Roberto Garberoglio

Thyroid Nodules and Related Symptoms Are Stably Controlled Two Years After Radiofrequency Thermal Ablation

BACKGROUND Percutaneous radiofrequency thermal ablation (RTA) is a promising new therapeutic approach to manage thyroid nodules (TNs). The aim of this study was to investigate the long-term effectiveness of RTA in inducing shrinkage of TNs as well as in controlling compressive symptoms and thyroid hyperfunction in a large series of elderly subjects with solid or mainly solid benign TNs. METHODS Ninety-four elderly patients with cytologically benign compressive TNs were prospectively enrolled in the study; 66 of them had nontoxic goiter and 28 had toxic or pretoxic goiter. RTA was performed by using a RITA StarBurst Talon hook-umbrella needle inserted in every single TN under ultrasonographic real-time guidance. TN volume, TN-related compressive symptoms and thyroid function were evaluated at baseline and 12 to 24 months after RTA. RESULTS All TNs significantly decreased in size after RTA. The mean decrease in TN volume 12 months after RTA was from 24.5 +/- 2.1 to 7.5 +/- 1.2 mL (p < 0.001), with a mean percent decrease of 78.6 +/- 2.0%. Two years after RTA, a 79.4 +/- 2.5% decrease of TNs size was observed. Compressive symptoms improved in all patients and completely disappeared in 83 of 94 (88%) patients. Hyperthyroidism resolved in most patients allowing methimazole therapy to be completely withdrawn in 79% of patients with pretoxic and toxic TNs (100% with pretoxic TNs and 53% with toxic TNs). The treatment was well tolerated by all patients. No patient needed hospitalization after RTA and no major complications were observed. CONCLUSIONS RTA is an effective and simple procedure for obtaining lasting shrinkage of TNs, controlling compressive symptoms, and treating thyroid hyperfunction. When performed in experienced medical centers, RTA may be a valid alternative to conventional treatments for nontoxic and pretoxic TNs. It is particularly attractive for elderly people for whom surgery and radioiodine therapy are often contraindicated or ineffective.

US-Guided Percutaneous Radiofrequency Thermal Ablation for the Treatment of Solid Benign Hyperfunctioning or Compressive Thyroid Nodules

The aim of the study was to define the effectiveness and safety of ultrasound-guided percutaneous radiofrequency (RF) thermal ablation in the treatment of compressive solid benign thyroid nodules. Thirty-one patients not eligible for surgery or radioiodine (131I) treatment underwent RF ablation for benign nodules; a total of 33 nodules were treated (2 patients had 2 nodules treated in the same session): 10 cold nodules and 23 hyperfunctioning. Fourteen patients complained of compressive symptoms. Nodule volume, thyroid function and compressive symptoms were evaluated before treatment and at 1, 3 and 6 mo. Ultrasound-guided RF ablation was performed using a Starbust RITA needle, with nine expandable prongs; total exposure time was 6 to 10 min at 95 degrees C in one area or more of the nodule. Baseline volume (measured at the time of RF ablation) was 27.7 +/- 21.5 mL (mean +/- SD), but significantly decreased during follow-up: 19.2 +/- 16.2 at 1 mo (-32.7%; p < 0.001), 15.9 +/- 14.1 mL at 3 mo (-46.4 %; p < 0.001) and 14.6 +/- 12.6 mL at 6 mo (-50.7%; p < 0.001). After treatment, all patients with cold nodules remained euthyroid: five patients with hot nodules normalized thyroid function, and the remaining sixteen showed a partial remission of hyperthyroidism. Besides a sensation of heat and mild swelling of the neck, no major complications were observed. Improvement in compressive symptoms was reported by 13 patients, with a reduction on severity scale from 6.1 +/- 1.4 to 2.2 +/- 1.9 (p < 0.0001). Radiofrequency was effective and safe in reducing volume by about 50% and compressive symptoms in large benign nodules. Hyperfunction was fully controlled in 24% of patients and partially reduced in the others.

FINE-NEEDLE ASPIRATION BIOPSY OF THE THYROID: COMPARISON BETWEEN THYROID PALPATION AND ULTRASONOGRAPHY

OBJECTIVE To describe our experience with fine-needle aspiration biopsy (FNAB) of the thyroid and compare our results with direct palpation versus ultrasound scanning (USS) in an area of endemic goiter in Italy. METHODS We considered all patients submitted to ultrasound-guided FNAB of thyroid nodules during a 10-month period at our outpatient clinic and analyzed the following: (1) clinical data (number of nodules and identification of the nodule for FNAB); (2) USS data (number of nodules and identification of the nodule for FNAB on the basis of hypoechoic pattern + blurred perinodal halo + microcalcifications or intranodal color Doppler signal indicative of blood flow); (3) cytologic specimens, categorized as suspicious, malignant, negative, or nondiagnostic; and (4) histologic final report of the cytologically positive nodules. RESULTS The study group consisted of 348 female and 72 male patients who underwent FNAB of the thyroid at our institution. Among the 140 patients with no palpable thyroid nodules, USS showed that 106 had a single nodule and 34 had multinodular goiters. Among the 182 patients with a single palpable thyroid nodule, USS revealed that 138 had a single nodule, 42 had a multinodular goiter, and 2 had lobe enlargement without detectable nodules. All 98 patients with multinodular palpable goiter had a similar pattern on USS. Of the 420 cytologic specimens, 46(11.0%) were positive for thyroid cancer, 313 (74.5%)were negative, and 61 (14.5%) were nondiagnostic. Histologic malignant growth was confirmed in 27 cytologically positive nodules. Of these histologically malignant nodules, 12 (45%) were nonpalpable, 9 (33%) were single palpable nodules, and 6 (22%) were from a nodule with a suspicious ultrasound pattern within a multinodular goiter. CONCLUSION Manually guided FNAB is not feasible in nonpalpable nodules and not accurate in a multinodular goiter. Both situations are clinical challenges, and USS should be performed for accurate FNAB under these circumstances. Because 52% of histologically malignant nodules in our study were found only with the aid of ultrasound-guided FNAB, this procedure should be used where multinodular goiter is endemic. Our overall rate of nondiagnostic specimens was comparable to that reported in the literature.

Cost-Effective and Non-Invasive Automated Benign & Malignant Thyroid Lesion Classification in 3D Contrast-Enhanced Ultrasound Using Combination of Wavelets and Textures: A Class of ThyroScan™ Algorithms

Ultrasound has great potential to aid in the differential diagnosis of malignant and benign thyroid lesions, but interpretative pitfalls exist and the accuracy is still poor. To overcome these difficulties, we developed and analyzed a range of knowledge representation techniques, which are a class of ThyroScan™ algorithms from Global Biomedical Technologies Inc., California, USA, for automatic classification of benign and malignant thyroid lesions. The analysis is based on data obtained from twenty nodules (ten benign and ten malignant) taken from 3D contrast-enhanced ultrasound images. Fine needle aspiration biopsy and histology confirmed malignancy. Discrete Wavelet Transform (DWT) and texture algorithms are used to extract relevant features from the thyroid images. The resulting feature vectors are fed to three different classifiers: K-Nearest Neighbor (K-NN), Probabilistic Neural Network (PNN), and Decision Tree (DeTr). The performance of these classifiers is compared using Receiver Operating Characteristic (ROC) curves. Our results show that combination of DWT and texture features coupled with K-NN resulted in good performance measures with the area of under the ROC curve of 0.987, a classification accuracy of 98.9%, a sensitivity of 98%, and a specificity of 99.8%. Finally, we have proposed a novel integrated index called Thyroid Malignancy Index (TMI), which is made up of texture features, to diagnose benign or malignant nodules using just one index. We hope that this TMI will help clinicians in a more objective detection of benign and malignant thyroid lesions.

High Diagnostic Accuracy and Interobserver Reliability of Real-Time Elastography in the Evaluation of Thyroid Nodules

Elastography is a new diagnostic tool in the evaluation of thyroid nodules. Aim of the study was to evaluate the accuracy and reliability of elastography in discriminating thyroid lesions and the interobserver variability. One hundred thirty-two nodules in 115 patients selected for thyroid surgery underwent conventional ultrasound and elastographic evaluation. Elastography score was divided in four categories (totally elastic nodule, mainly elastic, mainly rigid and totally rigid) according to signal distribution. Three independent operators conducted the study. Final histology showed 92 benign nodules and 40 malignant. On elastography, 77/92 benign nodules were classified as score 1 or 2 and 34/40 malignant nodules as score 3 or 4 (sensitivity 85%, specificity 83.7%, positive predictive value [PPV] 69.3%, negative predictive value [NPV] 92.7%). Rate of concordance between operators was good (K test: 0.64, p < 0.0001). Simple to use, with good interobserver agreement, elastography has all the requisites to become an important complement of conventional US examination in the near future.

Non-invasive automated 3D thyroid lesion classification in ultrasound: A class of ThyroScan™ systems.

Ultrasound-based thyroid nodule characterization into benign and malignant types is limited by subjective interpretations. This paper presents a Computer Aided Diagnostic (CAD) technique that would present more objective and accurate classification and further would offer the physician a valuable second opinion. In this paradigm, we first extracted the features that quantify the local changes in the texture characteristics of the ultrasound off-line training images from both benign and malignant nodules. These features include: Fractal Dimension (FD), Local Binary Pattern (LBP), Fourier Spectrum Descriptor (FS), and Laws Texture Energy (LTE). The resulting feature vectors were used to build seven different classifiers: Support Vector Machine (SVM), Decision Tree (DT), Sugeno Fuzzy, Gaussian Mixture Model (GMM), K-Nearest Neighbor (KNN), Radial Basis Probabilistic Neural Network (RBPNN), and Naive Bayes Classifier (NBC). Subsequently, the feature vector-classifier combination that results in the maximum classification accuracy was used to predict the class of a new on-line test thyroid ultrasound image. Two data sets with 3D Contrast-Enhanced Ultrasound (CEUS) and 3D High Resolution Ultrasound (HRUS) images of 20 nodules (10 benign and 10 malignant) were used. Fine needle aspiration biopsy and histology results were used to confirm malignancy. Our results show that a combination of texture features coupled with SVM or Fuzzy classifiers resulted in 100% accuracy for the HRUS dataset, while GMM classifier resulted in 98.1% accuracy for the CEUS dataset. Finally, for each dataset, we have proposed a novel integrated index called Thyroid Malignancy Index (TMI) using the combination of FD, LBP, LTE texture features, to diagnose benign or malignant nodules. This index can help clinicians to make a more objective differentiation of benign/malignant thyroid lesions. We have compared and benchmarked the system with existing methods.

Characterization of single thyroid nodules by contrast-enhanced 3-D ultrasound.

High-resolution ultrasonography (HRUS) has potentialities in differential diagnosis between malignant and benign thyroid lesions, but interpretative pitfalls remain and accuracy is still poor. We developed an image processing technique for characterizing the intra-nodular vascularization of thyroid lesions. Twenty nodules (10 malignant) were analyzed by three-dimensional (3-D) contrast-enhanced ultrasound imaging. The 3-D volumes were preprocessed and skeletonized. Seven vascular parameters were computed on the skeletons: number of vascular trees (NT); vascular density (VD); number of branching nodes (or branching points) (NB); mean vessel radius (MR); 2-D (DM) and 3-D (SOAM) tortuosity; and inflection count metric (ICM). Results showed that the malignant nodules had higher values of NT (83.1 vs. 18.1), VD (00.4 vs. 0.01), NB (1453 vs. 552), DM (51 vs. 18), ICM (19.9 vs. 8.7) and SOAM (26 vs. 11). Quantification of nodular vascularization based on 3-D contrast-enhanced ultrasound and skeletonization could help differential diagnosis of thyroid lesions.

EFFICACY AND SAFETY OF RADIOFREQUENCY THERMAL ABLATION IN THE TREATMENT OF THYROID NODULES WITH PRESSURE SYMPTOMS IN ELDERLY PATIENTS

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Effect of complex wavelet transform filter on thyroid tumor classification in three-dimensional ultrasound

Ultrasonography has great potential in differentiating malignant thyroid nodules from the benign ones. However, visual interpretation is limited by interobserver variability, and further, the speckle distribution poses a challenge during the classification process. This article thus presents an automated system for tumor classification in three-dimensional contrast-enhanced ultrasonography data sets. The system first processes the contrast-enhanced ultrasonography images using complex wavelet transform–based filter to mitigate the effect of speckle noise. The higher order spectra features are then extracted and used as input for training and testing a fuzzy classifier. In the off-line training system, higher order spectra features are extracted from a set of images known as the training images. These higher order spectra features along with the clinically assigned ground truth are used to train the classifier and obtain an estimate of the classifier or training parameters. The ground truth tells the class label of the image (i.e. whether the image belongs to a benign or malignant nodule). During the online testing phase, the estimated classifier parameters are applied on the higher order spectra features that are extracted from the testing images to predict their class labels. The predicted class labels are compared with their corresponding original ground truth to evaluate the performance of the classifier. Without utilizing the complex wavelet transform filter, the fuzzy classifier demonstrated an accuracy of 91.6%, while utilizing the complex wavelet transform filter, the accuracy significantly boosted to 99.1%.

Automated benign & malignant thyroid lesion characterization and classification in 3D contrast-enhanced ultrasound

In this work, we present a Computer Aided Diagnosis (CAD) based technique for automatic classification of benign and malignant thyroid lesions in 3D contrast-enhanced ultrasound images. The images were obtained from 20 patients. Fine needle aspiration biopsy and histology confirmed malignancy. Discrete Wavelet Transform (DWT) and texture based features were extracted from the thyroid images. The resulting feature vectors were used to train and test three different classifiers: K-Nearest Neighbor (K-NN), Probabilistic Neural Network (PNN), and Decision Tree (DeTr) using ten-fold cross validation technique. Our results show that combination of DWT and texture features in the K-NN classifier resulted in a classification accuracy of 98.9%, a sensitivity of 98%, and a specificity of 99.8%. Thus, the preliminary results of the proposed technique show that it could be adapted as an adjunct tool that can give valuable second opinions to the doctors regarding the nature of the thyroid nodule. The technique is cost-effective, non-invasive, fast, completely automated and gives more objective and reproducible results compared to manual analysis of the ultrasound images. We however intend to establish the clinical applicability of this technique by evaluating it with more data in the future.