[Show abstract][Hide abstract] ABSTRACT: Ultrasound of the neck detects a large number of non-palpable thyroid nodules in the population, but it offers poor diagnostic accuracy (the presence of microcalcifications is the only statistically significant criterion indicative of malignancy). The aim of this study is to evaluate elastography, a technique which allows differentiation between pathological and normal tissue by determining its hardness and which could also prove useful in the characterisation of thyroid nodules.
In this prospective study, 51 thyroid nodules in 40 consecutive patients were examined (25 women, 15 men, mean age +/- SD, 54 +/- 13.4). Elastosonography was performed by real-time, free-hand technique, using Logos HiVision equipment with a 10 MHz transducer and lesions were classified and scored in 4 classes of hardness. All patients were also examined by grey scale high frequency ultrasound and colour Doppler. Final diagnoses were obtained from cytological and/or histological evaluation.
Final diagnoses revealed 11 malignant and 40 benign nodules. Only in two cases ultrasound demonstrated signs useful for a differential diagnosis (intrinsic microcalcifications). Correct differentiation of malignant from benign nodules was obtained by elastosonography in 43 / 51 cases with 5 false positives (FP) and 3 false negatives (FN). Specificity, sensitivity and accuracy were 87.5 %, 81.8 % and 86.2 %, respectively. Predictive negative value (PNV) and predictive positive value (PPV) were 94.5 % and 64 % area under the curve (AUC) 0.86.
Elastosonography provides an interesting contribution to the differentiation of malignant and benign thyroid nodules. Particularly worthy of mention is that an entirely elastic nodule pattern was observed only in relation to benign nodules, a result which would suggest that immediate recourse to FNAB might be avoided.
Ultraschall in der Medizin 06/2008; 30(2):175-9. DOI:10.1055/s-2008-1027442 · 4.92 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to assess the performance of experimental software (Qontraxt) intended to provide automated quantification of sonographic signal intensity, which is related to the contrast enhancement of lymph node tissue, to differentiate benign from malignant lymph nodes.
In 31 patients (age range, 24-86 years; mean age +/- SD, 53.6 +/- 14.4 years) a single lymph node per patient was evaluated on sonography after the administration of sulfur hexafluoride-filled microbubbles. The stored sonographic images were analyzed and processed into chromatic maps that had numeric values related to the amount of contrast. The lymph node regions in which the increase of signal intensity values with respect to baseline were highest (maximum signal intensity value [SImax]) and lowest (minimum signal intensity value [SImin]) were identified, and the corresponding numeric data were stored. Statistical analyses were performed by means of the Student's t test; a p value of less than 0.05 was considered to be statistically significant.
Histopathologic analysis revealed metastatic lesions in 12 of the 31 lymph nodes; the remaining 19 were benign (16 reactive lymph nodes, two cases of granulomatous lymphadenitis, and one case of tubercular lymphadenitis). Values obtained from the SImax regions showed no consistent difference between benign and malignant lymph nodes; on the other hand, values from the SImin regions comparing baseline and maximal contrast-enhanced values were significantly different in the two groups (p < 0.001). Confidence for characterization of malignancy was significant using the difference between values from SImax and SImin regions, with the higher diagnostic value from 24 to 31 inclusive: sensitivity, 92% (11/12); specificity, 89% (17/19); positive predictive value, 85% (11/13); and accuracy, 90% (28/31).
The software being tested proved to be useful in differentiating benign from metastatic lymph nodes on the basis of the quantitative data it provided.
American Journal of Roentgenology 05/2007; 188(4):977-83. DOI:10.2214/AJR.06.0562 · 2.73 Impact Factor