Schilddrüsen-Elastografie

Bojunga, Jörg

doi:10.1055/a-0790-0885

Cited by 7 publications

(4 citation statements)

References 33 publications

(37 reference statements)

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“…Real-time tissue strain elastography helps assess the anatomical structure and biological traits of PTC because it represents the relative hardness of the lesion and its surrounding tissues, whereas the hardness of PTC tissues is closely related to its internal pathological structure. Bojunga et al 25 showed that elastography US could effectively distinguish between benign and malignant thyroid nodules. Recent research has demonstrated that varied cell arrangements and cell compositions result in varying tissue elastography indices 26,27 ; the harder elastography US imaging is for PTC, the higher its malignancy.…”

Section: Discussionmentioning

confidence: 99%

Predicting BRAFV600E mutations in papillary thyroid carcinoma using six machine learning algorithms based on ultrasound elastography

Agyekum,

Wang,

et al. 2023

Sci Rep

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The most common BRAF mutation is thymine (T) to adenine (A) missense mutation in nucleotide 1796 (T1796A, V600E). The BRAFV600E gene encodes a protein-dependent kinase (PDK), which is a key component of the mitogen-activated protein kinase pathway and essential for controlling cell proliferation, differentiation, and death. The BRAFV600E mutation causes PDK to be activated improperly and continuously, resulting in abnormal proliferation and differentiation in PTC. Based on elastography ultrasound (US) radiomic features, this study seeks to create and validate six distinct machine learning algorithms to predict BRAFV6OOE mutation in PTC patients prior to surgery. This study employed routine US strain elastography image data from 138 PTC patients. The patients were separated into two groups: those who did not have the BRAFV600E mutation (n = 75) and those who did have the mutation (n = 63). The patients were randomly assigned to one of two data sets: training (70%), or validation (30%). From strain elastography US images, a total of 479 radiomic features were retrieved. Pearson's Correlation Coefficient (PCC) and Recursive Feature Elimination (RFE) with stratified tenfold cross-validation were used to decrease the features. Based on selected radiomic features, six machine learning algorithms including support vector machine with the linear kernel (SVM_L), support vector machine with radial basis function kernel (SVM_RBF), logistic regression (LR), Naïve Bayes (NB), K-nearest neighbors (KNN), and linear discriminant analysis (LDA) were compared to predict the possibility of BRAFV600E. The accuracy (ACC), the area under the curve (AUC), sensitivity (SEN), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV), decision curve analysis (DCA), and calibration curves of the machine learning algorithms were used to evaluate their performance. ① The machine learning algorithms' diagnostic performance depended on 27 radiomic features. ② AUCs for NB, KNN, LDA, LR, SVM_L, and SVM_RBF were 0.80 (95% confidence interval [CI]: 0.65–0.91), 0.87 (95% CI 0.73–0.95), 0.91(95% CI 0.79–0.98), 0.92 (95% CI 0.80–0.98), 0.93 (95% CI 0.80–0.98), and 0.98 (95% CI 0.88–1.00), respectively. ③ There was a significant difference in echogenicity,vertical and horizontal diameter ratios, and elasticity between PTC patients with BRAFV600E and PTC patients without BRAFV600E. Machine learning algorithms based on US elastography radiomic features are capable of predicting the likelihood of BRAFV600E in PTC patients, which can assist physicians in identifying the risk of BRAFV600E in PTC patients. Among the six machine learning algorithms, the support vector machine with radial basis function (SVM_RBF) achieved the best ACC (0.93), AUC (0.98), SEN (0.95), SPEC (0.90), PPV (0.91), and NPV (0.95).

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Section: Discussionmentioning

confidence: 99%

Predicting BRAFV600E mutations in papillary thyroid carcinoma using six machine learning algorithms based on ultrasound elastography

Agyekum,

Wang,

et al. 2023

Sci Rep

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“…Bojunga et al showed that elasticity ultrasound can effectively distinguish between benign and malignant thyroid nodules (19), while Moon et al found that PTC elastography findings with a degree of high hardness were associated with extrathyroidal invasion (20). These studies provide a new perspective for the ultrasound diagnosis of BRAF V600E mutation-positive and negative PTC.…”

Section: Discussionmentioning

confidence: 99%

Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAFV600E Mutations in Papillary Thyroid Carcinoma

Wang¹,

Agyekum

et al. 2022

Front. Endocrinol.

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BRAFV600E is the most common mutated gene in thyroid cancer and is most closely related to papillary thyroid carcinoma(PTC). We investigated the value of elasticity and grayscale ultrasonography for predicting BRAFV600E mutations in PTC.Methods138 patients with PTC who underwent preoperative ultrasound between January 2014 and 2021 were retrospectively examined. Patients were divided into BRAFV600E mutation-free group (n=75) and BRAFV600E mutation group (n=63). Patients were randomly divided into training (n=96) and test (n=42) groups. A total of 479 radiomic features were extracted from the grayscale and elasticity ultra-sonograms. Regression analysis was done to select the features that provided the most information. Then, 10-fold cross-validation was used to compare the performance of different classification algorithms. Logistic regression was used to predict BRAFV600E mutations.ResultsEight radiomics features were extracted from the grayscale ultrasonogram, and five radiomics features were extracted from the elasticity ultrasonogram. Three models were developed using these radiomic features. The models were derived from elasticity ultrasound, grayscale ultrasound, and a combination of grayscale and elasticity ultrasound, with areas under the curve (AUC) 0.952 [95% confidence interval (CI), 0.914−0.990], AUC 0.792 [95% CI, 0.703−0.882], and AUC 0.985 [95% CI, 0.965−1.000] in the training dataset, AUC 0.931 [95% CI, 0.841−1.000], AUC 0. 725 [95% CI, 0.569−0.880], and AUC 0.938 [95% CI, 0.851−1.000] in the test dataset, respectively.ConclusionThe radiomic model based on grayscale and elasticity ultrasound had a good predictive value for BRAFV600E gene mutations in patients with PTC.

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“…TI-RADS (Thyroid Imaging Reporting And Data System) versucht durch bestimmte sonografische Kriterien wie unscharfe Abgrenzbarkeit, Hypoechogenität, Mikrokalk, "taller than wide" das Risiko für das Vorliegen einer malignen Veränderung zu quantifizieren und danach das Vorgehen wie Kontrolle, Feinnadelaspirationszytologie oder Operation auszurichten [13]. Die Etablierung der Elastografie als semiobjektives Verfahren zur Bestimmung der Härte eines Gewebes schafft einen weiteren Parameter zur Eingrenzung der präoperativen Risikostratifizierung [14]. Die sonografischen Verfahren haben die Bedeutung der Szintigrafie in der Beurteilung von knotigen Schilddrüsenfoci hinsichtlich ihrer Malignität ("kalter Knoten = bösartig") deutlich relativiert.…”

Section: Introductionunclassified

Die Behandlung von Schilddrüsenmalignomen aus HNO-ärztlicher Sicht

Issing¹,

Köhler²,

Tebben³

et al. 2021

Laryngorhinootologie

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Zusammenfassung Einleitung Die Zahl der Schilddrüsenmalignome zeigt eine deutliche Zunahme. Da die Schilddrüse an der HNO-Klinik Bad Hersfeld im Fokus steht, war dies für uns Anlass, unsere Behandlungsresultate zu untersuchen und Erfahrungen darzustellen. Material und Methoden Es handelt sich um eine Untersuchung beginnend im Jahre 2014 bis zum Juli 2020. Es wurden alle Patienten mit Schilddrüsenmalignomen erfasst und wichtige demografische und medizinische Parameter wie Alter, Geschlecht, Histologie, Calcium, OP-Dauer, Rekurrensparese etc. registriert. Ergebnisse Es wurden insgesamt 63 Patienten mit malignen Schilddrüsenerkrankungen eingeschlossen. Davon waren 42 weiblichen und 21 männlichen Geschlechts. Die Altersspanne reichte von 11 bis zu 95 Jahren. Patienten mit differenzierten Schilddrüsenkarzinomen waren im Schnitt jünger als diejenigen mit anaplastischen Malignomen. Histologisch dominierten die papillären Schilddrüsenkarzinome mit 65 % (n = 41) gegenüber anderen Varianten wie dem follikulären (n = 6), medullären (n = 5) und entdifferenzierten Karzinom (n = 6). Alle Patienten wurden einer operativen Behandlung unterzogen; postoperativ erhielten die Betroffenen mit fortgeschrittenen, differenzierten Karzinomen eine Radiojodtherapie. Von den Patienten mit einem entdifferenzierten Karzinom sind alle ihrem Leiden erlegen, während nach unserer Kenntnis nur eine Betroffene mit einem differenzierten Malignom tumorbedingt verstorben ist. Schlussfolgerung In die Behandlung von malignen Schilddrüsenerkrankungen ist der HNO-Arzt eingebunden. Wie bei den benignen Erkrankungen der endokrinen Halsorgane ist eine interdisziplinäre Zusammenarbeit entscheidend.

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Schilddrüsen-Elastografie

Cited by 7 publications

References 33 publications

Predicting BRAFV600E mutations in papillary thyroid carcinoma using six machine learning algorithms based on ultrasound elastography

Predicting BRAFV600E mutations in papillary thyroid carcinoma using six machine learning algorithms based on ultrasound elastography

Radiomic Model for Determining the Value of Elasticity and Grayscale Ultrasound Diagnoses for Predicting BRAFV600E Mutations in Papillary Thyroid Carcinoma

Die Behandlung von Schilddrüsenmalignomen aus HNO-ärztlicher Sicht

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