Comparative Diagnostic Evaluation with Contrast-Enhanced Ultrasound, Computed Tomography and Magnetic Resonance Imaging in Patients with Pancreatic Cystic Neoplasms

Can cereal-based oral contrast agents-assisted ultrasound become an alternative to non-contrast magnetic resonance imaging (MRI) in radiological follow-up for pancreatic cystic lesions?

Background

Pancreatic cystic lesions (PCLs) are recommended to be examined by magnetic resonance imaging (MRI), yet MRI still has limitations, such as high costs, the risk of triggering claustrophobia, and relatively low availability compared with ultrasound. Oral contrast agents-assisted ultrasound has been used to examine the gallbladder and stomach, but whether oral contrast agents could improve the accuracy of transabdominal ultrasound (TAUS) for PCLs and could be a potential alternative to non-contrast MRI for PCL follow-up has not been studied. This study aimed to explore the value of cereal-based oral contrast agents in improving the accuracy of PCLs during TAUS.

Methods

This is a prospective cohort study. Patients with PCL who were admitted to our center between January 2023 and January 2024 were enrolled, and TAUS was performed before and after taking cereal-based oral contrast agents. The imaging quality of the PCL was measured by structural visualization scores. The structural visualization scores of oral contrast agent-assisted ultrasound and non-contrast MRI were also compared.

Results

A total of 27 patients with PCLs were enrolled, and 30 PCLs were detected. The sonolucency of the PCL improved after oral contrast agent administration. Before taking the agent, only 30% of patients had satisfactory sonolucency; after taking the oral contrast agent, the corresponding proportion reached 80% (P=0.002). The structural visualization score of the PCL determined by oral contrast agent-assisted TAUS was higher than that determined without the aid of an agent [1 (0-6) vs. 1 (0-3), P=0.001], which was mainly reflected in the increase in the number of visible septa after taking the agent. No significant difference was detected between the structural visualization score of the PCL examined by oral contrast agent-assisted TAUS and that examined by non-contrast MRI and the correlation between the 2 types of scores were satisfactory [1 (0-6) vs. 2 (0-7), P=0.070, Spearman correlation factor r=0.880].

Conclusions

This study used a structured scoring system to confirm that cereal-based oral contrast agents could improve the ultrasound quality of PCLs, and the correlation between the quality of oral contrast agent-assisted ultrasound and non-contrast MRI findings on PCLs was satisfactory. Further research to improve visualization of PCLs on TAUS using oral contrast agents could result in TAUS being a potential alternative to MRI in the follow-up of PCLs in resource-limited situations.

DenseNet model incorporating hybrid attention mechanisms and clinical features for pancreatic cystic tumor classification

PURPOSE

The aim of this study is to develop a deep learning model capable of discriminating between pancreatic plasma cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) by leveraging patient-specific clinical features and imaging outcomes. The intent is to offer valuable diagnostic support to clinicians in their clinical decision-making processes.

METHODS

The construction of the deep learning model involved utilizing a dataset comprising abdominal magnetic resonance T2-weighted images obtained from patients diagnosed with pancreatic cystic tumors at Changhai Hospital. The dataset comprised 207 patients with SCN and 93 patients with MCN, encompassing a total of 1761 images. The foundational architecture employed was DenseNet-161, augmented with a hybrid attention mechanism module. This integration aimed to enhance the network's attentiveness toward channel and spatial features, thereby amplifying its performance. Additionally, clinical features were incorporated prior to the fully connected layer of the network to actively contribute to subsequent decision-making processes, thereby significantly augmenting the model's classification accuracy. The final patient classification outcomes were derived using a joint voting methodology, and the model underwent comprehensive evaluation.

RESULTS

Using the five-fold cross validation, the accuracy of the classification model in this paper was 92.44%, with an AUC value of 0.971, a precision rate of 0.956, a recall rate of 0.919, a specificity of 0.933, and an F1-score of 0.936.

CONCLUSION

This study demonstrates that the DenseNet model, which incorporates hybrid attention mechanisms and clinical features, is effective for distinguishing between SCN and MCN, and has potential application for the diagnosis of pancreatic cystic tumors in clinical practice.

Abdominal ultrasound in the characterization of branch-duct intraductal papillary mucinous neoplasms: A new tool for surveillance of low-risk patients?

BACKGROUND

Magnetic resonance imaging (MRI) is regarded as gold-standard for intraductal papillary mucinous neoplasms (IPMNs) follow-up. Given the low risk of transformation and the increasing population under surveillance, there is growing interest in identifying optimal follow-up strategies.

AIM

To evaluate reliability of abdominal ultrasound (US) for characterization of low-risk IPMN, compared to MRI.

METHODS

Prospective monocentric study among 79 consecutive patients with a suspected BD-IPMN on US. Each patient underwent confirmatory MRI. We evaluated Cohen's kappa statistic and concordance rate (CR) between MRI and US.

RESULTS

Of 79 suspected IPMNs on US, MRI confirmed 71 BD-IPMNs. There was high agreement for cyst location and number (CR and kappa of 77.5 % and 81.7 % and 0.66±0.08 and 0.62±0.11 respectively). We found high agreement for cyst size (CR=96.5 %, kappa=0.93±0.05) and main pancreatic duct (MPD) dilatation (CR=100 %, kappa=1). There was a good agreement for thickened septa (CR=80.3 %, kappa=0.38±0.12). US seems inferior to MRI for the identification of mural nodules < 5 mm (CR=97.2 %, kappa=0).

CONCLUSIONS

In a cohort of low-risk BD-IPMN, US presented high agreement rate with MRI regarding location, number, and size. There was a good agreement for MPD dilatation and thickened septa, while US underperform for detection of mural nodules < 5 mm.

The Diagnostic Impact of Contrast-Enhanced Computed Tomography (CECT) in Evaluating Lymph Node Involvement in Colorectal Cancer: A Comprehensive Review

Colorectal cancer (CRC) remains a significant global health burden, necessitating accurate staging and treatment planning for optimal patient outcomes. Lymph node involvement is a critical determinant of prognosis in CRC, emphasizing the importance of reliable imaging techniques for its evaluation. Contrast-enhanced computed tomography (CECT) has emerged as a cornerstone in CRC imaging, offering high-resolution anatomical detail and vascular assessment. This comprehensive review synthesizes the existing literature to evaluate the diagnostic impact of CECT in assessing lymph node involvement in CRC. Key findings highlight CECT's high sensitivity and specificity in detecting lymph node metastases, facilitating accurate staging and treatment selection. However, challenges such as limited resolution for small lymph nodes and potential false-positives call for a cautious interpretation. Recommendations for clinical practice suggest the integration of CECT into multidisciplinary treatment algorithms, optimizing imaging protocols and enhancing collaboration between radiologists and clinicians. Future research directions include refining imaging protocols, comparative effectiveness studies with emerging modalities, and prospective validation of CECT's prognostic value. Overall, this review stresses the pivotal role of CECT in CRC management and identifies avenues for further advancements in imaging-guided oncology care.

Radiomics Based on Contrast-Enhanced Ultrasound Images for Diagnosis of Pancreatic Serous Cystadenoma

OBJECTIVE

The purpose of the study was to develop and validate a radiomics model by using contrast-enhanced ultrasound (CEUS) data for pre-operative differential diagnosis of pancreatic cystic neoplasms (PCNs), especially pancreatic serous cystadenoma (SCA).

METHODS

Patients with pathologically confirmed PCNs who underwent CEUS examination at Chinese PLA hospital from May 2015 to August 2022 were retrospectively collected. Radiomic features were extracted from the regions of interest, which were obtained based on CEUS images. A support vector machine algorithm was used to construct a radiomics model. Moreover, based on the CEUS image features, the CEUS and the combined models were constructed using logistic regression. The performance and clinical utility of the optimal model were evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity and decision curve analysis.

RESULTS

A total of 113 patients were randomly split into the training (n = 79) and test cohorts (n = 34). These patients were pathologically diagnosed with SCA, mucinous cystadenoma, intraductal papillary mucinous neoplasm and solid-pseudopapillary tumor. The radiomics model achieved an AUC of 0.875 and 0.862 in the training and test cohorts, respectively. The sensitivity and specificity of the radiomics model were 81.5% and 86.5% in the training cohort and 81.8% and 91.3% in the test cohort, respectively, which were higher than or comparable with that of the CEUS model and the combined model.

CONCLUSION

The radiomics model based on CEUS images had a favorable differential diagnostic performance in distinguishing SCA from other PCNs, which may be beneficial for the exploration of personalized management strategies.

Identification of high-risk features in mucinous cystic neoplasms of the pancreas

BACKGROUND

Mucinous cystic neoplasms of the pancreas are uncommon tumors that have the potential of becoming cancer. There is no consensus regarding the high-risk features of these tumors. Our study aimed to identify the preoperative demographic, clinical, or radiologic factors that can predict the presence of high-grade dysplasia or invasive carcinoma in mucinous cystic neoplasms of the pancreas.

METHODS

We identified 157 patients who underwent resection and fulfilled the pathologic criteria for mucinous cystic neoplasms of the pancreas in a prospectively maintained database spanning 3 decades (1990-2020). Multivariable logistic regression was used to identify predictors of high-grade dysplasia or invasive carcinoma in mucinous cystic neoplasms of the pancreas.

RESULTS

The rate of high-grade dysplasia or invasive carcinoma was 11%. Tumor size ≥4 cm (P < .001), mural nodularity (P = .04), and a serum CA 19-9 level >37 U/mL (P < .001) were associated with high-grade dysplasia or invasive carcinoma. In the multivariable analysis, tumor size ≥4 cm (odds ratio 16.9, 95% confidence interval 2.04-140, P = .009) and a CA 19-9 level >37 U/mL (odds ratio 5.68, 95% confidence interval 1.52-21.3, P = .010) were predictors of high-grade dysplasia or invasive carcinoma. There were no tumors with high-grade dysplasia or invasive carcinoma in patients with tumor size <4 cm in the absence of an elevated CA 19-9 or mural nodularity.

CONCLUSION

Tumors with a size ≥4 cm and/or a high CA 19-9 level should be considered for prompt surgical resection. Conversely, tumors <4 cm with no other high-risk features have a negligible risk for high-grade dysplasia or invasive carcinoma and may benefit from nonoperative surveillance. Mural nodularity is an additional suspicious feature. These findings may contribute to future guidelines.

Practice Management Strategies for Imaging Facilities Facing an Acute Iodinated Contrast Media Shortage

An unanticipated but severe shortage in iodinated contrast media (ICM) is currently affecting imaging practices across the globe and is expected to persist through at least the end of June 2022. This supply shock may lead to healthcare systems experiencing an acute imaging crisis, as many affected facilities have contrast agent supplies that are anticipated to last only a week or two under normal operating conditions. To maximize the opportunity to continue to provide optimal care for patients with emergent or life-threatening imaging indications and thereby minimize the overall impact on patient care, practice leaders will need to quickly assess their contrast material inventories, prioritize examination indications, and reduce their expected short-term usage of ICM. This Clinical Perspective reviews ICM conservation techniques that we have deployed, or are considering deploying, depending on the severity and length of the supply shortage.

Focal Pancreatic Lesions: Role of Contrast-Enhanced Ultrasonography

The introduction of contrast-enhanced ultrasonography (CEUS) has led to a significant improvement in the diagnostic accuracy of ultrasound in the characterization of a pancreatic mass. CEUS, by using a blood pool contrast agent, can provide dynamic information concerning macro- and micro-circulation of focal lesions and of normal parenchyma, without the use of ionizing radiation. On the basis of personal experience and literature data, the purpose of this article is to describe and discuss CEUS imaging findings of the main solid and cystic pancreatic lesions with varying prevalence.

Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning

Pancreatic cystic lesions (PCL) are a frequent and underreported incidental finding on CT scans and can transform into neoplasms with devastating consequences. We developed and evaluated an algorithm based on a two-step nnU-Net architecture for automated detection of PCL on CTs. A total of 543 cysts on 221 abdominal CTs were manually segmented in 3D by a radiology resident in consensus with a board-certified radiologist specialized in abdominal radiology. This information was used to train a two-step nnU-Net for detection with the performance assessed depending on lesions' volume and location in comparison to three human readers of varying experience. Mean sensitivity was 78.8 ± 0.1%. The sensitivity was highest for large lesions with 87.8% for cysts ≥220 mm³ and for lesions in the distal pancreas with up to 96.2%. The number of false-positive detections for cysts ≥220 mm³ was 0.1 per case. The algorithm's performance was comparable to human readers. To conclude, automated detection of PCL on CTs is feasible. The proposed model could serve radiologists as a second reading tool. All imaging data and code used in this study are freely available online.

Update in Contrast-Enhanced Ultrasound

BACKGROUND

The aim of modern medicine is to safely classify diseases for successful therapy without invasive measures. Sonography, computed tomography (CT), and magnetic resonance imaging (MRI) are potent imaging techniques. However, without contrast medium, the informative value of the 3 native methods is limited. The advantages of sonography are: no radiation exposure or previously known physically harmful interactions with tissue, proportionate disappearance of a contrast agent risk, no (probably irreversible) contrast agent deposits, and no risk of renal insufficiency. But, is that enough to compete with of even exceed CT and MRI?

SUMMARY

In this review, the state of the art of contrast-enhanced ultrasound (CEUS) in the abdominal cavity is presented. The remarkable diagnostic possibilities can unfortunately only be demonstrated here in a small number of impressive, typical case studies underpinned by the literature, so that, from one's own perspective, the full spectrum of CEUS can be used by oneself or initiated. Within the limits of physics, the real-time dynamics of CEUS enable conclusions to be drawn, so that with the current technology, sonography, including expansion by contrast, can be considered superior to other imaging methods. It is not uncommon for CEUS to have the value of a control and reference method.

KEY MESSAGES

Sonography very often enables reliable diagnostics. The introduction of a contrast agent in sonography has led to a quantum leap similar to that of other imaging techniques. Already natively, the real-time representation of dynamic events leads to a certain superiority, i.e., complete observation of the inflow and outflow phases of the contrast medium and the resulting diagnostic; tissue-specific differentiation options provide a unique selling point. Further advantages of the first-choice imaging diagnostic method are: a lack of radiation exposure, repeatability of the examination at any time, local independence, a negligible allergy rate compared to the contrast agents of other methods, and a lack of kidney and thyroid exposure or excluded deposits.