8). The results of the tissue compression are displayed as an image called an elastogram, on which stiff areas appear dark and soft areas appear bright. Although sonoelastography is not yet used in routine clinical practice, it has been shown to be useful in the differential diagnosis of breast, thyroid, and prostate cancers (9–11). Our recent study results showed that sonoelastography is a promising imaging technique that can provide assistance in the differentiation of benign and metastatic thyroid tumors (10). However, to our knowledge, sonoelastography has not been applied to lymph node characterization.
Neck lymph nodes are well positioned for elastographic examination: They are easily accessible and can be efficiently compressed against underlying anatomic structures with use of a US probe. The information on lymph node stiffness would seem to be clinically useful for guidance of percutaneous biopsy and/or nodal dissection. Use of this information can also improve patient follow-up by enabling detection of cancer recurrence (depicted as stiffness) at early stages. Thus, the aim of our study was to prospectively estimate the accuracy of sonoelastography in the differentiation of benign and metastatic cervical lymph nodes in patients suspected of having thyroid or hypopharyngeal cancer, with histologic nodal findings as the reference standard.
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MATERIALS AND METHODS |
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Patients
The study was conducted at Kyoto University Hospital during a 12-month period: from January through December 2005. The study protocol was approved by the institutional review board. Before enrollment, each patient gave written informed consent, as required by the Kyoto University Human Study Committee. The inclusion criterion was preoperative suspicion of thyroid or hypopharyngeal cancer based on clinical, imaging, and cytologic findings. Patients who refused to give informed consent or who did not undergo surgical treatment were excluded from the study. All patients included in our study underwent surgery, and the final diagnosis was based on the results of histologic examination of the resected specimens.
A total of 47 patients (23 men, 24 women; mean age, 58 years ± 13 [standard deviation]; range, 32–85 years) were referred for our study. Four patients (one man, three women) were excluded owing to a lack of informed consent for sonoelastography. The remaining 43 consecutive patients (22 men, 21 women; mean age, 58 years ± 13; range, 32–85 years) who met the inclusion criteria were included in this prospective study (Fig 1).
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For all patients, the US examination started with gray-scale imaging. The positioning of the patients for imaging was identical to that used for standard clinical neck US: The patient was positioned on his or her back with the neck slightly extended over a pillow. During gray-scale US, lymph nodes were identified, electronic calipers were used to measure the nodes in three planes, and a region of interest for sonoelastography was identified. The size of the gray-scale images was 40 mm in depth and 40 mm in lateral width; the size of the region of interest for sonoelastography was 35 mm in depth and 30 mm in lateral width. At gray-scale US, the following US characteristics of the examined lymph nodes were evaluated: short-axis diameter and short-to-long-axis diameter ratio in the longitudinal plane with respect to the patient's neck, echogenicity, and presence of micro- or macrocalcifications (12). Lymph nodes were assessed for echogenicity with respect to the surrounding muscles and classified as hypoechoic, isoechoic, or hyperechoic. The lymph node hilum, which normally appears as a hyperechoic region (13), was excluded in this assessment.
At power Doppler US, the type and intensity of nodal blood flow were evaluated for all examined lymph nodes. Two types of lymph node vascularity were identified: In type 1, flow signals were absent or the blood flow was limited to the lymph node hilum. In type 2, there was increased peripheral blood flow (14). Doppler amplification was controlled so that the surrounding tissues displayed minimal noise.
Radiofrequency Image Acquisition and Off-line Strain Image Reconstruction
After gray-scale and power Doppler US, both examiners (A.L., T.H.) acquired a separate new set of radiofrequency echo data for sonoelastography for each lymph node. Before image acquisition, light compression (precompression) was applied, with use of the US probe, to the anterior part of the neck above the examined lesion to fix the position of the lymph node and limit its lateral movement. Then, a second light compressive force (main compression) was applied to the same area. During the steady increase in compressive force, a total of 26 images were acquired at a speed of 16 frames per second. After acquisition, the radiofrequency images were stored in the scanner's memory and then exported to an external personal computer for off-line processing. Preparation for the radiofrequency image acquisitions, including region of interest selection and lymph node precompression, required 1–2 minutes; the radiofrequency image acquisitions required 1–2 seconds; and image storage and transfer required 2–3 minutes of examination time. The precompression and the main compression were applied by using a freehand technique, without measurement of the actual force applied to the US transducer.
Strain images were processed from the original radiofrequency data by using cross-correlation algorithms (15,16). These algorithms were identical to the algorithm used in our previous study for off-line elastographic imaging of thyroid gland tumors (10). Of the two acquired sets of strain images for each examined lymph node, only the image set that had the lowest amount of noise and decorrelation artifacts (due to lateral and out-of-plane motion) was selected for final analysis. The strain image set to be used for final analysis was selected by consensus. From 26 successive frames taken for each nodule, we generated 25 displacement images by comparing the neighboring frames. The derivative of each displacement image was calculated to be the initial strain image.
After the calculation of the initial strain images, an "averaged" elastogram was formed by averaging successful initial strain images in the strain series. To obtain compatible results of relative strain values between patients, we normalized each elastogram by first subtracting the average strain, before averaging. The image-processing software averaged the shift and the strain and then discarded them before displaying the image. To improve the quality of the final averaged elastograms, frames affected by a substantial amount of noise and decorrelation artifacts on the lymph node and/or the surrounding muscle areas were excluded from the series. The images that would be excluded from the series were selected by consensus. For all patients, strain image processing was performed by the same radiologist (A.L.). Reconstruction of one set of strain images usually required 30–40 minutes of computer processing time.
The final averaged elastogram for each examined lymph node was evaluated with use of the following qualitative criteria, which were assessed by using a four-point scale: For lymph node visualization, a rating of not visible, barely visible, partially visible, or very visible was assigned. For relative lymph node brightness with respect to the surrounding neck muscles, a classification of very dark, substantially darker than surrounding muscle, slightly darker than surrounding muscle, or same brightness as or brighter than surrounding muscle was assigned. For regularity of the outline of the lymph node margin with respect to smoothness of the lymph node contour, a classification of very irregular, moderately irregular, slightly irregular, or regular was assigned. The outline of the lymph node margin was also assessed for definability: A classification of indistinct, less than 50% of border distinct, or more than 50% of border distinct was assigned. In addition, the mean values of lymph node strain and surrounding neck muscle strain were measured in each region of interest, which was placed on the same image over the examined lymph node and over the surrounding neck muscles, and the muscle-to–lymph node strain ratio (ie, strain index) was calculated. Region of interest sizes ranged from 5 to 10 mm. To avoid stress decay over the examination depth, the region of interest for the muscle tissue was placed at a depth similar to the depth of the analyzed lymph node. The difference in region of interest depth never exceeded 10 mm.
Surgery and Histologic Examination
All patients underwent lymphadenectomy and surgical removal of the primary tumor within 3 days after US. All possible measurements were taken to ensure an accurate one-to-one comparison between the lymph nodes that were imaged and those that were removed during surgery. After US examination, the location of each lymph node was mapped with respect to the surrounding anatomic structures (ie, trachea, main vessels, and sternocleidomastoid muscle) and plotted on the sketch diagram of the neck. In addition, the surgeons were assisted by a radiologist (T.H.) for correlation of the lymph node location seen on the US images with the lymph nodes seen in the lymphadenectomy specimens. After being resected, each lymph node specimen was fixed in 10% formalin, embedded in paraffin, cut into thin slices, and stained with standard hematoxylin-eosin. During histologic examination, two or three histologic slices per lymph node were examined. The final diagnosis of metastatic lymph node involvement was made by a pathologist who had 15 years of experience performing histologic cervical lymph node diagnosis. Certain additional features that can affect the elastic properties of examined lymph nodes, such as complete versus incomplete metastatic involvement and presence of necrosis and/or calcifications, were also recorded.
Statistical Analyses
Quantitative variables were compared by using the Mann-Whitney U test. Qualitative variables were compared by using the 
2 test. The elastographic characteristics of each lymph node were registered separately and processed blindly for statistical evaluation. The unit of analysis was each lymph node rather than each patient. The value of each visual and qualitative criterion that showed the highest diagnostic accuracy in the distinction between benign and metastatic lymph nodes was selected as the cutoff value. One-way analysis of variance was performed to assess the differences in elastographic characteristics between the metastatic and benign lymph nodes. A multivariate analysis was performed by using the generalized estimating equation method to select the variables (ie, examined US and elastographic criteria) that were independently associated with lymph node metastasis (17,18). This is a repeated-measures analysis for correlated dichotomous outcomes (metastatic lymph nodes) and a set of covariates (examined US and elastographic criteria). The generalized estimating equation method was used to adjust the intracorrelation effect for patients who had multiple measurements. Each variable had a binary value (greater than and less than the selected cutoff value).
The model used was selected on the basis of the Akaike information criterion and the Schwarz Bayesian criterion. For each criterion examined, the sensitivity, specificity, positive and negative predictive values, and overall accuracy in the differentiation between benign and metastatic lymph nodes were calculated. Quantitative data are presented as means ± 1 standard deviation. P < .05 indicated statistical significance. Post hoc power analysis involving the use of the two-sided Fisher exact test for binomial distribution was performed to determine whether the resultant sample size was of sufficient magnitude to support confidence in the outcome results (19). The statistical analyses were performed by using a statistical software package (StatView, version 5.0; SAS Institute, Cary, NC).
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RESULTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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Lymph Nodes
A total of 141 peripheral neck lymph nodes (60 [43%] metastatic, 81 [57%] metastasis free) were examined. Metastasis from papillary thyroid cancer was histologically diagnosed in 39 nodes (28%), and metastasis from hypopharyngeal squamous cell cancer was histologically diagnosed in 21 (15%) nodes. Seventeen of the 43 patients (11 men, six women) had metastatic lymph nodes: Five patients had one metastatic lymph node each; four patients, two each; three patients, three each; two patients, four each; two patients, five each; and one patient, six each.
Nineteen patients (seven men, 12 women) had benign lymph nodes. Of these 19 patients, three had one benign lymph node each; five, two benign nodes each; four, three benign nodes each; three, five benign nodes each; three, six benign nodes each; and one, eight benign nodes each.
Seven patients (four men, three women) had both metastatic and metastasis-free (benign) lymph nodes. Of these seven patients, three had one metastatic and one benign lymph node; one patient, one metastatic and two benign nodes; one patient, one metastatic and five benign nodes; one patient, three metastatic and two benign nodes; and one patient, six metastatic and three benign nodes.
B-Mode US
There was no significant difference in the gray-scale US or elastographic lymph node characteristics between the patients with thyroid abnormalities and those with hypopharyngeal abnormalities. The characteristics of the examined lymph nodes are listed in Table 1, and the diagnostic accuracy of each of the features tested is detailed in Table 2.
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Power Doppler US
Performing power Doppler US did not substantially improve the diagnostic accuracy of the US criteria for metastatic lymph nodes. Although only one (1%) benign lymph node had peripheral vascularity, this feature was observed in less that half (47%) of the metastatic lymph nodes (P < .01).
Sonoelastography
The majority (93%) of the metastatic lymph nodes (Fig 2) were very or partially visible on US elastograms and had a visualization score greater than 2. This finding was observed in 33% (P < .01) of the benign lymph nodes (Fig 3). Although the majority of the metastatic lymph nodes were visible on US elastograms, only 63% of them were substantially darker (ie, stiffer) than the surrounding tissues and had a relative brightness index lower than or equal to 2. Thirty-seven percent of the metastatic lymph nodes, as well as 95% of the benign nodes, were slightly darker, brighter, or the same in brightness compared with the surrounding muscles.
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In contrast, the diagnostic accuracy of the muscle-to–lymph node strain index was high. There was a significant difference in mean strain index between the benign and metastatic lymph nodes: 0.8 ± 0.5 (95% CI: 0.7, 0.9) versus 4.4 ± 3.6 (95% CI: 3.5, 5.3), respectively (P < .01). Among the numerous cutoff values tested, the strain index cutoff value of 1.5 enabled the best distinction between metastatic and benign lymph nodes. The majority (98%) of the benign lymph nodes were less than 1.5 times stiffer than the surrounding muscles; however, 85% of the metastatic lymph nodes were more than 1.5 times stiffer than the surrounding muscles (P < .01). When the diagnostic accuracy of a strain index greater than 1.5 was calculated, results showed that this criterion had 85% sensitivity, 98% specificity, a 96% positive predictive value, a 90% negative predictive value, and the highest overall accuracy (92%) of all the diagnostic criteria examined. The false-negative results obtained with this criterion included metastatic lymph nodes that were less than 1.5 times stiffer than the surrounding muscles owing to incomplete replacement of normal lymphoid tissues by malignant cells in six lymph nodes (Fig 4) and to central necrosis in three lymph nodes (Fig 5).
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Post Hoc Power Analysis
The estimated proportions for the power analysis were based on the overall accuracies of the best B-mode US (short-to-long-axis diameter ratio > 0.5) and elastographic (strain index > 1.5) criteria for the diagnosis of metastatic lymph nodes (79% and 92%, respectively). According to the power analysis results, our sample had a power of 84% for detection of the difference between sonoelastography and routine B-mode US in the diagnosis of metastatic lymph nodes at a significance level of 5%. This finding supports the adequacy of the sample size used in our study.
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DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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Lymph node shape also has been used as a criterion for the detection of metastatic lymph nodes. In some previous studies, as well as in our current investigation, metastatic lymph nodes often appeared as round lesions, whereas benign nodes are usually flat or oval (23). The presence of a hyperechoic hilum and changes in the internal echogenicity of the nodes are usually considered strong diagnostic criteria for benign lymph nodes (24). It has been reported that 84%–92% of benign nodes but less than 5% of metastatic nodes have a hyperechoic hilum (25). On the other hand, some authors have reported that a hyperechoic hilum can be visualized in up to 51.5% of metastatic nodes (26). An absent lymph node hilum had high sensitivity but low specificity and overall accuracy. In contrast to this finding, abnormal lymph node echogenicity was a specific but not sensitive criterion.
Calcification in metastatic lymph nodes is generally rare (27,28). Some authors, however, have reported that about 68.7% of metastatic nodes from papillary cancer of the thyroid had calcification at US and histologic analysis (29). These findings are in disagreement with our results: Nodal calcifications were detected in only two of the lymph nodes that we examined, and they were specific but not sensitive.
Assessment of internal nodal vascularity at color or power Doppler US yielded additional criteria for the diagnosis of metastatic lymph nodes. It has been noted that benign lymph nodes tend to show hilar vascularity or appear avascular (30,31). In contrast, metastatic nodes tend to have peripheral or mixed (both peripheral and hilar) vascularity (32). In our study, power Doppler US vascularity had high specificity but low sensitivity. These findings correspond to previously published reports that the value of power Doppler US cannot compete with that of fine-needle aspiration biopsy in the diagnosis of metastatic adenopathy (33).
Our results in the differential diagnosis of metastatic lymph nodes at sonoelastography show that the majority of the benign nodes had the same brightness as the surrounding anatomic structures and therefore were not clearly visible on US elastograms. This is probably because of the small difference in elastic properties between benign lymph nodes and surrounding neck muscles. In contrast, the majority of the metastatic lymph nodes were partially or very visible and appeared substantially darker on the US elastograms. Again, these findings are probably related to the relative stiffness of metastatic lymph nodes compared with the elasticity of the surrounding muscles and other anatomic structures. However, additional studies of the real biomechanical properties of benign and metastatic lymph nodes performed by using previously elaborated measurement techniques are needed to elucidate these findings (34,35).
The margins of the metastatic lymph nodes on US elastograms were more regular and distinct than the margins of the benign lymph nodes. This finding might reflect the greater difference in elastic properties between metastatic lymph nodes and surrounding tissues or a certain desmoplastic reaction that creates a stiff rim around metastatic lymph nodes. All of the visual elastographic criteria examined in our study, although promising, had low diagnostic accuracy and were comparable in accuracy to the routine US criteria.
On the other hand, quantitative elastographic measurements of relative lymph node elasticity, obtained by comparing the absolute values of lymph node strain with the absolute values of surrounding muscle strain, had the best diagnostic accuracy of all the US and elastographic criteria evaluated. Our results show that the majority of benign lymph nodes were less than 1.5 times stiffer than the surrounding muscles and that the majority of the metastatic lymph nodes were more than 1.5 times stiffer. The high diagnostic accuracy of this criterion was confirmed by the results of multivariate regression analysis. This finding suggests that sonoelastography can be helpful in the selection of suspicious neck lymph nodes that should be examined at percutaneous biopsy and/or nodal dissection for accurate preoperative staging and individual therapy selection for patients with thyroid or hypopharyngeal cancer.
Some of the limitations of our study should be addressed. During histologic examination, only two or three tissue slices per lymph node were examined; therefore, we could not accurately assess the extent of tumor involvement in the nodes. This should be investigated in detail in the future, because the severity of metastatic involvement may affect the strain characteristics of a lymph node. In addition, the difference in elastic properties between the benign and metastatic lymph nodes measured at sonoelastography was not confirmed by direct measurements of the biomechanical properties of the examined tissues removed at surgery. Thus, future studies that yield the biomechanical data needed to support correct interpretations of abnormal US elastograms are warranted. Because of the study design, we were unable to assess the observers' ability to diagnose thyroid cancer on the basis of the elastogram findings. Therefore, future studies to evaluate the inter- and intraobserver variability and the reliability of sonoelastography in the detection of metastatic lymph node involvement are needed.
At present, the methods used to perform sonoelastography are not ideal. Real-time elastography, which is incorporated into some commercially available US scanners, involves the use of fast strain image reconstruction algorithms. However, this technique is not as accurate as the off-line processing of strain images. On the other hand, offline processing of US elastograms, as performed in the present study, is too time consuming and labor intensive to be used in busy clinical settings. Thus, future advances in image acquisition and reconstruction algorithms are needed to improve image quality and increase the clinical utility of this method. In addition, the image quality and diagnostic performance of US elastograms acquired with freehand compression depend substantially on the quality of the compression and the specifications of the elasticity formation algorithms.
In the present study, the overall quality of the strain images was substantially affected by decorrelation noise, which resulted from the nonaxial and out-of-plane motion of the examined lesions and from the pulsation of the carotid artery. This problem may be partially solved when the computational capability of US systems increases to the extent that we can acquire higher quality primary images at high frame rates. Another drawback is that the compression load applied with freehand elastography is not standardized and thus may result in some inter- and intraobserver variability. All of these issues require thoughtful elaboration in the future to improve the diagnostic accuracy of sonoelastography in patients with cancer.
In conclusion, sonoelastography is a promising imaging technique that can provide assistance in the differentiation of benign and metastatic neck lymph nodes. Our findings suggest that sonoelastography can be helpful in the selection of suspicious neck lymph nodes that should be examined at cytologic examination or open biopsy for accurate preoperative staging and individual therapy selection for patients suspected of having thyroid or hypopharyngeal cancer.
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ADVANCE IN KNOWLEDGE |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Abbreviations: CI = confidence interval
Authors stated no financial relationship to disclose.
Author contributions: Guarantors of integrity of entire study, A.L., T.H.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; literature research, A.L.; clinical studies, all authors; statistical analysis, A.L.; and manuscript editing, A.L., T.H., A.B.B.
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References |
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S. K. Venkatesh, M. Yin, J. F. Glockner, N. Takahashi, P. A. Araoz, J. A. Talwalkar, and R. L. Ehman MR Elastography of Liver Tumors: Preliminary Results Am. J. Roentgenol., June 1, 2008; 190(6): 1534 - 1540. [Abstract] [Full Text] [PDF]
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