Instytut Podstawowych Problemów Techniki

Streszczenie:

Ultrasonography is a basic tool used in the evaluation of thyroid nodules, but there is no single feature of this method which predicts malignancy with statistical significance. The aim of the study is to assess the usefulness of contrast enhanced-ultrasound (CEUS) in the differential diagnosis of thyroid nodules. The highest value of the study results from the multiparameter approach to the evaluation of thyroid lesions in the light of new diagnostics methods and assessment of the unique combinations of both B-mode and CEUS features as predictors of thyroid cancers. Moreover, several qualitative contrast features predicting benign lesions were evaluated. The preliminary results indicate that CEUS is a useful tool in assessing the risk of malignancy of thyroid lesions. The combination of the qualitative enhancement parameters and B-mode sonographic features significantly increases the method’s usefulness. Further studies should be performed to introduce CEUS patterns in the diagnostic algorithm of thyroid nodules.

Słowa kluczowe:

thyroid cancer, cancer screening, clinical trial, contrast-enhanced ultrasound, thyroid lesion

Afiliacje autorów:

Streszczenie:

Introduction:
The latest World Health Organization (WHO) classification from 2022 distinguishes the division of low-risk thyroid neoplasms such as non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), follicular tumour of uncertain malignant potential (FT-UMP), and well-differentiated tumour of uncertain malignant potential (WDT-UMP). The final diagnosis is made postoperatively according to histopathologic results. The aim of the study was the assessment of ultrasonographic and cytopathological features of borderline lesions to predict low-risk tumours preoperatively and plan the optimal treatment for that group of patients.

Material and methods:
A total of 35 patients (30 women; 5 men), aged 20–81 years with a mean age of 49 years, were enrolled in the study. The study evaluated 35 focal lesions of the thyroid gland, classified as low-risk neoplasms according to the WHO 2022 classification: FT-UMP (n = 21), NIFTP (n = 7), and WDT-UMP (n = 7). Ultrasonographic features of nodules including contrast-enhanced ultrasound (CEUS) and elastography were assessed by 2 specialists, and the risk of malignancy was evaluated according to EU-TIRADS-PL classification.

Results:
Of the 35 focal thyroid lesions, most were categorised as low or intermediate risk of malignancy according to EU-TIRADS-PL, with dominant category 3 [n = 13 (37.2%)] and category 4 [n = 15 (42.8%)]. High-risk category 5 was assessed in 7 lesions (20%). In cytopathology nodules were categorised as follows (Bethesda System TBSRTC 2023): Bethesda II (n = 4), Bethesda III (n = 2), Bethesda IV (n = 25), Bethesda V (n = 3), and Bethesda VI (n = 1). In the CEUS study, contrasting patterns dominated compared to the surrounding parenchyma, such as enhancement equal to the parenchyma (66.6%) or intense (28.5%), heterogeneous (61.9%), centripetal (42.8%), or diffuse (57.1%) with fast (33.3%) or compared to parenchyma contrast wash-in (42.8%) and its fast (33.3%) or comparable to thyroid parenchyma wash-out (52.3%).

Conclusions:
The study indicates that lesions with uncertain malignant potential typically present features suggesting low to intermediate risk of malignancy based on EU-TIRADS-PL classification, with dominant cytopathologic Bethesda IV category. However, 20% of lesions were assessed tas EU-TIRADS-PL category 5. Low-risk tumours, including NIFTP, FT-UMP, and WDT-UMP, require careful observation and monitoring post surgical treatment due to their potential for recurrence and metastasis. The preoperatively prediction of borderline tumour may play an important role in proper treatment and follow-up.

Słowa kluczowe:

thyroid tumour, ultrasound, thyroid cancer, contrast-enhanced-ultrasound

Afiliacje autorów:

Streszczenie:

Thyroid nodule assessment is an important problem in ultrasound (US) imaging. In this work, we propose a novel approach to thyroid lesion classification in contrast-enhanced ultrasound (CEUS). We develop implicit neural representations (INRs) that jointly encode B-mode and CEUS sequences, mapping spatio-temporal coordinates to both image types. INRs are coordinate-based neural networks that store information in their weights, enabling continuous and compact representations of medical image data. This representation naturally captures texture and contrast dynamics relevant to nodule characterization, without the need for handcrafted features or specialized recurrent architectures. In our study, each CEUS sequence is encoded using a SIREN INR, and a probing technique is then applied in the weight space of the trained networks to differentiate malignant and benign nodules. We evaluated our method on CEUS data, showing that it achieves good classification performance. To our knowledge, this is the first study to apply INRs to CEUS analysis for thyroid nodule assessment, highlighting their potential for deep learning based tissue characterization in US.

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