Diagnosis of malignant pleural disease: Ultrasound as "a detective probe"

The Value of Contrast-Enhanced Ultrasound (CEUS) in the Evaluation of Central Lung Cancer with Obstructive Atelectasis

Purpose: To assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) alongside contrast-enhanced computed tomography (CECT) in evaluating central lung cancer (CLC). Materials and Methods: From 2006 to 2022, 54 patients with CLC and obstructive atelectasis (OAT) underwent standardized examinations using CEUS in addition to CECT. The ability to differentiate CLC from atelectatic tissue in CECT and CEUS was categorized as distinguishable or indistinguishable. In CEUS, in distinguishable cases, the order of enhancement (time to enhancement) (OE; categorized as either an early pulmonary arterial [PA] pattern or a delayed bronchial arterial [BA] pattern of enhancement), the extent of enhancement (EE; marked or reduced), the homogeneity of enhancement (HE; homogeneous or inhomogeneous), and the decrease in enhancement (DE; rapid washout [<120 s] or late washout [≥120 s]) were evaluated. Results: The additional use of CEUS improved the diagnostic capability of CECT from 75.9% to 92.6% in differentiating a CLC from atelectatic tissue. The majority of CLC cases exhibited a BA pattern of enhancement (89.6%), an isoechoic reduced enhancement (91.7%), and a homogeneous enhancement (91.7%). Rapid DE was observed in 79.2% of cases. Conclusions: In cases of suspected CLC with obstructive atelectasis, the application of CEUS can be helpful in differentiating tumor from atelectatic tissue and in evaluating CLC.

Comparative Evaluation of Chest Ultrasonography and Computed Tomography as Predictors of Malignant Pleural Effusion: A Prospective Study

Malignant pleural effusion (MPE) is a manifestation of advanced cancer that requires a prompt and accurate diagnosis. Ultrasonography (US) and computed tomography (CT) are valuable imaging techniques for evaluating pleural effusions; however, their relative predictive ability for a malignant origin remains debatable. This prospective study aimed to compare chest US with CT findings as predictors of malignancy in patients with undiagnosed exudative pleural effusion. Fifty-four adults with undiagnosed exudative pleural effusions underwent comprehensive clinical evaluation including chest US, CT, and histopathologic biopsy. Blinded radiologists evaluated the US and CT images for features suggestive of malignancy, based on predefined criteria. Diagnostic performance measures were calculated using histopathology as a reference standard. Of the 54 patients, 33 (61.1%) had MPEs confirmed on biopsy. No significant differences between US and CT were found in detecting parietal pleural abnormalities, lung lesions, chest wall invasion, or liver metastasis. US outperformed CT in identifying diaphragmatic pleural thickening ≥10 mm (33.3% vs. 6.1%, p < 0.001) and nodularity (45.5% vs. 3%, p < 0.001), whereas CT was superior for mediastinal thickening (48.5% vs. 15.2%, p = 0.002). For diagnosing MPE, diaphragmatic nodularity detected by US had 45.5% sensitivity and 100% specificity, whereas CT mediastinal thickening had 48.5% sensitivity and 90.5% specificity. Both US and CT demonstrate reasonable diagnostic performance for detecting MPE, with particular imaging findings favoring a malignant origin. US may be advantageous for evaluating diaphragmatic pleural involvement, whereas CT is more sensitive to mediastinal abnormalities.

Diagnostic Accuracy of Ultrasound Guided Percutaneous Pleural Needle Biopsy for Malignant Pleural Mesothelioma

Background/Objectives: Ultrasound (US) has been progressively spreading as the most useful technique for guiding biopsies and fine-needle aspirations that are performed percutaneously. Malignant pleural mesothelioma (MPM) represents the most common malignant pleural tumour. Thoracoscopy represents the gold standard for diagnosis, although conditions hampering such diagnostic approach often coexist. The Objective was to determine whether ultrasound-guided percutaneous needle biopsy (US-PPNB) has a high diagnostic accuracy and represents a safe option for diagnosis of MPM. Methods: US-PPNB of pleural lesions suspected for MPM in patients admitted from January 2021 to June 2023 have been retrospectively analyzed. An 18-gauge semi-automatic spring-loaded biopsy system (Medax Velox 2®) was used by experienced pneumologists. The obtained specimens were histologically evaluated and defined as adequate or non-adequate for diagnosis according to whether the material was considered appropriate or not for immunohistochemistry (IHC) analysis. The primary objective of the study was the diagnostic yield for a tissue diagnosis. Results: US-PPNB was diagnostic of MPM in 15 out of 18 patients (sensitivity: 83.39%; specificity: 100%; PPV: 100%). Three patients with non-adequate US-PPNB underwent thoracoscopy for diagnosis. We found significant differences in terms of mean pleural lesion thickness between patients with adequate and not-adequate biopsy (15.4 mm (SD: 9.19 mm) and 3.77 mm (SD: 0.60 mm), p < 0.0010. In addition, a significant positive correlation has been observed between diagnostic accuracy and FDG-PET avidity value. Conclusions: US-PPNB performed by a pneumologist represents a valid procedure with a high diagnostic yield and accuracy for the diagnosis of MPM, and may be considered as an alternative option in patients who are not suitable for thoracoscopy.

Lung Ultrasound and Pleural Artifacts: A Pictorial Review

Lung ultrasound is a well-established diagnostic approach used in detecting pathological changes near the pleura of the lung. At the acoustic boundary of the lung surface, it is necessary to differentiate between the primary visualization of pleural parenchymal pathologies and the appearance of secondary artifacts when sound waves enter the lung or are reflected at the visceral pleura. The aims of this pictorial essay are to demonstrate the sonographic patterns of various pleural interface artifacts and to illustrate the limitations and pitfalls of the use of ultrasound findings in diagnosing any underlying pathology.

Predicting survival for patients with mesothelioma: development of the PLACE prognostic model

INTRODUCTION

The overall survival of patients with mesothelioma is poor and heterogeneous. At present, the prediction model for Chinese patients needs to be improved. We sought to investigate predictors of survival in malignant pleural mesothelioma and develop prognostic prediction models.

METHODS

This Two-center retrospective cohort study recruited patients with pathologically diagnosed mesothelioma at Beijing Chao-Yang Hospital and Beijing Tong-Ren Hospital. We developed a new prognostic prediction model based on COX multivariable analysis using data from patients who were recruited from June 1, 2010 to July 1, 2021 in Beijing Chao-Yang Hospital (n = 95, development cohort) and validated this model using data from patients recruited from July 18, 2014 to May 9, 2022 in Beijing Tong-Ren Hospital (n = 23, validation cohort). Receiver operating characteristic analysis was used to estimate model accuracy.

RESULTS

The parameters in this new model included PLT > 289.5(10^9/L) (1 point), Lymphocyte > 1.785(10^9/L) (-1point), Age > 73 years old (1 point), Calcium > 2.145(mmol/L) (-1point), Eastern Cooperative Oncology Group performance status (ECOG PS) > 2 (2 points). When the sum of scores < 0, it is recognized as a low-risk group; when the score is 0 ~ 3, it is recognized as a high-risk group. The survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (hazard ratio [HR], 3.878; 95% confidence interval [CI], 2.226-6.755; P < 0.001). The validation group had similar results (HR,3.574; 95%CI,1.064-12.001; P = 0.039). Furthermore, the areas under the curve 6 months after diagnosis in the two cohorts were 0.900 (95% CI: 0.839-0.962) and 0.761 (95% CI: 0.568-0.954) for development and validation cohorts, respectively.

CONCLUSION

We developed a simple, clinically relevant prognostic prediction model for PLACE by evaluating five variables routinely tested at the time of diagnosis. The predictive model can differentiate patients of Chinese ethnicity into different risk groups and further guide prognosis.