For diagnosis of liver masses, fine-needle aspiration versus needle core biopsy: which is better?

Characterization of the Breast Cancer Liver Metastasis Microenvironment via Machine Learning Analysis of the Primary Tumor Microenvironment

Breast cancer liver metastases (BCLM) are hypovascular lesions that resist intravenously administered therapies and have grim prognosis. Immunotherapeutic strategies targeting BCLM critically depend on the tumor microenvironment (TME), including tumor-associated macrophages. However, a priori characterization of the BCLM TME to optimize therapy is challenging because BCLM tissue is rarely collected. In contrast to primary breast tumors for which tissue is usually obtained and histologic analysis performed, biopsies or resections of BCLM are generally discouraged due to potential complications. This study tested the novel hypothesis that BCLM TME characteristics could be inferred from the primary tumor tissue. Matched primary and metastatic human breast cancer samples were analyzed by imaging mass cytometry, identifying 20 shared marker clusters denoting macrophages (CD68, CD163, and CD206), monocytes (CD14), immune response (CD56, CD4, and CD8a), programmed cell death protein 1, PD-L1, tumor tissue (Ki-67 and phosphorylated ERK), cell adhesion (E-cadherin), hypoxia (hypoxia-inducible factor-1α), vascularity (CD31), and extracellular matrix (alpha smooth muscle actin, collagen, and matrix metalloproteinase 9). A machine learning workflow was implemented and trained on primary tumor clusters to classify each metastatic cluster density as being either above or below median values. The proposed approach achieved robust classification of BCLM marker data from matched primary tumor samples (AUROC ≥ 0.75, 95% confidence interval ≥ 0.7, on the validation subsets). Top clusters for prediction included CD68+, E-cad+, CD8a+PD1+, CD206+, and CD163+MMP9+. We conclude that the proposed workflow using primary breast tumor marker data offers the potential to predict BCLM TME characteristics, with the longer term goal to inform personalized immunotherapeutic strategies targeting BCLM.

SIGNIFICANCE

BCLM tissue characterization to optimize immunotherapy is difficult because biopsies or resections are rarely performed. This study shows that a machine learning approach offers the potential to infer BCLM characteristics from the primary tumor tissue.

Up-to-Date Role of Liver Imaging Reporting and Data System in Hepatocellular Carcinoma

This article overviews Liver Imaging Reporting and Data System (LI-RADS), a system that standardizes techniques, interpretation and reporting of imaging studies done for hepatocellular carcinoma surveillance, diagnosis, and locoregional treatment response assessment. LI-RADS includes 4 algorithms, each of which defines ordinal categories reflecting probability of the assessed outcome. The categories, in turn, guide patient management. The LI-RADS diagnostic algorithms provide diagnostic criteria for the entire spectrum of lesions found in at-risk patients. In addition, the use of LI-RADS in clinical care improves clarity of communication between radiologists and clinicians and may improve the performance of inexperienced users to the levels of expert liver imagers.

Standardizing liver imaging reporting and interpretation: LI-RADS and beyond

Imaging plays a crucial role in diagnosis and post-treatment monitoring of primary liver cancers. Clear, consistent, and actionable communication of imaging results is crucial to avoid miscommunication and potential detrimental impact on patient care. In this review, we discuss the importance, advantages, and potential impact of universal adoption of standardized terminology and interpretive criteria for liver imaging, from the point of view of radiologists and clinicians.

Comparison of fine-needle cytologic diagnosis between the left and right liver lobes of dogs and cats with diffuse liver disease

Background and Aim:

Ultrasound-guided fine-needle sample collection for cytology with manual restraint is frequently used for the primary assessment of diffuse liver disease in veterinary patients in Thailand. For better diagnosis, repeated collection of samples ensures the collection of adequate, representative samples, which increase diagnostic accuracy. However, in those that are unable to receive general anesthesia, it is difficult to collect the samples from several liver locations in manually restrained dogs and cats. The study aimed to compare the cytologic diagnosis of the ultrasound-guided fine-needle non-aspiration technique between the left and right liver lobes in dogs and cats with neoplastic and non-neoplastic diffuse liver disease.

Materials and Methods:

This prospective study included 25 client-owned dogs and cats with diffuse liver diseases. Two liver samples were randomly collected from the left and right liver lobes under ultrasound guidance for cytologic examination. All slides were subsequently examined blindly by experienced pathologists for cytologic analysis with cytologic agreement scores (CASs).

Results:

Among all 50 samples obtained from ultrasound-guided fine-needle sample collection of the left and right liver, 78% were diagnostic and 22% were non-diagnostic. In the diagnostic group, 73.3% of fine-needle samples had concordant results between the left and right liver, which exhibited 100% cytologic agreement in lymphoma and 63.6% in non-neoplastic groups. Samples collected from the left liver had slightly higher CAS and higher cytologic quality than had those from the right liver lobe (p=0.053).

Conclusion:

The location and number of sample collections did not have a significant difference in the cytologic diagnosis of diffuse liver disease, especially in patients with lymphoma. For manually restrained patients, one time ultrasound-guided non-aspiration cytology procedure from the left liver lobe not only decreased restraint duration and minimized tissue trauma but also allowed for an adequate cytologic diagnosis in diffuse liver disease compared to multiple collections.

Image-guided Percutaneous Biopsy of the Liver

Percutaneous Biopsy of the Liver (PBL) is a cornerstone in the diagnosis of parenchymal liver disease and focal hepatic lesions. The indications for PBL can broadly be divided into those used to garner information regarding diagnosis, prognosis, or treatment. While the diagnosis of many common liver diseases can usually be made with imaging and serologic testing alone, PBL may be indicated in situations where the diagnosis is in question. Furthermore, liver biopsies are a foundational element for personalized treatment approaches for cancer patients; increasing emphasis is being placed on acquiring sufficient tissue for molecular profiling. While a variety of image guidance and procedural techniques have been applied to PBL, following conventional principles can ensure technical success and minimize complication risks. In this technique article, we review the practical periprocedural considerations of PBL with emphasis on recent advancements and societal recommendations.

Direct comparison of biopsy techniques for hepatic malignancies

Background/Aims

The core needle biopsy (CNB), fine needle aspiration cytology (FNAC) and touch imprint cytology (TIC) are commonly used tools for the diagnosis of hepatic malignancies. However, little is known about the benefits and criteria for selecting appropriate technique among them in clinical practice. We aimed to compare the sensitivity of ultrasound-guided CNB, FNAC, TIC as well as combinations for the diagnosis of hepatic malignancies, and to determine the factors associated with better sensitivity in each technique.

Methods

From January 2018 to December 2019, a total of 634 consecutive patients who received ultrasound-guided liver biopsies at the National Taiwan University Hospital was collected, of whom 235 with confirmed malignant hepatic lesions receiving CNB, FNAC and TIC simultaneously were enrolled for analysis. The clinical and procedural data were compared.

Results

The sensitivity of CNB, FNAC and TIC for the diagnosis of malignant hepatic lesions were 93.6%, 71.9%, and 85.1%, respectively. Add-on use of FNAC or TIC to CNB provided additional sensitivity of 2.1% and 0.4%, respectively. FNAC exhibited a significantly higher diagnostic rate in the metastatic cancers (P=0.011), hyperechoic lesions on ultrasound (P=0.028), and those with depth less than 4.5 cm from the site of needle insertion (P=0.036).

Conclusions

The sensitivity of CNB is superior to that of FNAC and TIC for the diagnosis of hepatic malignancies. Nevertheless, for shallow (depth <4.5 cm) and hyperechoic lesions not typical for primary liver cancers, FNAC alone provides excellent sensitivity.

Application of decision tree-based ensemble learning in the classification of breast cancer

As a common screening and diagnostic tool, Fine Needle Aspiration Biopsy (FNAB) of the suspicious breast lumps can be used to distinguish between malignant and benign breast cytology. In this study, we first review published works on the classification of breast cancer where the machine learning and data mining algorithms have been applied by using the Wisconsin Breast Cancer Database (WBCD). This work then introduces useful new tools, based on Random Forest (RF) and Extremely Randomized Trees or Extra Trees (ET) algorithms to classify breast cancer. The RF and ET strategies use the decision trees as proper classifiers to attain the ultimate classification. The RF and ET approaches include four main stages: input identification, determination of the optimal number of trees, voting analysis, and final decision. The models implemented in this research consider important factors such as uniformity of cell size, bland chromatin, mitoses, and clump thickness as the input parameters. According to the statistical analysis, the proposed methods are able to classify the type of breast cancer accurately. The error analysis results reveal that the designed RF and ET models offer easy-to-use outcomes and the highest diagnostic performance, compared to previous tools/models in the literature for the WBCD classification. The highest and lowest magnitudes of relative importance are attributed to the uniformity of cell size and mitoses among the factors. It is expected that the RF and ET algorithms play an important role in medicine and health systems for screening and diagnosis in the near future.

An update on touch preparations of small biopsies

Touch preparations (TPs) are being increasingly utilized in the era of personalized medicine. They fill a gap in cytopathology practice by providing a method to perform rapid onsite evaluation of small tissue samples such as core needle biopsies. However, there is a paucity of literature about how best to perform and interpret a TP. A high-quality TP can provide excellent diagnostic accuracy and good concordance with core needle biopsy histopathology findings. Although many of the cytomorphologic features of TPs overlap with fine needle aspirate smears, TP cytology is unique and differs from conventional smears in many aspects. It is important for cytologists to recognize these features, as well as potential pitfalls and artifacts in order to avoid misinterpretation. Core depletion of tumor cells is a notable drawback if TPs are performed too aggressively. TP slides are also valuable for ancillary testing because they often contain a cellular and pure population of whole tumor cells. This paper reviews all of the aspects of TPs including their clinical utility, proper slide preparation techniques, distinctive cytomorphologic characteristics, limitations, and potential pitfalls.

Precision pathology analysis of the development and progression of hepatocellular carcinoma: Implication for precision diagnosis of hepatocellular carcinoma

Outcomes for patients with hepatocellular carcinoma (HCC) remain poor because the condition is often unresponsive to the available treatments. Consequently, the early and precise diagnosis of HCC is crucial to achieve improvements in prognosis. For patients with chronic liver disease, the assessment of liver fibrosis is also important to ascertain both the staging of fibrosis and the risk of HCC occurrence. Early HCC was first described in 1991 in Japan and was defined internationally in 2009. As the concept of early HCC spread, the multistage hepatocarcinogenesis process became accepted. Consequently, improvements in imaging technology made the early diagnosis of HCC possible. At present, the most appropriate therapeutic strategy for HCC is determined using an integrated staging system that assesses the tumor burden, the degree of liver dysfunction and the patient performance status; however, pathological and molecular features are not taken into account. The recent introduction of several new therapeutic agents will change the treatment strategy for HCC. Against this background, HCC subclassification based on tumor cellular and microenvironmental characteristics will become increasingly important. In this review, we give an overview of how pathological analysis contributes to understanding the development and progression of HCC and establishing a precision diagnosis of HCC.

A randomised controlled comparison of aspiration and non-aspiration fine-needle techniques for obtaining ultrasound-guided cytological samples from canine livers

Ultrasound-guided fine-needle sampling to obtain cytological samples is a well-established technique. However, the application of suction during sampling is controversial. Evidence from the human literature and one previous veterinary study suggest that non-aspiration may be superior for a number of organs. This prospective study compared the quality and diagnostic value of cytological samples from canine livers obtained by fine-needle aspiration (FNA) and non-aspiration (FN-NA) techniques. A total of 119 dogs that required ultrasound-guided FNA of the liver as part of their clinical investigation were recruited and randomly assigned to either FNA (n=54) or FN-NA (n=65) sampling groups. Specimens were reviewed by external cytopathologists masked to the technique used. Cytological reports were reviewed for their overall diagnostic value, cellularity, cell preservation and haemodilution. Overall, 88.2% (95% confidence intervals [CI], 82.4-94.0) of samples were diagnostic. There was a significant difference, as demonstrated by Chi-squared statistical analysis, in the prevalence of diagnostic samples between the FNA (81.5%; 95% CI, 71.1-91.8) and FN-NA groups (93.9%; 95% CI, 88.0-99.7; P=0.037). Non-diagnostic samples were significantly associated with lower cellularity, poorer cell preservation and more severe haemodilution (P<0.001 for each). However, there were no significant differences in the frequency of these specific variables between the FNA and FN-NA groups. In this study, fine-needle non-aspiration was superior to an aspiration technique for sampling the canine liver, as it resulted in higher rates of diagnostic cytology samples, with greater cellularity, less haemodilution and better cytological preservation.