Journal of Ultrasonography最新文献

Ultrasound-guided percutaneous core-needle biopsy is an excellent diagnostic tool for solid pancreatic lesions. It allows for identifying neoplastic pancreatic tumors with nearly 100% sensitivity, specificity and accuracy. Unresectable tumor assessment prior to planned palliative treatment is the primary indication for percutaneous pancreatic tumor biopsy. In the case of potential tumors eligible for radical surgery, endosonography-guided biopsy is used, if clinically necessary, to avoid the peritoneal spread of tumor cells during puncture. The possibility of obtaining a specimen for a detailed microscopic assessment during an easily accessible and simple procedure is the main advantage of core-needle biopsy over the low, yet higher when compared to other biopsy techniques, risk of complications. Obtaining tissue samples for molecular analysis is essential for palliative targeted therapy in pancreatic cancer and may become the main indication for the common core-needle biopsy of inoperable pancreatic tumors in the near future. The present paper describes the indications and the technique for core-needle biopsy in pancreatic tumors. Based on the studies published to date, the safety of the procedure, significant complications, including bleeding in particular, and the diagnostic sensitivity and specificity, also compared to other biopsy techniques, have been summarized. The present paper may contribute to the introduction of core-needle biopsy of pancreatic masses into clinical practice.

The aim of this article is to provide a short review of the literature concerning the basic principles, usefulness and limitations of ultrasound-guided biopsy of musculoskeletal soft-tissue tumors, with particular focus on core needle biopsies. Musculoskeletal soft-tissue tumors represent a rare and complex group of heterogeneous lesions. Prompt diagnosis of these uncommon lesions can improve the outcome and increase the patient survival rate. A biopsy examination of soft-tissue tumors with imaging modalities is necessary in all cases of aggressive or undetermined lesions. Although fine needle aspiration can be helpful for the biopsy of certain tumor types, core needle biopsy is a standard procedure in most tertiary sarcoma centers. It has a high diagnostic accuracy, low complication rate and lower price in comparison to open biopsy, and can replace it in the majority of cases of soft-tissue tumor assessment. However, the examining physician has to be familiar with the technique, and the strengths and potential difficulties in performing ultrasound-guided biopsy, as well as possible solutions to obstacles. Several recently developed ultrasound techniques can be helpful and improve the outcome of imaging-guided biopsies of musculoskeletal lesions.

Purpose: Pseudotumor is a rare complication after arthroplasty, most often of the hip joint, in response to metal particles present in the implant. There are merely sporadic reports of pseudotumor in patients with bone sarcoma after sparing surgery with endoprosthesis implant. The aim of this study is to present the characteristic imaging features of pseudotumor.

Case report: We present a case of a 21-year-old male patient in whom a scheduled follow-up ultrasound revealed a painless lesion suspected of local recurrence at the border of the endoprosthesis and the bone stump 3.5 years after the end of treatment for osteosarcoma of the femur. Histopathology of the biopsy specimen revealed that the lesion was a pseudotumor.

Conclusions: Although pseudotumor is sporadic in patients treated with endoprosthesis for bone sarcoma, their prolonged survival could bear the risk of such a complication. Imaging studies, in particular ultrasound, may be helpful in differentiating from local recurrence of sarcoma, however, the histopathology of the specimen obtained by open biopsy at a reference center is crucial for the final diagnosis.

Numerous scientific societies around the world have published their TIRADS (Thyroid Imaging Reporting and Data System) classifications that evaluate the risk of malignancy of focal thyroid lesions, presenting different ultrasound features for each category and lesion size thresholds to determine eligibility for biopsy. The use of such risk estimation systems in focal thyroid lesions facilitates the reporting of thyroid ultrasound findings and improves the qualification of focal lesions for fine-needle aspiration biopsy (FNAB). In this publication, the three most popular TIRADS classifications, European - EU-TIRADS, Korean - K-TIRADS, and developed by the American Society of Radiology - ACR-TIRADS, are presented and discussed based on a literature review. The results of available head-to-head statistical analyses comparing the classifications are also presented. The advantage of the EU-TIRADS and K-TIRADS systems is that they include only the most important ultrasound features, so their application is not time-consuming, and the scores are easy to incorporate into clinical practice. ACR-TIRADS, unlike other scales, is based on a unique classification system and represents the most comprehensive classification. Each of the five categories of ultrasound features - morphology, echogenicity, shape, margins, microcalcifications - are evaluated and assigned a score from 0 to 3, with a higher score being associated with a higher risk of cancer. Based on the available data, the greatest benefit has been demonstrated for the ACR-TIRADS classification, which also has implications for minimising the number of unnecessary FNABs. However, limitations related to the heterogeneity of the groups analysed in the study, including differences in the populations studied, inclusion criteria, proportions of patients of either sexes, and the number of malignant lesions analysed, should also be taken into account.

Breast cancer, which is the most common cancer in women, is a major problem both in Poland and worldwide. Mammography remains the primary screening method. However, the sensitivity of mammographic screening is lower in women with dense glandular breasts due to tissue overlap and the effect of the glandular tissue obscuring the tumor and the fact that tumors and glandular tissue show similar X-ray absorption. Consequently, other methods are being sought to increase breast cancer detection rates. Currently, the most common and used methods are ultrasonography, magnetic resonance imaging and advanced mammographic methods (digital breast tomosynthesis and contrast-enhanced spectral mammography). Despite many advantages and superiority over mammography in dense breasts, they also have many disadvantages. Ultrasound is operator-dependent and the other techniques are expensive or not widely available. The Automated Breast Ultrasound Service (ABUS) technique appears to be a good option in terms of both effectiveness and lower cost.

Breast cancer is a heterogeneous disease both in its clinical and radiological manifestations and response to treatment. This is largely due to the polymorphism of the histological types as well as diversified molecular profiles of individual breast cancer types. Progress in the understanding of the biology of breast cancer was made with the introduction of immunohistochemical research into the common practice. On this basis, four main breast cancer subtypes were distinguished: luminal A, luminal B, HER2 positive (human epidermal growth factor receptor-2 positive), and triple negative cancer. The classification of a tumour to an appropriate subtype allows for the optimisation of treatment (surgery or pre-operative chemotherapy). In this study, the authors present different patterns of breast cancer subtypes in ultrasound examination and differences in their treatment, with particular emphasis on aggressive breast cancer subtypes, such as triple negative or HER2 positive. They can, unlike the luminal subtypes, create diagnostic problems. Based on multifactorial analysis of the ultrasound image, with the assessment of lesion margins, orientation, shape, echogenicity, vascularity, the presence of calcifications or assessment by sonoelastography, it is possible to initially differentiate individual subtypes.

Neoadjuvant chemotherapy is increasingly becoming the first treatment step in breast cancer. Despite the enormous advantages of this therapy, it is a method characterized by a high level of toxicity and thus carries a huge burden for the patient. Therefore, it is highly desirable to begin monitoring the patient's response to treatment at an earlier stage. Currently, apart from traditional imaging methods, a completely new technique (in the context of monitoring the outcomes of chemotherapy), called quantitative ultrasound, is gaining popularity. It is a method based on the exact same ultrasound echoes as in traditional ultrasound imaging. The innovative approach of the method is that these echoes are not used for visualization but to characterize the condition of the tissue by parameterizing it with the aid of ultrasound biomarkers. The biomarkers make it possible to assess the state of the tissue at the microscopic level, and thus evaluate changes occurring in the tissue under the influence of treatment at a very early treatment stage. The present paper aims to familiarize the reader with the physical foundations of this method as well as present the latest results of related research.

Uterine tumors are a challenge encountered by every gynecologist in clinical practice. In the era of increasing incidence of endometrial cancer in the general population of women at reproductive age, compared to other genital malignancies, we should not forget about other tumors originating from the mucous and muscular layer of the uterus. Clear ultrasonographic differentiation of uterine tumors into benign (myomas) and malignant (sarcomas) lesions may sometimes prove impossible. Myomas, the most common uterine tumors, are characterized by discrete vascularization on color Doppler and high blood flow velocity as well as the lack of early diastolic notch on Doppler ultrasound. Sarcomas, on the other hand, show characteristic rich vascularization. Rapid tumor growth should also be noted when making the diagnosis. There are multiple known causes of uterine tumors. So far, no clear Doppler flow markers have been identified to characterize benign and malignant lesions.

Sarcoidosis is a systemic inflammatory disease of unknown aetiology. Given its complex clinical presentation, the disorder frequently causes diagnostic challenges. In most cases, the primary manifestation is in the lungs and mediastinum. Breast involvement as the primary manifestation of sarcoidosis is rare, accounting for less than 1% of cases. The authors present the case of a 44-year-old woman whose disease first manifested as multiple non-specific BIRADS 4 lesions in both breasts, accompanied by axillary lymphadenopathy, detected by ultrasound examination. The lesions were not visible on mammography. The course of the disease was clinically silent, with intermittent remissions, until the complete resolution of focal breast lesions on ultrasound after two years of follow-up. The paper presents an algorithm for the management of multifocal breast pathology with associated lymphadenopathy, which led to the prompt verification of sarcoidosis.

Aim of the study: Deep neural networks have achieved good performance in breast mass classification in ultrasound imaging. However, their usage in clinical practice is still limited due to the lack of explainability of decisions conducted by the networks. In this study, to address the explainability problem, we generated saliency maps indicating ultrasound image regions important for the network's classification decisions.

Material and methods: Ultrasound images were collected from 272 breast masses, including 123 malignant and 149 benign. Transfer learning was applied to develop a deep network for breast mass classification. Next, the class activation mapping technique was used to generate saliency maps for each image. Breast mass images were divided into three regions: the breast mass region, the peritumoral region surrounding the breast mass, and the region below the breast mass. The pointing game metric was used to quantitatively assess the overlap between the saliency maps and the three selected US image regions.

Results: Deep learning classifier achieved the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of 0.887, 0.835, 0.801, and 0.868, respectively. In the case of the correctly classified test US images, analysis of the saliency maps revealed that the decisions of the network could be associated with the three selected regions in 71% of cases.

Conclusions: Our study is an important step toward better understanding of deep learning models developed for breast mass diagnosis. We demonstrated that the decisions made by the network can be related to the appearance of certain tissue regions in breast mass US images.