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Role of dynamic MRI in differentiating benign from malignant follicular thyroid nodule
Auris Nasus Larynx 38 (2011) 718–723 www.elsevier.com/locate/anl
Role of dynamic MRI in differentiating benign from malignant follicular thyroid nodule Nikhil Gupta a,*, Choden Norbu b, Binita Goswami d, Veena Chowdhury c, L. RaviShankar e, Praveen Gulati f, Arun Kakar b a Department of Surgery, Lady Hardinge Medical College, Delhi, India Department of Surgery, Maulana Azad Medical College and Associated Lok Nayak and GB Pant Hospitals, New Delhi, India c Department of Radiodiagnosis, Maulana Azad Medical College and Associated Lok Nayak and GB Pant Hospitals, New Delhi, India d Department of Biochemistry, Maulana Azad Medical College and Associated Lok nayak and GB Pant Hospitals, New Delhi, India e Thyroid Division, Institute of Nuclear Medicine and allied Sciences, Timarpur, Delhi, India f MR Imaging Centre, Green park, Delhi, India b
Received 19 September 2010; accepted 7 February 2011 Available online 13 May 2011
Abstract Objectives: Thyroid nodular swellings are very common, consisting of both benign and malignant ones. Fine needle aspiration cytology is an excellent diagnostic modality for papillary cancers, medullary cancers, colloid goiter and lymphoma but fails in differentiating follicular adenomas from carcinomas. The purpose of this study was to evaluate role of Dynamic MRI with signal intensity time curve evaluation in differentiating benign from malignant follicular nodules. Materials and methods: This study was carried out in Department of Surgery in collaboration with department of Radiodiagnosis, Maulana Azad Medical College, Delhi. 28 patients with solitary thyroid nodule (STN) having follicular etiologies were included in the study. Dynamic MRI with signal intensity time curve analysis was carried out in all the cases and findings were compared with the final diagnosis based on histopathological examination of surgical specimen. Results: In the present study, rapid enhancement was seen in 87.5% of malignant cases and washout pattern was seen in 87.5% of malignant STN ( p = 0.019). Only 20% of the benign lesions showed washout pattern ( p = 0.0034). Benign cases demonstrated gradual enhancement in 85% cases as compared to 12.5% in malignant STN ( p = 0.0098). Conclusion: This study suggests that signal intensity time curve may help in differentiating benign from malignant follicular thyroid nodules. # 2011 Elsevier Ireland Ltd. All rights reserved. Keywords: Follicular adenoma; Signal intensity time curve; Dynamic MRI
Abbreviations: STN, solitary thyroid nodule; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; FNAC, fine needle aspiration cytology; FS, frozen section; TSE, turbo spin echo; STIR, short T1 inversion recovery; TRUE FISP, coherent gradient echo (Siemens); TE, echo time; TR, repetition time; FOV, field of view; DWI, diffusion weighted MR imaging; ADC, apparent diffusion coefficient; DCE-MRI, dynamic contrast medium-enhanced magnetic resonance imaging. * Corresponding author. Tel.: +91 011 9810592084. E-mail addresses: [email protected] (N. Gupta), [email protected] (C. Norbu), [email protected] (B. Goswami), [email protected] (V. Chowdhury), [email protected] (L. RaviShankar), [email protected] (P. Gulati), [email protected] (A. Kakar).
1. Introduction Thyroid nodules are very common clinical entities. Clinical palpation suggests a prevalence of thyroid nodules in 1–7% of the general population [1]. The overwhelming majority of thyroid nodules are benign with the incidence of malignancy being only 5% [2]. It may not always be possible to differentiate precisely a benign pathology from the malignant pathology with the available diagnostic modalities. Fine needle aspiration cytology though accurate in diagnosing thyroid lesions, has limitations in differentiating follicular malignancy from follicular adenomas [2]. Ultra-
0385-8146/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.anl.2011.02.002
N. Gupta et al. / Auris Nasus Larynx 38 (2011) 718–723
sonography has a low sensitivity as well as specificity in definitive differential diagnosis of thyroid nodules [3]. Computed tomography (CT) of neck is often limited by streak artifacts caused by swallowing or respiratory motion and X-ray beam hardening [4]. MRI can demonstrate gross morphological features of nodules; however, it cannot accurately differentiate benign from malignant lesions [5]. This dilemma necessitated the discovery of newer preferably non invasive diagnostic modalities for the diagnosis of thyroid pathologies. The introduction of nuclear magnetic resonance spectroscopy as a diagnostic tool has made it possible to understand the patterns of metabolite changes in pathological processes [6]. Thyroid tissue characterization achieved by the adoption of newer techniques such as proton spectroscopy has indeed proved to be beneficial in the differential diagnosis of thyroid disorders as shown in our previous study [7]. There are studies that have evaluated the utility of Dynamic MRI with time signal intensity curve specifications as an important criterion in differentiating benign and malignant lesions in breast MR imaging [8–10]. However, there are very few studies evaluating the role of signal intensity time curve in thyroid disorders [11,12]. Two different criteria are used to describe lesion enhancement kinetics. First, behavior of signal intensity in the early phase after the administration of contrast material is evaluated by means of the steepness of the post contrast signal intensity curve; and second, the behavior of signal intensity in the intermediate and late post contrast periods. Visual or quantitative evaluation is dependent on the shape of the time–signal intensity curve: whether the signal intensity continues to increase after the initial upstroke, whether it is cut off and reaches a plateau, or whether it washes out. The relative enhancement (percentage of signal intensity increase) is calculated according to the enhancement formula ((Sic SI)/SI) 100, where SI and SIc are the precontrast and the postcontrast signal intensities, respectively. By plotting the lesion signal intensity over time, the time–signal intensity curve was obtained to depict the lesions’ enhancement behavior. The signal intensity time curves are classified according to their shapes as [13]: Type I steady enhancement Type II plateau of signal intensity Type III washout of signal intensity The three curve types differ in their signal intensity time courses in the intermediate and late postcontrast periods (Fig. 1). Type I is straight or curved. In type Ia, the straight type, the signal intensity continues to increase over the entire dynamic period; in type Ib, the curved type, the time–signal intensity curve is flattened in the late postcontrast period because of saturation effects. Type II is a plateau in which there is an initial upstroke, after which enhancement is abruptly cut off, and the signal intensity plateaus in the
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Fig. 1. Signal intensity time curve. (A) Early postcontrast phase, (B) intermediate and late postcontrast phase. Type I corresponds to a straight (Ia) or curved (Ib) line; enhancement continues over the entire dynamic study. Type II is a plateau curve with after the initial upstroke. Type III is a washout pattern.
intermediate and late postcontrast periods. Type III is a washout in which there is an initial upstroke, after which enhancement is abruptly cut off, and the signal intensity decreases (washes out) in the intermediate postcontrast period (i.e., 2–3 min after injection of contrast material). The lesion enhancement rate in the early postcontrast period (also known as ‘‘enhancement velocity’’ or ‘‘slope of enhancement’’) serves as a differential diagnostic criterion, with malignant lesions exhibiting stronger and faster enhancement than benign lesions. The blood circulation at the capillary level is determined by the metabolic activity of the tissue. In pathological processes (such as tumour genesis), the microcirculation becomes altered. There can be an increase in microvascular density resulting from the growth of new capillary networks (angiogenesis) as well as vasodilatation of existing vessels. The biologic basis of the different time curves for benign and malignant lesions may be due to the presence of this increased vessel density and arteriovenous anastomoses with rapid outflow and thus fading of the contrast material in malignant lesions. On the basis of studies published in literature, the lesions are classified according to the different time signal intensity curves. A type I curve is considered to be indicative of a benign lesion, type II curve is suggestive of malignancy and type III curve is indicator of a malignant lesion. Our study attempts to evaluate the plausible role of signal intensity time curves in differentiating benign from malignant follicular neoplasms.
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N. Gupta et al. / Auris Nasus Larynx 38 (2011) 718–723
2. Materials and methods The present prospective study was conducted in the department of surgery in collaboration with the department of radio diagnosis, Maulana Azad medical college, New Delhi from February 2007 to July 2009. This study was approved by the ethical committee of the institution. Patients fulfilling the following three criteria were included in the study: (a) presenting with solitary thyroid nodule (b) euthyroid status (c) FNAC findings suggestive of follicular etiology A total of 28 such patients presenting to the surgical out patient’s department were enrolled in the study. Patients were excluded if they were pregnant, had an electrically powered implanted device (e.g., pacemaker), or had previously diagnosed cancer of the head or neck. The patients were enrolled after prior informed consent and ethical clearance. A detailed history and clinical examination of all the patients was performed. All the patients underwent indirect laryngoscopy, anteroposterior and lateral view of soft neck tissue X-ray along with routine hematological investigations. MR signal intensity time curve analysis was carried out in all the cases and its findings were compared with the final diagnosis based on histopathological examination of surgical specimen. MRI was performed on 1.5 T super conductive systems. Examination of neck and upper mediastinum was done using a neck coil. After localizing the lesion, the voxel was placed on the lesion and position checked in all three planes. Volume of the voxel used was between 10 and 20 mm depending on the size of the lesion. T1 and T2 weighted images were obtained in axial, coronal and sagittal planes using TSE, STIR and TRUE FISP sequences (Fig. 2). The following parameters were used:
Fig. 2. TRUE FISP coronal image showing a large well defined homogeneously hyperintense lesion in the left lobe of thyroid gland.
3. FOV – 320 mm Four sets of images were obtained over a period of 12 min. The acquired images were evaluated to generate time signal intensity curves. Signal intensity time curves were analyzed for presence of enhancement, rate of enhancement and type of curve. All the patients were subjected to hemithyroidectomy. Specimens were sent for frozen section and complete thyroidectomy was performed whenever frozen section result was positive for malignancy. The data was carefully recorded and subjected to appropriate statistical analysis. Chi square test and Fisher’s exact t test were used for analysis. p < 0.05 was considered significant.
3. Observations and results 1. TSE – TR 2500, TE 13.00 ms, slice thickness 5 mm 2. STIR – TR 3600, TE 67 ms, slice thickness 4 mm 3. TRUE FISP – TR 4.4, TE 2.2, slice thickness 4 mm Dynamic post contrast scanning of the neck was done after bolus intravenous injection of 0.1 mmol of gadopentetate dimeglumine per kilogram of body weight and a 10mL saline solution flush. The injection and flushing time were set to take 5–7 s. Over the whole dynamic series, the system’s receiver adjustment remained unchanged. After the dynamic series, image subtraction was performed to suppress the signal from fat, and enhancing lesions were identified on the subtracted images. To verify the presence of a contrast-enhancing lesion and to exclude subtraction artifacts, we also reidentified the lesions on the nonsubtracted images. The following parameters were used: 1. 3D flash sequences with TR 28 ms 2. TE – 4.76 ms and slice thickness 3 mm
A total of 28 cases with solitary thyroid nodules were included in the study. Most cases presented in the age group of 20–40 years (range 18–55 years). Age distribution was comparable in both benign and malignant groups [p = 0.129 (chi square test)]. Most of the cases were females irrespective of whether the lesion was benign or malignant [p = 0.264(chi square test)] (Female: male ratio was 22: 6). There were 20 benign cases (follicular adenomas) and 8 follicular carcinoma cases (5 minimal invasive and 3 widely invasive). Fig. 3a shows the signal intensity time curve patterns for the follicular adenomas. They showed gradual rate of enhancement in 85% (17/20) of cases and steady rising curve in 50% of cases. Follicular thyroid carcinoma demonstrated rapid enhancement in 87.5%(7/8) with washout pattern in 87.5%(7/8) of cases (Fig. 3b). However, one case of follicular carcinoma showed gradual enhancement with a plateau (12.5%). Table 1 provides an integrated
N. Gupta et al. / Auris Nasus Larynx 38 (2011) 718–723 A
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B
136.4
58.3
126.9
55.0
117.4
51.6 0
2
6
4
8
10
0
2
(Minutes)
4
6 (Minutes)
8
10
Fig. 3. (A) (Left): steadily rising enhancement pattern on dynamic MRI- suggestive of benign etiology (X-axis depicts time in mins). (B) (Right): rapid uptake of contrast and washout pattern- indicator of malignancy.
Table 1 Signal intensity time curve features in follicular thyroid nodules. Signal intensity Enhancement Rate Type of curve
Present Absent Rapid Gradual Steady rise Plateau Washout
assessment of the different signal intensity time curve patterns in benign and malignant lesions. Malignant cases demonstrated rapid rate of enhancement in 87.5% (7/8) as compared to 15% (3/20) of benign cases [p = 0.019](Fig. 4a). Washout pattern was seen in 7/8 (87.5%) of malignant cases as compared to 4/20 (20%) of benign cases [p = 0.0034]. Benign cases demonstrated gradual rate of enhancement in 17/20 (85%) cases as compared to only 1/8 (12.5%) in malignant cases [p = 0.0098] (Fig. 4b). By using these data, the diagnostic indices—sensitivity, specificity, negative and positive predictive values—of the shape of the time–signal intensity curve and of the rate were determined. The diagnostic indices for signal intensity time course were sensitivity, 87.5%; specificity, 80%; positive predictive value, 63.6%; and negative predictive value, 94.5%. The diagnostic indices for the enhancement rate were sensitivity, 87.5%; specificity, 85%; positive predictive value, 70%; and negative predictive value, 94%.
Benign (adenoma) N = 20
Malignant (carcinoma) N = 8
20 0 3 17 10 6 4
8 0 7 1 0 1 7
(100%) (0%) (15%) (85%) (50%) (30%) (20%)
(100%) (0%) (87.5%) (12.5%) (0%) (12.5%) (87.5%)
4. Discussion Solitary thyroid nodules (STNs) are very common clinical entities. The incidence of malignancy in STNs is 5–10% [2]. Thus the majority of the lesions are benign; therefore management of STNs has been controversial. While there are supporters of aggressive approach advocating surgical extirpation of all the STNs, others are equally strong supporters of a more conservative approach. Fine needle aspiration cytology is the most commonly practiced technique for the diagnosis of solitary thyroid nodules with an accuracy of 90%. However, as many as 30% of thyroid nodules end up with indeterminate cytological findings as the result of the inability of FNAC in differentiating follicular adenoma from follicular carcinoma [14]. Such nodules should not be considered benign as the chances of malignancy are as high as 20–30% [15]. As already mentioned, thyroid ultrasonography is of limited use
Fig. 4. (A) (Left): difference in enhancement patterns of benign and malignant thyroid nodules. (B) (Right): distribution of time curves for benign and malignant thyroid nodules on dynamic MRI.
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as it cannot differentiate benign from malignant nodules [3]. Thyroid scintigraphy has not proven to be beneficial in facilitating decision in indeterminate thyroid nodules and is questionable when TSH levels are low [16]. An intense hunt is underway for an efficient diagnostic modality for thyroid disorders which can accurately segregate malignant from benign nodules and hence synchronize diagnostics and management of thyroid nodules. Evolving technological innovations are being scrutinized to provide the clinicians with an easy, non invasive, cost effective and accurate diagnostic tool. Stojadinovic et al. evaluated the role of electrical impedance scanning of thyroid nodules as an adjunctive diagnostic modality. They concluded from their study that the sensitivity and specificity of electrical impedance scanning is lower than that of FNAC [17]. Magnetic resonance imaging has proved to be superior to computed tomography due to its better resolution and its efficacy in the preoperative assessment of the extent of malignant invasion. However this technique has not yet proven to be of sufficient discriminatory value [18]. Timeresolved MR angiography and high-spatial-resolution MR angiography have also been assessed but none of the findings obtained during these investigations are pathognomonic of malignancy [19]. Diffusion-weighted MR imaging (DWI) is another technique that was evaluated by Schueller– Weidekamma et al. They calculated the apparent diffusion coefficient (ADC) and used it for differentiation. They found that an ADC threshold value of 2.25 10 3 mm2/s can differentiate adenoma from carcinoma with an accuracy of 88%. However the different types of malignancies could not be differentiated on the basis of their ADC values. Another shortcoming of this technique is that microcarcinomas <8 mm cannot be detected by the DWI technique [20]. Positron Emission Tomography (PET) cannot be used in solitude for thyroid disorders as confirmation by FNAC is required to validate the results. The diagnostic algorithm post PET scan is complex. Incidentomas and areas of localized uptake have a high probability of malignancy whereas diffuse uptake calls for further ultrasonographical evaluation [22,23]. Our study is an attempt to evaluate yet another biophysical phenomenon for diagnostic purposes. This study was undertaken to analyze signal intensity time curve in follicular thyroid nodules and to correlate it with histopathology results so as to differentiate benign from malignant nodules. There have been very limited studies evaluating the role of signal intensity time curve in thyroid disorders. We have extended the principle of signal intensity time curve used for assessing breast pathology in thyroid disorders [13]. The dynamic images can be evaluated by plotting the change in signal intensity of the lesion against time. The role of Dynamic contrast enhanced MRI as a diagnostic modality has been studied with breast, salivary gland, and brain tumors. It has been shown that it can detect
malignant neovascularity and cell proliferating activity in different types of carcinomas. Significant correlation between histopathologic grade, axillary lymph node status and enhancement parameters were observed in patients with breast carcinoma [9,10,13]. Gadolinium-enhanced dynamic MRI can also differentiate benign from malignant salivary gland tumors, with high sensitivity and specificity [24]. Signal intensity time curves in evaluation of breast lesions are classified according to their shapes as type I steady enhancement, type II plateau and type III washout pattern. Kaiser and Zeitler demonstrated that rate of enhancement could be used to differentiate benign from malignant breast lesions [9]. Kusunoki et al. evaluated the role of Gd- DTPA – enhanced MRI in patients with thyroid tumors. They concluded that delayed washout pattern of contrast enhancement is associated with thyroid carcinoma, high cell proliferative activity, and increased vascularity [12]. In the present study, rapid rate of enhancement was seen in 87.5% of malignant cases and washout pattern was seen in 87.5% of malignant neoplasms ( p = 0.019). Only 20% of the benign lesions showed washout pattern ( p = 0.0034). Benign cases demonstrated gradual rate of enhancement in 85% cases as compared to 12.5% in malignant ones ( p = 0.0098). These findings suggest that the washout pattern can be used as a differentiating feature for malignant and benign follicular nodules. Tezelman et al. evaluated the utility of dynamic contrast medium-enhanced magnetic resonance imaging (DCE-MRI) technique in thyroid disorders [21]. They demonstrated the higher sensitivity and diagnostic accuracy of DCE-MRI to detect thyroid carcinoma as compared to fine-needle aspiration biopsy and frozen section analysis (100% vs 50% and 85.7%; and 90% vs 70.6% and 87.5%, respectively). However, that study included only one follicular carcinoma and two follicular adenoma cases. One drawback of our study is the small sample size that may impinge on the statistical validity of the results. Nonetheless, this marks a new beginning in our quest for an ideal diagnostic tool for follicular thyroid nodules. Further studies are required to establish their role as a diagnostic modality in thyroid disorders.
5. Conclusions With the availability of newer diagnostic techniques, it is now possible to have a selective approach in the management of STN by identifying those patients likely to have malignancy and avoiding thyroidectomy in majority of the patients with benign disease. FNAC is gold standard diagnostic modality but has limitations in follicular lesions. We conclude that the signal intensity time curve is a promising imaging technique for the differentiation between malignant and benign follicular nodules and can add to the diagnostic algorithm.
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References [1] Kim N, Lavertu P. Evaluation of a thyroid nodule. Orthop Clin North Am 2003;36:17–33. [2] Castro MR, Gharib H. Thyroid fine-needle aspiration biopsy: progress, practice and pitfalls. Endocr Pract 2003;9:128–36. [3] King DA, Ahuja AT, King W, Metreweli C. The role of ultrasound in the diagnosis of a large, rapidly growing, thyroid mass. Postgrad Med J 1997;73:412–4. [4] Ishigaki S, Shimamoto K, Satake H, Sawaki A, Itoh S, Ikeda M, et al. Multi-slice CT of thyroid nodules: comparison with ultrasonography. Radiat Med 2004;22:346–53. [5] Lean CL, Delbridge L, Russell P, May GL, MacKinnon WB, Roman S, et al. Diagnosis of follicular thyroid lesions by proton magnetic resonance on fine needle biopsy. J Clin Endocrinol Metab 1995;80: 1306–11. [6] Johnson M, Selinsky B, Davis M, Lawrence TL, Cleveland G, Perry JR, et al. In vitro NMR evaluation of human thyroid lesions. Invest Radiol 1989;24:666–71. [7] Gupta N, Kakar A, Chowdhury V, Gulati P, Shankar L, Vindal A. Magnetic resonance spectroscopy as a diagnostic modality for carcinoma thyroid. Eur J Radiol 2007;64:414–8. [8] Heywang SH, Wolf A, Pruss E, Hilbertz T, Eiermann W, Permanetter W. MR imaging of the breast with gadolinium DTPA: use and limitations. Radiology 1989;171:95–103. [9] Kaiser WA, Zeitler E. MR imaging of the breast; fast imaging sequences with and without gadolinium DTPA. Radiology 1989; 170:681–6. [10] Stack JP, Redmomd OM, Codd MB, Dervan PA, Ennis JT. Breast disease: tissue characterization with gadolinium DTPA enhancement profiles. Radiology 1990;174:491–4. [11] Kusunoki T, Murata K, Hosoi H, Nishida S, Tomura T, Inoue M. Malignancies of human thyroid tumors and dynamic magnetic resonance imaging. Auris Nasus Larynx 1998;25:419–24. [12] Kusunoki T, Murata K, Nishida S, Tomura T, Inoue M. Histopathological findings of human thyroid tumors and dynamic MRI. Auris Nasus Larynx 2002;29:357–60. [13] Kuhl CK, Mielcareck P, Leutner G, Wardelmann E, Gieseke J, Schild HH. Dynamic breast MR imaging: are signal intensity time course data
[14]
[15]
[16] [17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
723
useful for differential diagnosis of enhancing lesions? Radiology 1999;211:101–10. Tee YY, Lowe AJ, Brand CA, Judson RT. Fine-needle aspiration may miss a third of all malignancy in palpable thyroid nodules: a comprehensive literature review. Ann Surg 2007;246:714–20. Brooks AD, Shaha AR, DuMornay W, Huwos AG, Zakowski M, Brennan MF, et al. Role of fine-needle aspiration biopsy and frozen section analysis in the surgical management of thyroid tumors. Ann Surg Oncol 2001;8:92–100. Meier DA, Kaplan MM. Radioiodine uptake and thyroid scintiscanning. Endocrinol Metab Clin North Am 2001;30:291–313. Stojadinovic FA, Fields SI, Shriver CD, Lenington S, Ginor R, Peoples GE, et al. Electrical impedance scanning of thyroid nodules before thyroid surgery: a prospective study. Ann Surg Oncol 2005; 12:152–60. Mihailovic J, Stefanovic LJ, Prvulovic M. Magnetic resonance imaging in diagnostic algorithm of solitary cold thyroid nodules. J BUON 2006;11:341–6. Lohan DG, Tomasian A, Saleh R, Krishnam M, Finn JP. Hypervascular thyroid nodules on time-resolved MR angiography at 3T: radiologic– pathologic correlation. AJR 2008;190:W255–60. Schueller-Weidekamm C, Kaserer K, Schueller G, Scheuba C, Ringl H, Weber M, et al. Can quantitative diffusion-weighted MR imaging differentiate benign and malignant cold thyroid nodules? Initial results in 25 patients. Am J Neuroradiol 2009;30:417–22. Tezelman S, Giles Y, Tunca F, Gok K, Poyanli A, Salmasloglu A, et al. Diagnostic value of dynamic contrast medium-enhanced magnetic resonance imaging in preoperative detection of thyroid carcinoma. Arch Surg 2007;142:1036–41. Are C, Hsu JF, Schoder H, Shah JP, Larson SM, Shaha AR. FDG-PET detected thyroid incidentalomas: need for further investigation? Ann Surg Oncol 2007;14:239–47. Choi JY, Lee KS, Kim HJ, Shim YM, Kwon OJ, Park K, et al. Focal thyroid lesions incidentally identified by integrated 18F-FDG PET/ CT: clinical significance and improved characterization. J Nucl Mater 2006;47:609–15. Hisatomi M, Asaumi J, Yanagi Y, Unetsubo T, Maki Y, Murakami J, et al. Diagnostic value of dynamic contrast-enhanced MRI in the salivary gland tumors. Oral Oncol 2007;43:940–7.
Role of dynamic MRI in differentiating benign from malignant follicular thyroid nodule Nikhil Gupta a,*, Choden Norbu b, Binita Goswami d, Veena Chowdhury c, L. RaviShankar e, Praveen Gulati f, Arun Kakar b a Department of Surgery, Lady Hardinge Medical College, Delhi, India Department of Surgery, Maulana Azad Medical College and Associated Lok Nayak and GB Pant Hospitals, New Delhi, India c Department of Radiodiagnosis, Maulana Azad Medical College and Associated Lok Nayak and GB Pant Hospitals, New Delhi, India d Department of Biochemistry, Maulana Azad Medical College and Associated Lok nayak and GB Pant Hospitals, New Delhi, India e Thyroid Division, Institute of Nuclear Medicine and allied Sciences, Timarpur, Delhi, India f MR Imaging Centre, Green park, Delhi, India b
Received 19 September 2010; accepted 7 February 2011 Available online 13 May 2011
Abstract Objectives: Thyroid nodular swellings are very common, consisting of both benign and malignant ones. Fine needle aspiration cytology is an excellent diagnostic modality for papillary cancers, medullary cancers, colloid goiter and lymphoma but fails in differentiating follicular adenomas from carcinomas. The purpose of this study was to evaluate role of Dynamic MRI with signal intensity time curve evaluation in differentiating benign from malignant follicular nodules. Materials and methods: This study was carried out in Department of Surgery in collaboration with department of Radiodiagnosis, Maulana Azad Medical College, Delhi. 28 patients with solitary thyroid nodule (STN) having follicular etiologies were included in the study. Dynamic MRI with signal intensity time curve analysis was carried out in all the cases and findings were compared with the final diagnosis based on histopathological examination of surgical specimen. Results: In the present study, rapid enhancement was seen in 87.5% of malignant cases and washout pattern was seen in 87.5% of malignant STN ( p = 0.019). Only 20% of the benign lesions showed washout pattern ( p = 0.0034). Benign cases demonstrated gradual enhancement in 85% cases as compared to 12.5% in malignant STN ( p = 0.0098). Conclusion: This study suggests that signal intensity time curve may help in differentiating benign from malignant follicular thyroid nodules. # 2011 Elsevier Ireland Ltd. All rights reserved. Keywords: Follicular adenoma; Signal intensity time curve; Dynamic MRI
Abbreviations: STN, solitary thyroid nodule; CT, computed tomography; MRI, magnetic resonance imaging; PET, positron emission tomography; FNAC, fine needle aspiration cytology; FS, frozen section; TSE, turbo spin echo; STIR, short T1 inversion recovery; TRUE FISP, coherent gradient echo (Siemens); TE, echo time; TR, repetition time; FOV, field of view; DWI, diffusion weighted MR imaging; ADC, apparent diffusion coefficient; DCE-MRI, dynamic contrast medium-enhanced magnetic resonance imaging. * Corresponding author. Tel.: +91 011 9810592084. E-mail addresses: [email protected] (N. Gupta), [email protected] (C. Norbu), [email protected] (B. Goswami), [email protected] (V. Chowdhury), [email protected] (L. RaviShankar), [email protected] (P. Gulati), [email protected] (A. Kakar).
1. Introduction Thyroid nodules are very common clinical entities. Clinical palpation suggests a prevalence of thyroid nodules in 1–7% of the general population [1]. The overwhelming majority of thyroid nodules are benign with the incidence of malignancy being only 5% [2]. It may not always be possible to differentiate precisely a benign pathology from the malignant pathology with the available diagnostic modalities. Fine needle aspiration cytology though accurate in diagnosing thyroid lesions, has limitations in differentiating follicular malignancy from follicular adenomas [2]. Ultra-
0385-8146/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.anl.2011.02.002
N. Gupta et al. / Auris Nasus Larynx 38 (2011) 718–723
sonography has a low sensitivity as well as specificity in definitive differential diagnosis of thyroid nodules [3]. Computed tomography (CT) of neck is often limited by streak artifacts caused by swallowing or respiratory motion and X-ray beam hardening [4]. MRI can demonstrate gross morphological features of nodules; however, it cannot accurately differentiate benign from malignant lesions [5]. This dilemma necessitated the discovery of newer preferably non invasive diagnostic modalities for the diagnosis of thyroid pathologies. The introduction of nuclear magnetic resonance spectroscopy as a diagnostic tool has made it possible to understand the patterns of metabolite changes in pathological processes [6]. Thyroid tissue characterization achieved by the adoption of newer techniques such as proton spectroscopy has indeed proved to be beneficial in the differential diagnosis of thyroid disorders as shown in our previous study [7]. There are studies that have evaluated the utility of Dynamic MRI with time signal intensity curve specifications as an important criterion in differentiating benign and malignant lesions in breast MR imaging [8–10]. However, there are very few studies evaluating the role of signal intensity time curve in thyroid disorders [11,12]. Two different criteria are used to describe lesion enhancement kinetics. First, behavior of signal intensity in the early phase after the administration of contrast material is evaluated by means of the steepness of the post contrast signal intensity curve; and second, the behavior of signal intensity in the intermediate and late post contrast periods. Visual or quantitative evaluation is dependent on the shape of the time–signal intensity curve: whether the signal intensity continues to increase after the initial upstroke, whether it is cut off and reaches a plateau, or whether it washes out. The relative enhancement (percentage of signal intensity increase) is calculated according to the enhancement formula ((Sic SI)/SI) 100, where SI and SIc are the precontrast and the postcontrast signal intensities, respectively. By plotting the lesion signal intensity over time, the time–signal intensity curve was obtained to depict the lesions’ enhancement behavior. The signal intensity time curves are classified according to their shapes as [13]: Type I steady enhancement Type II plateau of signal intensity Type III washout of signal intensity The three curve types differ in their signal intensity time courses in the intermediate and late postcontrast periods (Fig. 1). Type I is straight or curved. In type Ia, the straight type, the signal intensity continues to increase over the entire dynamic period; in type Ib, the curved type, the time–signal intensity curve is flattened in the late postcontrast period because of saturation effects. Type II is a plateau in which there is an initial upstroke, after which enhancement is abruptly cut off, and the signal intensity plateaus in the
719
Fig. 1. Signal intensity time curve. (A) Early postcontrast phase, (B) intermediate and late postcontrast phase. Type I corresponds to a straight (Ia) or curved (Ib) line; enhancement continues over the entire dynamic study. Type II is a plateau curve with after the initial upstroke. Type III is a washout pattern.
intermediate and late postcontrast periods. Type III is a washout in which there is an initial upstroke, after which enhancement is abruptly cut off, and the signal intensity decreases (washes out) in the intermediate postcontrast period (i.e., 2–3 min after injection of contrast material). The lesion enhancement rate in the early postcontrast period (also known as ‘‘enhancement velocity’’ or ‘‘slope of enhancement’’) serves as a differential diagnostic criterion, with malignant lesions exhibiting stronger and faster enhancement than benign lesions. The blood circulation at the capillary level is determined by the metabolic activity of the tissue. In pathological processes (such as tumour genesis), the microcirculation becomes altered. There can be an increase in microvascular density resulting from the growth of new capillary networks (angiogenesis) as well as vasodilatation of existing vessels. The biologic basis of the different time curves for benign and malignant lesions may be due to the presence of this increased vessel density and arteriovenous anastomoses with rapid outflow and thus fading of the contrast material in malignant lesions. On the basis of studies published in literature, the lesions are classified according to the different time signal intensity curves. A type I curve is considered to be indicative of a benign lesion, type II curve is suggestive of malignancy and type III curve is indicator of a malignant lesion. Our study attempts to evaluate the plausible role of signal intensity time curves in differentiating benign from malignant follicular neoplasms.
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2. Materials and methods The present prospective study was conducted in the department of surgery in collaboration with the department of radio diagnosis, Maulana Azad medical college, New Delhi from February 2007 to July 2009. This study was approved by the ethical committee of the institution. Patients fulfilling the following three criteria were included in the study: (a) presenting with solitary thyroid nodule (b) euthyroid status (c) FNAC findings suggestive of follicular etiology A total of 28 such patients presenting to the surgical out patient’s department were enrolled in the study. Patients were excluded if they were pregnant, had an electrically powered implanted device (e.g., pacemaker), or had previously diagnosed cancer of the head or neck. The patients were enrolled after prior informed consent and ethical clearance. A detailed history and clinical examination of all the patients was performed. All the patients underwent indirect laryngoscopy, anteroposterior and lateral view of soft neck tissue X-ray along with routine hematological investigations. MR signal intensity time curve analysis was carried out in all the cases and its findings were compared with the final diagnosis based on histopathological examination of surgical specimen. MRI was performed on 1.5 T super conductive systems. Examination of neck and upper mediastinum was done using a neck coil. After localizing the lesion, the voxel was placed on the lesion and position checked in all three planes. Volume of the voxel used was between 10 and 20 mm depending on the size of the lesion. T1 and T2 weighted images were obtained in axial, coronal and sagittal planes using TSE, STIR and TRUE FISP sequences (Fig. 2). The following parameters were used:
Fig. 2. TRUE FISP coronal image showing a large well defined homogeneously hyperintense lesion in the left lobe of thyroid gland.
3. FOV – 320 mm Four sets of images were obtained over a period of 12 min. The acquired images were evaluated to generate time signal intensity curves. Signal intensity time curves were analyzed for presence of enhancement, rate of enhancement and type of curve. All the patients were subjected to hemithyroidectomy. Specimens were sent for frozen section and complete thyroidectomy was performed whenever frozen section result was positive for malignancy. The data was carefully recorded and subjected to appropriate statistical analysis. Chi square test and Fisher’s exact t test were used for analysis. p < 0.05 was considered significant.
3. Observations and results 1. TSE – TR 2500, TE 13.00 ms, slice thickness 5 mm 2. STIR – TR 3600, TE 67 ms, slice thickness 4 mm 3. TRUE FISP – TR 4.4, TE 2.2, slice thickness 4 mm Dynamic post contrast scanning of the neck was done after bolus intravenous injection of 0.1 mmol of gadopentetate dimeglumine per kilogram of body weight and a 10mL saline solution flush. The injection and flushing time were set to take 5–7 s. Over the whole dynamic series, the system’s receiver adjustment remained unchanged. After the dynamic series, image subtraction was performed to suppress the signal from fat, and enhancing lesions were identified on the subtracted images. To verify the presence of a contrast-enhancing lesion and to exclude subtraction artifacts, we also reidentified the lesions on the nonsubtracted images. The following parameters were used: 1. 3D flash sequences with TR 28 ms 2. TE – 4.76 ms and slice thickness 3 mm
A total of 28 cases with solitary thyroid nodules were included in the study. Most cases presented in the age group of 20–40 years (range 18–55 years). Age distribution was comparable in both benign and malignant groups [p = 0.129 (chi square test)]. Most of the cases were females irrespective of whether the lesion was benign or malignant [p = 0.264(chi square test)] (Female: male ratio was 22: 6). There were 20 benign cases (follicular adenomas) and 8 follicular carcinoma cases (5 minimal invasive and 3 widely invasive). Fig. 3a shows the signal intensity time curve patterns for the follicular adenomas. They showed gradual rate of enhancement in 85% (17/20) of cases and steady rising curve in 50% of cases. Follicular thyroid carcinoma demonstrated rapid enhancement in 87.5%(7/8) with washout pattern in 87.5%(7/8) of cases (Fig. 3b). However, one case of follicular carcinoma showed gradual enhancement with a plateau (12.5%). Table 1 provides an integrated
N. Gupta et al. / Auris Nasus Larynx 38 (2011) 718–723 A
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B
136.4
58.3
126.9
55.0
117.4
51.6 0
2
6
4
8
10
0
2
(Minutes)
4
6 (Minutes)
8
10
Fig. 3. (A) (Left): steadily rising enhancement pattern on dynamic MRI- suggestive of benign etiology (X-axis depicts time in mins). (B) (Right): rapid uptake of contrast and washout pattern- indicator of malignancy.
Table 1 Signal intensity time curve features in follicular thyroid nodules. Signal intensity Enhancement Rate Type of curve
Present Absent Rapid Gradual Steady rise Plateau Washout
assessment of the different signal intensity time curve patterns in benign and malignant lesions. Malignant cases demonstrated rapid rate of enhancement in 87.5% (7/8) as compared to 15% (3/20) of benign cases [p = 0.019](Fig. 4a). Washout pattern was seen in 7/8 (87.5%) of malignant cases as compared to 4/20 (20%) of benign cases [p = 0.0034]. Benign cases demonstrated gradual rate of enhancement in 17/20 (85%) cases as compared to only 1/8 (12.5%) in malignant cases [p = 0.0098] (Fig. 4b). By using these data, the diagnostic indices—sensitivity, specificity, negative and positive predictive values—of the shape of the time–signal intensity curve and of the rate were determined. The diagnostic indices for signal intensity time course were sensitivity, 87.5%; specificity, 80%; positive predictive value, 63.6%; and negative predictive value, 94.5%. The diagnostic indices for the enhancement rate were sensitivity, 87.5%; specificity, 85%; positive predictive value, 70%; and negative predictive value, 94%.
Benign (adenoma) N = 20
Malignant (carcinoma) N = 8
20 0 3 17 10 6 4
8 0 7 1 0 1 7
(100%) (0%) (15%) (85%) (50%) (30%) (20%)
(100%) (0%) (87.5%) (12.5%) (0%) (12.5%) (87.5%)
4. Discussion Solitary thyroid nodules (STNs) are very common clinical entities. The incidence of malignancy in STNs is 5–10% [2]. Thus the majority of the lesions are benign; therefore management of STNs has been controversial. While there are supporters of aggressive approach advocating surgical extirpation of all the STNs, others are equally strong supporters of a more conservative approach. Fine needle aspiration cytology is the most commonly practiced technique for the diagnosis of solitary thyroid nodules with an accuracy of 90%. However, as many as 30% of thyroid nodules end up with indeterminate cytological findings as the result of the inability of FNAC in differentiating follicular adenoma from follicular carcinoma [14]. Such nodules should not be considered benign as the chances of malignancy are as high as 20–30% [15]. As already mentioned, thyroid ultrasonography is of limited use
Fig. 4. (A) (Left): difference in enhancement patterns of benign and malignant thyroid nodules. (B) (Right): distribution of time curves for benign and malignant thyroid nodules on dynamic MRI.
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as it cannot differentiate benign from malignant nodules [3]. Thyroid scintigraphy has not proven to be beneficial in facilitating decision in indeterminate thyroid nodules and is questionable when TSH levels are low [16]. An intense hunt is underway for an efficient diagnostic modality for thyroid disorders which can accurately segregate malignant from benign nodules and hence synchronize diagnostics and management of thyroid nodules. Evolving technological innovations are being scrutinized to provide the clinicians with an easy, non invasive, cost effective and accurate diagnostic tool. Stojadinovic et al. evaluated the role of electrical impedance scanning of thyroid nodules as an adjunctive diagnostic modality. They concluded from their study that the sensitivity and specificity of electrical impedance scanning is lower than that of FNAC [17]. Magnetic resonance imaging has proved to be superior to computed tomography due to its better resolution and its efficacy in the preoperative assessment of the extent of malignant invasion. However this technique has not yet proven to be of sufficient discriminatory value [18]. Timeresolved MR angiography and high-spatial-resolution MR angiography have also been assessed but none of the findings obtained during these investigations are pathognomonic of malignancy [19]. Diffusion-weighted MR imaging (DWI) is another technique that was evaluated by Schueller– Weidekamma et al. They calculated the apparent diffusion coefficient (ADC) and used it for differentiation. They found that an ADC threshold value of 2.25 10 3 mm2/s can differentiate adenoma from carcinoma with an accuracy of 88%. However the different types of malignancies could not be differentiated on the basis of their ADC values. Another shortcoming of this technique is that microcarcinomas <8 mm cannot be detected by the DWI technique [20]. Positron Emission Tomography (PET) cannot be used in solitude for thyroid disorders as confirmation by FNAC is required to validate the results. The diagnostic algorithm post PET scan is complex. Incidentomas and areas of localized uptake have a high probability of malignancy whereas diffuse uptake calls for further ultrasonographical evaluation [22,23]. Our study is an attempt to evaluate yet another biophysical phenomenon for diagnostic purposes. This study was undertaken to analyze signal intensity time curve in follicular thyroid nodules and to correlate it with histopathology results so as to differentiate benign from malignant nodules. There have been very limited studies evaluating the role of signal intensity time curve in thyroid disorders. We have extended the principle of signal intensity time curve used for assessing breast pathology in thyroid disorders [13]. The dynamic images can be evaluated by plotting the change in signal intensity of the lesion against time. The role of Dynamic contrast enhanced MRI as a diagnostic modality has been studied with breast, salivary gland, and brain tumors. It has been shown that it can detect
malignant neovascularity and cell proliferating activity in different types of carcinomas. Significant correlation between histopathologic grade, axillary lymph node status and enhancement parameters were observed in patients with breast carcinoma [9,10,13]. Gadolinium-enhanced dynamic MRI can also differentiate benign from malignant salivary gland tumors, with high sensitivity and specificity [24]. Signal intensity time curves in evaluation of breast lesions are classified according to their shapes as type I steady enhancement, type II plateau and type III washout pattern. Kaiser and Zeitler demonstrated that rate of enhancement could be used to differentiate benign from malignant breast lesions [9]. Kusunoki et al. evaluated the role of Gd- DTPA – enhanced MRI in patients with thyroid tumors. They concluded that delayed washout pattern of contrast enhancement is associated with thyroid carcinoma, high cell proliferative activity, and increased vascularity [12]. In the present study, rapid rate of enhancement was seen in 87.5% of malignant cases and washout pattern was seen in 87.5% of malignant neoplasms ( p = 0.019). Only 20% of the benign lesions showed washout pattern ( p = 0.0034). Benign cases demonstrated gradual rate of enhancement in 85% cases as compared to 12.5% in malignant ones ( p = 0.0098). These findings suggest that the washout pattern can be used as a differentiating feature for malignant and benign follicular nodules. Tezelman et al. evaluated the utility of dynamic contrast medium-enhanced magnetic resonance imaging (DCE-MRI) technique in thyroid disorders [21]. They demonstrated the higher sensitivity and diagnostic accuracy of DCE-MRI to detect thyroid carcinoma as compared to fine-needle aspiration biopsy and frozen section analysis (100% vs 50% and 85.7%; and 90% vs 70.6% and 87.5%, respectively). However, that study included only one follicular carcinoma and two follicular adenoma cases. One drawback of our study is the small sample size that may impinge on the statistical validity of the results. Nonetheless, this marks a new beginning in our quest for an ideal diagnostic tool for follicular thyroid nodules. Further studies are required to establish their role as a diagnostic modality in thyroid disorders.
5. Conclusions With the availability of newer diagnostic techniques, it is now possible to have a selective approach in the management of STN by identifying those patients likely to have malignancy and avoiding thyroidectomy in majority of the patients with benign disease. FNAC is gold standard diagnostic modality but has limitations in follicular lesions. We conclude that the signal intensity time curve is a promising imaging technique for the differentiation between malignant and benign follicular nodules and can add to the diagnostic algorithm.
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References [1] Kim N, Lavertu P. Evaluation of a thyroid nodule. Orthop Clin North Am 2003;36:17–33. [2] Castro MR, Gharib H. Thyroid fine-needle aspiration biopsy: progress, practice and pitfalls. Endocr Pract 2003;9:128–36. [3] King DA, Ahuja AT, King W, Metreweli C. The role of ultrasound in the diagnosis of a large, rapidly growing, thyroid mass. Postgrad Med J 1997;73:412–4. [4] Ishigaki S, Shimamoto K, Satake H, Sawaki A, Itoh S, Ikeda M, et al. Multi-slice CT of thyroid nodules: comparison with ultrasonography. Radiat Med 2004;22:346–53. [5] Lean CL, Delbridge L, Russell P, May GL, MacKinnon WB, Roman S, et al. Diagnosis of follicular thyroid lesions by proton magnetic resonance on fine needle biopsy. J Clin Endocrinol Metab 1995;80: 1306–11. [6] Johnson M, Selinsky B, Davis M, Lawrence TL, Cleveland G, Perry JR, et al. In vitro NMR evaluation of human thyroid lesions. Invest Radiol 1989;24:666–71. [7] Gupta N, Kakar A, Chowdhury V, Gulati P, Shankar L, Vindal A. Magnetic resonance spectroscopy as a diagnostic modality for carcinoma thyroid. Eur J Radiol 2007;64:414–8. [8] Heywang SH, Wolf A, Pruss E, Hilbertz T, Eiermann W, Permanetter W. MR imaging of the breast with gadolinium DTPA: use and limitations. Radiology 1989;171:95–103. [9] Kaiser WA, Zeitler E. MR imaging of the breast; fast imaging sequences with and without gadolinium DTPA. Radiology 1989; 170:681–6. [10] Stack JP, Redmomd OM, Codd MB, Dervan PA, Ennis JT. Breast disease: tissue characterization with gadolinium DTPA enhancement profiles. Radiology 1990;174:491–4. [11] Kusunoki T, Murata K, Hosoi H, Nishida S, Tomura T, Inoue M. Malignancies of human thyroid tumors and dynamic magnetic resonance imaging. Auris Nasus Larynx 1998;25:419–24. [12] Kusunoki T, Murata K, Nishida S, Tomura T, Inoue M. Histopathological findings of human thyroid tumors and dynamic MRI. Auris Nasus Larynx 2002;29:357–60. [13] Kuhl CK, Mielcareck P, Leutner G, Wardelmann E, Gieseke J, Schild HH. Dynamic breast MR imaging: are signal intensity time course data
[14]
[15]
[16] [17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
723
useful for differential diagnosis of enhancing lesions? Radiology 1999;211:101–10. Tee YY, Lowe AJ, Brand CA, Judson RT. Fine-needle aspiration may miss a third of all malignancy in palpable thyroid nodules: a comprehensive literature review. Ann Surg 2007;246:714–20. Brooks AD, Shaha AR, DuMornay W, Huwos AG, Zakowski M, Brennan MF, et al. Role of fine-needle aspiration biopsy and frozen section analysis in the surgical management of thyroid tumors. Ann Surg Oncol 2001;8:92–100. Meier DA, Kaplan MM. Radioiodine uptake and thyroid scintiscanning. Endocrinol Metab Clin North Am 2001;30:291–313. Stojadinovic FA, Fields SI, Shriver CD, Lenington S, Ginor R, Peoples GE, et al. Electrical impedance scanning of thyroid nodules before thyroid surgery: a prospective study. Ann Surg Oncol 2005; 12:152–60. Mihailovic J, Stefanovic LJ, Prvulovic M. Magnetic resonance imaging in diagnostic algorithm of solitary cold thyroid nodules. J BUON 2006;11:341–6. Lohan DG, Tomasian A, Saleh R, Krishnam M, Finn JP. Hypervascular thyroid nodules on time-resolved MR angiography at 3T: radiologic– pathologic correlation. AJR 2008;190:W255–60. Schueller-Weidekamm C, Kaserer K, Schueller G, Scheuba C, Ringl H, Weber M, et al. Can quantitative diffusion-weighted MR imaging differentiate benign and malignant cold thyroid nodules? Initial results in 25 patients. Am J Neuroradiol 2009;30:417–22. Tezelman S, Giles Y, Tunca F, Gok K, Poyanli A, Salmasloglu A, et al. Diagnostic value of dynamic contrast medium-enhanced magnetic resonance imaging in preoperative detection of thyroid carcinoma. Arch Surg 2007;142:1036–41. Are C, Hsu JF, Schoder H, Shah JP, Larson SM, Shaha AR. FDG-PET detected thyroid incidentalomas: need for further investigation? Ann Surg Oncol 2007;14:239–47. Choi JY, Lee KS, Kim HJ, Shim YM, Kwon OJ, Park K, et al. Focal thyroid lesions incidentally identified by integrated 18F-FDG PET/ CT: clinical significance and improved characterization. J Nucl Mater 2006;47:609–15. Hisatomi M, Asaumi J, Yanagi Y, Unetsubo T, Maki Y, Murakami J, et al. Diagnostic value of dynamic contrast-enhanced MRI in the salivary gland tumors. Oral Oncol 2007;43:940–7.