In vivo detection of breast cancer liver metastases in humanized tumour mice using tumour specific contrast agent BR55®

Exploring the potential of contrast agents in breast cancer echography: current state and future directions

Breast cancer stands as the most frequent malignancy and leading cause of death among women. Early and accurate detection of this pathology represents a crucial factor in enhancing both incidence and mortality rates. Ultrasound (US) examination has been extensively adopted in clinical practice due to its non-invasiveness, affordability, ease of implementation, and wide accessibility, thus representing a valuable first-line diagnostic tool for the study of the mammary gland. In this scenario, recent developments in nanomedicine are paving the way for new interpretations and applications of US diagnostics, which are becoming increasingly personalized based on the molecular phenotype of each tumor, allowing for more precise and accurate evaluations. This review highlights the current state-of-the-art of US diagnosis of breast cancer, as well as the recent advancements related to the application of US contrast agents to the field of molecular diagnostics, still under preclinical study.

Intraoperative ultrasound in minimally invasive thoracic surgery for the detection of pulmonary tumors: First intrathoracic application of TE9 and laparoscopic probe Lap 13-4cs (Mindray)

AIM

To apply intraoperative ultrasound (IO-US) for the first time using a laparascopic probe to detect malignancy-susceptible solitary pulmonary nodules (SPN) and assess macrovascularization using color-coded doppler sonography or power doppler. Description of technical feasibility.

METHODS

Technical description on intrathoracic endoscopic ultrasound. A positive ethics vote from the local ethics committee and written patient consent were available. Intraoperative ultrasound was performed using a laparascopic probe (Lap 13-4cs, Mindray) on the T9 ultrasound machine (Mindray, China). B-scan was used to detect the SPN. Color-coded doppler sonography (CCS) and power doppler were used to assess macrovascularization. Primary end point was the description of the technical performance of the Io-US. Secondary endpoints were the functions of Io-US in characterizing SPN.

RESULTS

Io-US was successfully applied using (n = 2) cases in video-assisted thoracic surgery. All SPN were successfully detected intraoperatively with the intrathoracically placed laparascopy probe using B-mode and examined using CCS or power Doppler (100%). Resection was sonography-guided with marking of the tumor area in all cases without complications. Histological workup revealed malignancy in both cases.

CONCLUSION

Intrathoracic application of laparascopically guided Io-US was technically feasible. In addition to B-mode detection, Io-US using power doppler and color-coded doppler sonography provided initial evidence for characterization of SPN based on macrovascularization.

Deep learning radiomics of ultrasonography for differentiating sclerosing adenosis from breast cancer

OBJECTIVES: The purpose of our study is to present a method combining radiomics with deep learning and clinical data for improved differential diagnosis of sclerosing adenosis (SA)and breast cancer (BC). METHODS: A total of 97 patients with SA and 100 patients with BC were included in this study. The best model for classification was selected from among four different convolutional neural network (CNN) models, including Vgg16, Resnet18, Resnet50, and Desenet121. The intra-/inter-class correlation coefficient and least absolute shrinkage and selection operator method were used for radiomics feature selection. The clinical features selected were patient age and nodule size. The overall accuracy, sensitivity, specificity, Youden index, positive predictive value, negative predictive value, and area under curve (AUC) value were calculated for comparison of diagnostic efficacy. RESULTS: All the CNN models combined with radiomics and clinical data were significantly superior to CNN models only. The Desenet121+radiomics+clinical data model showed the best classification performance with an accuracy of 86.80%, sensitivity of 87.60%, specificity of 86.20% and AUC of 0.915, which was better than that of the CNN model only, which had an accuracy of 85.23%, sensitivity of 85.48%, specificity of 85.02%, and AUC of 0.870. In comparison, the diagnostic accuracy, sensitivity, specificity, and AUC value for breast radiologists were 72.08%, 100%, 43.30%, and 0.716, respectively. CONCLUSIONS: A combination of the CNN-radiomics model and clinical data could be a helpful auxiliary diagnostic tool for distinguishing between SA and BC.

Contrast-enhanced ultrasound perfusion imaging of organs

In multimodal radiologic imaging, contrast-enhanced ultrasound (CEUS) is increasingly used. One of the advantages of CEUS is the possibility of repeated application of contrast media without decreasing renal function or affecting the thyroid gland. Small solid liver lesions can be diagnosed and detected with high accuracy. Moreover, solid lesions in other abdominal organs can also be characterized. Frequent applications for solid lesions in the near field concern thyroid tumors and lymph nodes. For prostate diagnostics, CEUS can be used with an endorectal probe and perfusion imaging. This review explains how the additional (semi-)quantitative perfusion analysis, especially time-intensity curve (TIC) analyses, and wash-in/wash-out kinetics of integrated or external perfusion software programs facilitate new options in dynamic assessment of microvascularization during tumor follow-up care and even minimally invasive tumor therapy.

Quantification of dynamic contrast-enhanced ultrasound (CEUS) in non-cystic breast lesions using external perfusion software

The aim of this present clinical pilot study is the display of typical perfusion results in patients with solid, non-cystic breast lesions. The lesions were characterized using contrast enhanced ultrasound (CEUS) with (i) time intensity curve analyses (TIC) and (ii) parametric color maps. The 24 asymptomatic patients included were genetically tested for having an elevated risk for breast cancer. At a center of early detection of familial ovary and breast cancer, those patients received annual MRI and grey-scale ultrasound. If lesions remained unclear or appeared even suspicious, those patients also received CEUS. CEUS was performed after intravenous application of sulfur hexafluoride microbubbles. Digital DICOM cine loops were continuously stored for one minute in PACS (picture archiving and communication system). Perfusion images and TIC analyses were calculated off-line with external perfusion software (VueBox). The lesion diameter ranged between 7 and 15 mm (mean 11 ± 3 mm). Five hypoechoic irregular lesions were scars, 6 lesions were benign and 12 lesions were highly suspicious for breast cancer with irregular enhancement at the margins and a partial wash out. In those 12 cases, histopathology confirmed breast cancer. All the suspicious lesions were correctly identified visually. For the perfusion analysis only Peak Enhancement (PE) and Area Under the Curve (AUC) added more information for correctly identifying the lesions. Typical for benign lesions is a prolonged contrast agent enhancement with lower PE and prolonged wash out, while scars are characterized typically by a reduced enhancement in the center. No differences (p = 0.428) were found in PE in the center of benign lesions (64.2 ± 28.9 dB), malignant lesions (88.1 ± 93.6 dB) and a scar (40.0 ± 17.0 dB). No significant differences (p = 0.174) were found for PE values at the margin of benign lesions (96.4 ± 144.9 dB), malignant lesions (54.3 ± 86.2 dB) or scar tissue (203.8 ± 218.9 dB). Significant differences (p < 0.001) were found in PE of the surrounding tissue when comparing benign lesions (33.6 ± 25.2 dB) to malignant lesions (15.7 ± 36.3 dB) and scars (277.2 ± 199.9 dB). No differences (p = 0.821) were found in AUC in the center of benign lesions (391.3 ± 213.7), malignant lesions (314.7 ± 643.9) and a scar (213.1 ± 124.5). No differences (p = 0.601) were found in AUC values of the margin of benign lesions (313.3 ± 372.8), malignant lesions (272.6 ± 566.4) or scar tissue (695.0 ± 360.6). Significant differences (p < 0.01) were found in AUC of the surrounding tissue for benign lesions (151.7 ± 127.8), malignant lesions (177.9 ± 1345.6) and scars (1091 ± 693.3). There were no differences in perfusion evaluation for mean transit time (mTT), rise time (RT) and time to peak (TTP) when comparing the center to the margins and the surrounding tissue. The CEUS perfusion parameters PE and AUC allow a very good assessment of the risk of malignant breast lesions and thus a downgrading of BI-RADS 4 lesions. The use of the external perfusion software (VueBox, Bracco, Milan, Italy) did not lead to any further improvement in the diagnosis of suspicious breast lesions and does appears not to have any additional diagnostic value in breast lesions.

Diagnostic performance of intravascular perfusion based contrast-enhanced ultrasound LI-RADS in the evaluation of hepatocellular carcinoma

BACKGROUND

The contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) is a relative new algorithm for hepatocellular carcinoma (HCC) assessment.

OBJECTIVE

To validate the diagnostic efficiency of the intravascular perfusion based CEUS LI-RADS for HCC.

METHODS

Archives of 873 patients with focal liver lesions (FLLs) undergoing CEUS were reviewed, and target images were read by two sonologists independently according to the CEUS LI-RADS. The diagnostic performance was calculated and compared.

RESULTS

Assessment with reference to CEUS LI-RADS, 87 of 218 FLLs (39.9%) were categorized as LR-5, 131 of 218 FLLs (60.1%) were categorized as non-LR-5, 19 of 99 HCCs were categorized as non-LR-5, and 7 of 119 non-HCCs were categorized as LR-5. The sensitivity, specificity, AUROC, positive and negative predictive values of CEUS LI-RADS for diagnosing HCC were 80.81%(95%CI: 71.7%-88.0%), 94.1%(95%CI: 88.3%-97.6%), 0.87 (95%CI: 0.82-0.92), 91.9%(95%CI: 84.1%-96.7%), and 85.5%(95%CI: 78.3%-91.0%), respectively.

CONCLUSIONS

The diagnostic efficiency of the intravascular perfusion based CEUS LI-RADS for the evaluation of HCCs is very good.