Ancillary Tool Research Articles

MSH6-proficient crypt foci in MSH6 constitutional mismatch repair deficiency: reversion of a frameshifted coding microsatellite to its wild-type sequence.

The discovery of "mismatch repair deficient (MMRd)-crypt foci" in non-neoplastic intestinal mucosa in Lynch syndrome (LS) has significantly enhanced our understanding of how tumors and tumor immunity form and evolve in LS. In this study, we report the frequent presence of "mismatch repair proficient (MMRp)-crypt foci" in both non-neoplastic and neoplastic intestinal mucosa in a patient with constitutional MMR deficiency (CMMRD), who carried a germline MSH6 pathogenic variant (c.3261dupC) in trans with an MSH6 likely pathogenic variant (c.3724_3726del) and whose tissues were otherwise deficient in MMR globally. The MMRp-crypts occurred at a rate of 1.1/100 crypts in non-neoplastic intestinal mucosa and were readily discernible in adenomas > 1cm. Sequencing analysis revealed normalization of the MSH6c.3261dupC variant in MMRp-adenoma crypts, indicating reverse frameshifting of the exon 5 C8 microsatellite. Interestingly but not surprisingly, the MMRp-adenoma crypts remained microsatellite-instability-high (MSI-H), and shared oncogenic APC mutations with the background MMRd-adenoma. Contrasting with MSH6-CMMRD, no PMS2-CMMRD individuals (0/5) harbored MMRp-crypts. In conclusion, our study documents distinct MMRp-crypts in MSH6-CMMRD, a phenomenon in keeping with MSH6 being a frequent target of MSI-H due to its coding microsatellite and suggesting that MSH6-CMMRD can potentially serve as a unique model system to further our understanding of MSH6's role in MSI-H tumor formation and evolution. Our findings also bear diagnostic implications; when using MMR immunohistochemistry as an ancillary tool in detecting CMMRD, awareness of these MMRp crypts can help avoid diagnostic pitfalls.

Immunohistochemistry and RT-PCR as ancillary tools in the diagnosis of acquired oral syphilis.

To investigate Treponema pallidum detection using immunohistochemistry (IHC) and reverse transcription-polymerase chain reaction (RT-PCR) assays in acquired oral syphilis (AOS). Thirty-seven paraffin-embedded tissue specimens of AOS (32 secondary and five primary) were analyzed, integrating double-positive serological results with clinicodemographic and histopathological data. T. pallidum presence was semiquantitatively assessed by IHC, while RT-PCR targeted T. pallidum DNA. Sensitivity, specificity, and the area under the curve (AUC) were calculated with 95% confidence intervals (CI). The study included mostly females (62.2%) with a mean age of 27.1 years. T. pallidum was detected in all samples by IHC, predominantly in the epithelium across all layers (43.2%). RT-PCR identified T. pallidum DNA in 32 cases, with negative results observed in cases of secondary AOS. The AUC for IHC versus disease stage was 62.5% (95% CI: 45.1-77.8), and for RT-PCR, it was 57.8% (95% CI: 40.5-73.8). The AUC comparing IHC to RT-PCR was 83.8% (95% CI: 67.9-93.8). This study represents the first attempt to evaluate the proposed direct detection algorithm for AOS. IHC and RT-PCR serve as ancillary tools for detecting T. pallidum in both primary and secondary stages of AOS.

The potential and pitfalls of using a large language model such as ChatGPT, GPT-4, or LLaMA as a clinical assistant.

This study aims to evaluate the utility of large language models (LLMs) in healthcare, focusing on their applications in enhancing patient care through improved diagnostic, decision-making processes, and as ancillary tools for healthcare professionals. We evaluated ChatGPT, GPT-4, and LLaMA in identifying patients with specific diseases using gold-labeled Electronic Health Records (EHRs) from the MIMIC-III database, covering three prevalent diseases-Chronic Obstructive Pulmonary Disease (COPD), Chronic Kidney Disease (CKD)-along with the rare condition, Primary Biliary Cirrhosis (PBC), and the hard-to-diagnose condition Cancer Cachexia. In patient identification, GPT-4 had near similar or better performance compared to the corresponding disease-specific Machine Learning models (F1-score ≥ 85%) on COPD, CKD, and PBC. GPT-4 excelled in the PBC use case, achieving a 4.23% higher F1-score compared to disease-specific "Traditional Machine Learning" models. ChatGPT and LLaMA3 demonstrated lower performance than GPT-4 across all diseases and almost all metrics. Few-shot prompts also help ChatGPT, GPT-4, and LLaMA3 achieve higher precision and specificity but lower sensitivity and Negative Predictive Value. The study highlights the potential and limitations of LLMs in healthcare. Issues with errors, explanatory limitations and ethical concerns like data privacy and model transparency suggest that these models would be supplementary tools in clinical settings. Future studies should improve training datasets and model designs for LLMs to gain better utility in healthcare. The study shows that LLMs have the potential to assist clinicians for tasks such as patient identification but false positives and false negatives must be mitigated before LLMs are adequate for real-world clinical assistance.

Performance evaluation of the Alinity m system for quantifying cytomegalovirus DNA in samples of the respiratory, gastrointestinal, and urinary tract.

Quantitation of cytomegalovirus (CMV) DNA load in specimens other than blood such as bronchoalveolar lavages, intestinal biopsies, or urine has become a common practice as an ancillary tool for the diagnosis of CMV pneumonitis, intestinal disease, or congenital infection, respectively. Nevertheless, most commercially available CMV PCR platforms have not been validated for CMV DNA detection in these specimen types. In this study, a laboratory-developed test based on Alinity m CMV ("Alinity LDT") was evaluated. Reproducibility assessment using spiked bronchial aspirate (BAS) or urine samples showed low standard deviations of 0.08 and 0.27 Log IU/mL, respectively. Evaluating the clinical performance of Alinity LDT in comparison to a laboratory-developed test based on RealTime CMV ("RealTime LDT") showed good concordance across 200 clinical specimens including respiratory specimens, intestinal biopsies, urine, and stool. A high Pearson's correlation coefficient of r = 0.92, a low mean bias of -0.12 Log IU/mL, a good qualitative agreement of 90%, and a Cohen's kappa value of 0.76 (substantial agreement) were observed. In separate analyses of the sample types BAS, tracheal aspirates, bronchoalveolar lavage, biopsies, and urine, the assay results correlated well between the two platforms with r values between 0.88 and 0.99 and a bias <0.5 Log IU/mL. Overall, the fully automated, continuous, random access Alinity LDT yielded good reproducibility, high concordance, and good correlation to RealTime LDT in respiratory, gastrointestinal, and urine samples and may enhance patient management with rapid result reporting.IMPORTANCEIn transplant recipients, a major cause for morbidity and mortality is end-organ disease by primary or secondary CMV infection of the respiratory or gastrointestinal tract. In addition, sensorineural hearing loss and neurodevelopmental abnormalities are frequent sequelae of congenital CMV infections in newborns. Standard of care for highly sensitive detection and quantitation of the CMV DNA load in plasma and whole blood specimens is real-time PCR testing. Beyond that, there is a need for quantitative determination of CMV DNA levels in respiratory, gastrointestinal, and urinary tract specimens using a highly automated, random access CMV PCR assay with a short turnaround time to enable early diagnosis and treatment. In the present study, clinical performance of the fully automated Alinity m analyzer in comparison to the current RealTime LDT assay was evaluated in eight different off-label sample types.

P53 immunohistochemistry as an ancillary tool for rapid assessment of residual disease in TP53-mutated acute myeloid leukemia and myelodysplastic syndromes.

Measurable residual disease flow cytometry (MRD-FC) and molecular studies are the most sensitive methods for detecting residual malignant populations after therapy for TP53-mutated acute myeloid leukemia and myelodysplastic neoplasms (TP53+ AML/MDS). However, their sensitivity is limited in suboptimal aspirates or when the immunophenotype of the neoplastic blasts overlaps with erythroids or normal maturing myeloid cells. In this study, we set out to determine if p53 immunohistochemistry (IHC) correlates with MRD-FC and next-generation sequencing (NGS) in the posttherapy setting and to determine the utility of p53 IHC to detect residual disease in the setting of negative or equivocal MRD-FC. We retrospectively identified 28 pre- and posttherapy bone marrow biopsy specimens from 9 patients with TP53+ AML/MDS and a p53 overexpressor phenotype by IHC (strong 3+ staining at initial diagnosis). Next-generation sequencing and/or MRD-FC results were collected for each specimen. Using a threshold of more than ten 2-3+ cells in any one 400× field, p53 IHC detected residual disease with a sensitivity of 94% and a specificity of 89%. The threshold used in this study showed a high degree of concordance among 6 blinded pathologists (Fleiss κ = 0.97). Our study suggests that p53 IHC can be used as a rapid tool (within 24 hours) to aid in the detection of residual disease that may complement MRD-FC or NGS in cases in which the flow cytometry immunophenotype is equivocal and/or the bone marrow aspirate is suboptimal.

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning.

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we developed a deep-learning method for tumor origin differentiation using cytological histology (TORCH) that can identify malignancy and predict tumor origin in both hydrothorax and ascites. We examined its performance on three internal (n = 12,799) and two external (n = 14,538) testing sets. In both internal and external testing sets, TORCH achieved area under the receiver operating curve values ranging from 0.953 to 0.991 for cancer diagnosis and 0.953 to 0.979 for tumor origin localization. TORCH accurately predicted primary tumor origins, with a top-1 accuracy of 82.6% and top-3 accuracy of 98.9%. Compared with results derived from pathologists, TORCH showed better prediction efficacy (1.677 versus 1.265, P < 0.001), enhancing junior pathologists' diagnostic scores significantly (1.326 versus 1.101, P < 0.001). Patients with CUP whose initial treatment protocol was concordant with TORCH-predicted origins had better overall survival than those who were administrated discordant treatment (27 versus 17 months, P = 0.006). Our study underscores the potential of TORCH as a valuable ancillary tool in clinical practice, although further validation in randomized trials is warranted.

The Impact of Next-generation Sequencing on Interobserver Agreement and Diagnostic Accuracy of Desmoplastic Melanocytic Neoplasms.

Next-generation sequencing (NGS) is increasingly being utilized as an ancillary tool for diagnostically challenging melanocytic neoplasms. It is incumbent upon the pathology community to perform studies assessing the benefits and limitations of these tools in specific diagnostic scenarios. One of the most challenging diagnostic scenarios faced by skin pathologists involves accurate diagnosis of desmoplastic melanocytic neoplasms (DMNs). In this study, 20 expert melanoma pathologists rendered a diagnosis on 47 DMNs based on hematoxylin and eosin sections with demographic information. After submitting their diagnosis, the experts were given the same cases, but this time with comprehensive genomic sequencing results, and asked to render a diagnosis again. Identification of desmoplastic melanoma (DM) improved by 7%, and this difference was statistically significant ( P <0.05). In addition, among the 15 melanoma cases, in the pregenomic assessment, only 12 were favored to be DM by the experts, while after genomics, this improved to 14 of the cases being favored to be DM. In fact, some cases resulting in metastatic disease had a substantial increase in the number of experts recognizing them as DM after genomics. The impact of the genomic findings was less dramatic among benign and intermediate-grade desmoplastic tumors (BIDTs). Interobserver agreement also improved, with the Fleiss multirater Kappa being 0.36 before genomics to 0.4 after genomics. NGS has the potential to improve diagnostic accuracy in the assessment of desmoplastic melanocytic tumors. The degree of improvement will be most substantial among pathologists with some background and experience in bioinformatics and melanoma genetics.

Detection of contraband drugs in forensic-correctional mental health services using TeknoScan-a gas chromatography tool

Substance misuse is a major problem among individuals involved in forensic-correctional mental health services. Urine drug screening detects substance use and deters the entry of contraband into forensic-correctional units, albeit with limitations. For example, a point-of-care urine sample may not be possible and patients can alter or substitute samples to avoid detection, highlighting the role of ancillary tools to detect contraband substances. This study describes the pattern and types of substances detected from environmental samples using a gas chromatographic analyzer (TeknoScan TSI3000) in forensic-correctional populations to model the benefits of similar tools in similar settings. Samples collected over 18 months (January 2020 to June 2021) by trained staff members using the machine were reviewed. During this period, 217 environmental samples were recorded, and 66 (30%) samples were positive for contraband substances, including tetrahydrocannabinol (25%), methamphetamines (19%), and cocaine (16%). Other substances detected include methylene-dioxymethamphetamine, heroin, morphine, lysergic acid diethylamide, tramadol, and methyl-benzoate. Fewer positive samples were detected, especially during the time corresponding with the COVID-19 restriction on the forensic units. TeknoScan was beneficial as an ancillary tool to detect and deter contraband substances. It also provided evidence for risk management. Adequate training is needed for the successful implementation of the tool.

Diagnostic value of vietnamese smell identification test in Parkinson's disease

IntroductionThe Vietnamese Smell Identification Test (VSIT) has been validated in determining olfactory dysfunction in the Vietnamese population; however, its value in diagnosing Parkinson's disease (PD) has not been established. MethodsThis case-control study was conducted at University Medical Center HCMC, Ho Chi Minh City, Vietnam. The study sample included non-demented PD patients and healthy controls (HC) who were gender- and age-matched. All participants were evaluated for odor identification ability using the VSIT and the Brief Smell Identification Test (BSIT). ResultsA total of 218 HCs and 218 PD patients participated in the study. The median VSIT and BSIT scores were significantly different between PD and HC groups (VSIT, 5 (3) vs. 9 (2), P < 0.0001; BSIT, 6 (3) vs 8 (2), P < 0.0001). Using the cut-off of <8 for correct answers out of 12 odorants, the VSIT had higher sensitivity (84.4%) and specificity (86.2%) than those of the BSIT (sensitivity of 81.7% and specificity of 69.3%) for the diagnosis of PD. The area under the curve (AUC) value was greater for the VSIT than for the BSIT (0.909 vs 0.818). The smell identification scores were not significantly correlated with disease duration, disease severity, or LEDD (all p > 0.05). ConclusionThe VSIT can be a valuable ancillary tool for supporting the diagnosis of PD in Vietnam. Olfactory dysfunction in PD was unrelated to the disease duration and severity. The VSIT can be applied to improve the accuracy of clinical PD diagnosis.

Differentiating electrocardiographic indications of massive and submassive pulmonary embolism: A cross-sectional study in Southern Iran from 2015 to 2020.

Although using electrocardiogram (ECG) for pulmonary embolism (PE) risk stratification has shown mixed results, it is currently used as supplementary evidence in risk stratification. This cross-sectional study aimed to assess and compare ECG findings of massive and submassive PE versus segmental PE. This cross-sectional study included 250 hospitalized patients with a confirmed diagnosis of acute PE from 2015 to 2020 in Southern Iran. Demographic variables, clinical data, troponin levels, on-admission ECG findings, echocardiography findings, and ECG findings 24 h after receiving anticoagulants or thrombolytics were extracted. Patients diagnosed with submassive or massive PE exhibited significantly higher rates of right axis deviation (p = .010), abnormal ST segment (p < .0001), S1Q3T3 pattern (p < .0001), inverted T wave in leads V1-V3 (p < .0001), inverted T wave in leads V4-V6 (p < .0001), and inverted T wave in leads V1-V6 (p < .0001). In a multivariable model, inverted T wave in leads V1-V3, inverted T wave in leads V4-V6, pulse rate, and positive troponin test were the statistically independent variables for predicting submassive or massive PE. Furthermore, inverted T wave in leads V1-V3 (sensitivity: 85%, specificity: 95%, accuracy: 93%, AUC: 0.902) and troponin levels (sensitivity: 72%, specificity: 86%, accuracy: 83%, AUC: 0.792) demonstrated the best diagnostic test performance for discriminating submassive or massive PE from segmental PE. In addition to clinical rules, ECG can serve as an ancillary tool for assessing more invasive testing and earlier aggressive treatments among patients with PE, as it can provide valuable information for the diagnosis and risk stratification of submassive or massive PE.

Ukraine and the Debacle of Russian Soft Power

ABSTRACT The war in Ukraine has demonstrated Russia’s incapacity to implement a foreign policy strategy without resorting to hard power means, exposing the limits in its soft power capacity to ‘attract’ and ‘persuade’. Specifically, Russian soft power in Ukraine built around the model of the ‘Russian world’ (Russkiy Mir) was unable to persuade Kyiv to align with Moscow through peaceable means. Simultaneously, EU-inspired soft power based on the idea of ‘Greater Europe’ and Ukrainian ‘Europeanness’ conceived through the normative prism of liberal-democratic values and the potential of higher levels of economic development, limited the impact of Russia’s soft power in Ukraine. Russian soft power in Ukraine was not inspired by the idea of attraction but conceived as a propagandistic means to justify expansionist policies, merging de facto with hard power. After the 2022 invasion, in the occupied regions, Moscow’s influence could only be imposed coercively as an ancillary tool of hard power through a unique combination of smart and sharp power. Overall, a comparison of the influence of Russian and EU soft power in Ukraine highlights that the latter proved to be generally more persuasive, leading Moscow to resort to military force.

Probability Calculation for Utilization of Photovoltaic Energy in Electric Vehicle Charging Stations

In recent years, there has been a growing emphasis on the efficient utilization of natural resources across various facets of life. One such area of focus is transportation, particularly electric mobility in conjunction with the deployment of renewable energy sources. To fully realize this objective, it is crucial to quantify the probability of achieving the desired state—production exceeding consumption. This article deals with the computation of the probability that the energy required to charge an electric vehicle will originate from a renewable source at a specific time and for a predetermined charging duration. The base of the model lies in artificial neural networks, which serve as an ancillary tool for the actual probability assessment. Neural networks are used to forecast the values of energy production and consumption. Following the processing of these data, the probability of energy availability for a given day and month is determined. A total of seven scenarios are calculated, representing individual days of the week. These findings can help users in their decision-making process regarding when and for how long to connect their electric vehicle to a charging station to receive assured clean energy from a local photovoltaic source.

Interpretable machine learning model for prediction of overall survival in laryngeal cancer

Background: The mortality rates of laryngeal squamous cell carcinoma cancer (LSCC) have not significantly decreased in the last decades. Objectives: We primarily aimed to compare the predictive performance of DeepTables with the state-of-the-art machine learning (ML) algorithms (Voting ensemble, Stack ensemble, and XGBoost) to stratify patients with LSCC into chance of overall survival (OS). In addition, we complemented the developed model by providing interpretability using both global and local model-agnostic techniques. Methods: A total of 2792 patients in the Surveillance, Epidemiology, and End Results (SEER) database diagnosed with LSCC were reviewed. The global model-agnostic interpretability was examined using SHapley Additive exPlanations (SHAP) technique. Likewise, individual interpretation of the prediction was made using Local Interpretable Model Agnostic Explanations (LIME). Results: The state-of-the-art ML ensemble algorithms outperformed DeepTables. Specifically, the examined ensemble algorithms showed comparable weighted area under receiving curve of 76.9, 76.8, and 76.1 with an accuracy of 71.2%, 70.2%, and 71.8%, respectively. The global methods of interpretability (SHAP) demonstrated that the age of the patient at diagnosis, N-stage, T-stage, tumor grade, and marital status are among the prominent parameters. Conclusions: A ML model for OS prediction may serve as an ancillary tool for treatment planning of LSCC patients.

Glycoprotein Nonmetastatic Melanoma Protein B (GPNMB) Immunohistochemistry Can Be a Useful Ancillary Tool to Identify Perivascular Epithelioid Cell Tumor

Perivascular epithelioid cell tumors (PEComas) are rare mesenchymal tumors that express smooth muscle and melanocytic makers. Diagnosis of PEComas can be challenging due to focal or lost expression of traditional immunohistochemical markers, limited availability of molecular testing, and morphological overlap with much more common smooth muscle tumors. This study evaluates the use of glycoprotein nonmetastatic melanoma protein B (GPNMB) immunohistochemical staining as a surrogate marker for TSC1/2/MTOR alteration or TFE3 rearrangement to differentiate PEComas from other mesenchymal tumors. Cathepsin K was also assessed for comparison. A total of 399 tumors, including PEComas, alveolar soft part sarcomas, and other histologic PEComa mimics, were analyzed using GPNMB and cathepsin K immunohistochemistry. GPNMB expression was seen in all PEComas and alveolar soft part sarcomas with the majority showing diffuse and moderate-to-strong labeling, whereas other sarcomas were negative or showed focal labeling. When a cutoff of diffuse and at least moderate staining was used, GPNMB demonstrated 95% sensitivity and 97% specificity in distinguishing PEComas from leiomyosarcoma, well-differentiated/dedifferentiated liposarcomas, and undifferentiated pleomorphic sarcomas. Cathepsin K with a cutoff of any labeling had lower sensitivity (78%) and similar specificity (94%) to GPNMB. This study highlights GPNMB as a highly sensitive marker for PEComas and suggests its potential use as an ancillary tool within a panel of markers for accurate classification of these tumors.

DNA content and clinicopathological features aid in distinguishing ameloblastic carcinoma from ameloblastoma.

Ameloblastoma and ameloblastic carcinoma are epithelial odontogenic tumors that can be morphologically similar. In the present study, we evaluated the DNA content and Ki-67 index in the two tumors. The paraffin blocks of the tumors were selected to obtain sections for the immunohistochemical reactions and preparation of the cell suspension for acquisition in a flow cytometer. The Random Forest package of the R software was used to verify the contribution of each variable to classify lesions into ameloblastoma or ameloblastic carcinoma. Thirty-two ameloblastoma and five ameloblastic carcinoma were included in the study. In our sample, we did not find statistically significant differences in Ki-67 labeling rates. A higher fraction of cells in 2c (G1) was correlated with the diagnosis of ameloblastoma, whereas higher rates of 5c-exceeding rate (5cER) were correlated with ameloblastic carcinoma. The Random Forest model highlighted histopathological findings and parameters of DNA ploidy study as important features for distinguishing ameloblastoma from ameloblastic carcinoma. Our findings suggest that the parameters of the DNA ploidy study can be ancillary tools in the classification of ameloblastoma and ameloblastic carcinoma.

Electrocardiogram Features in Non-Cardiac Diseases: From Mechanisms to Practical Aspects.

Despite the noteworthy advancements and the introduction of new technologies in diagnostic tools for cardiovascular disorders, the electrocardiogram (ECG) remains a reliable, easily accessible, and affordable tool to use. In addition to its crucial role in cardiac emergencies, ECG can be considered a very useful ancillary tool for the diagnosis of many non-cardiac diseases as well. In this narrative review, we aimed to explore the potential contributions of ECG for the diagnosis of non-cardiac diseases such as stroke, migraine, pancreatitis, Kounis syndrome, hypothermia, esophageal disorders, pulmonary embolism, pulmonary diseases, electrolyte disturbances, anemia, coronavirus disease 2019, different intoxications and pregnancy.

Correlation of uterine artery Doppler flow velocimetry and β-human chorionic gonadotropin levels during postmolar evacuation surveillance: A pilot study in a tertiary hospital

BACKGROUND: During postmolar evacuation surveillance, beta-human chorionic gonadotropin (β-hCG) regression levels can predict invasive disease while Doppler ultrasound can assess in vivo tumor neovascularization and quantify uterine blood supply. As an ancillary tool to β-hCG monitoring, ultrasound can detect the early presence of viable trophoblastic tissues and identify patients at risk of developing postmolar gestational trophoblastic Neoplasia (PMGTN). OBJECTIVE: The objective of this study was to correlate uterine artery Doppler ultrasound with β-hCG levels during pre- and postmolar evacuation surveillance among patients with complete mole. MATERIALS AND METHODS: A cohort of patients with sonographic diagnosis of complete hydatidiform mole and managed with suction curettage in the same institution were prospectively followed up after evacuation. The pre- and postmolar evacuation surveillance period was at days 1, 7, 14, 21, 28, and 35. Monitoring of serum β-hCG levels was based on the standard regression curve. For Doppler ultrasound parameters, monitoring of the systolic/diastolic (S/D) ratio, pulsatility index (PI), resistance index (RI), and peak systolic velocity (PSV) was based on its relationship with its serum β-hCG levels. The ultrasound images generated were archived and reviewed by the authors. Descriptive and inferential statistics were utilized to analyze median differences. For the correlation of uterine artery Doppler flow parameters, analysis for the test of difference used Pearson correlation and multiple linear regression analysis for the odds ratio. RESULTS: Sixteen of the 23 enrolled patients completed the protocol (16 of 23, 69.50%). A majority had spontaneous remission (13; 81%) while 3 cases (19%) presented increasing and plateauing β-hCG levels. The pre- and post evacuation median β-hCG levels showed a significant decrease (P = 0.001). As post evacuation β-hCG levels decreased, PSV also decreased (r = 0.478, P = 0.061) while Doppler parameters, RI, PI, and S/D ratio increased. However, when post evacuation β-hCG levels rose or plateaued, Doppler parameters decreased. These changes had statistical correlation (all P &lt; 0.05). Moreover, the magnitude of the relationship for β-hCG and Doppler parameters was moderate and ranged from 0.524 to 0.581. Among the Doppler parameters, the S/D ratio and RI of the right uterine artery strongly predicted a rise in β-hCG levels. The odds ratio of predicting increased β-hCG levels and risk of gestational trophoblastic neoplasia by the right S/D ratio were − 2683.67 (confidence interval [CI] = −271.692–5095.655; P = 0.034) and by the right RI − 66,193.34 (CI = −161,818.107–29,431.433; P = 0.046). Notably, Doppler parameter changes appeared early at day 14 up to day 35 and before the appearance of abnormal β-hCG regression patterns. CONCLUSION: There is a strong correlation between uterine artery Doppler flow changes and β-hCG levels during postmolar evacuation surveillance. The inverse relationship of the S/D ratio, PI and RI, and β-hCG regression patterns confirms spontaneous remission of the disease. For patients with abnormal β-hCG patterns, this relationship is altered. The Doppler changes become erratic, unpredictable, and significantly decreased. These changes were detected as early as 2 weeks post evacuation. Thus, the use of ultrasound as an adjunct to β-hCG post evacuation surveillance can predict abnormal β-hCG regression patterns and identify patients at risk of developing postmolar gestational trophoblastic neoplasia (PMGTN).

Fetal and Neonatal Autopsy in the Molecular Age: Exploring Tissue Selection for Testing Success.

While conventional autopsy is the gold-standard for determining cause of demise in the fetal and neonatal population, molecular analysis is increasingly used as an ancillary tool. Testing methods and tissue selection should be optimized to provide informative genetic results. This institutional review compares testing modalities and postmortem tissue type in 53 demises occurring between 20 weeks of gestation and 28 days of life. Testing success, defined as completion of analysis, varies by technique and may require viable cells for culture or extractable nucleic acid. Success was achieved by microarray in 29/30 tests (96.7%), karyotype in 40/54 tests (74.1%), fluorescent in situ hybridization in 5/9 tests (55.6%), and focused gene panels in 2/2 tests (100%). With respect to tissue type, postmortem prepartum amniotic fluid was analyzed to completion in 100% of tests performed; compared to 84.0%, 54.5%, and 80.8% of tests using placenta, fetal only, and mixed fetal-placental tissue collection, respectively. Sampling skin (83.3%, in cases with minimal maceration) and kidney (75.0%) were often successful, compared to lower efficacy of umbilical cord (57.1%) and liver (25.0%). Addition of genetic testing into cases with anomalous clinical and gross findings can increase the utility of the final report for family counseling and future pregnancy planning.

Learnability of Thyroid Nodule Assessment on Ultrasonography: Using a Big Data Set.

The aims of the work described here were to evaluate the learnability of thyroid nodule assessment on ultrasonography (US) using a big data set of US images and to evaluate the diagnostic utilities of artificial intelligence computer-aided diagnosis (AI-CAD) used by readers with varying experience to differentiate benign and malignant thyroid nodules. Six college freshmen independently studied the "learning set" composed of images of 13,560 thyroid nodules, and their diagnostic performance was evaluated after their daily learning sessions using the "test set" composed of images of 282 thyroid nodules. The diagnostic performance of two residents and an experienced radiologist was evaluated using the same "test set." After an initial diagnosis, all readers once again evaluated the "test set" with the assistance of AI-CAD. Diagnostic performance of almost all students increased after the learning program. Although the mean areas under the receiver operating characteristic curves (AUROCs) of residents and the experienced radiologist were significantly higher than those of students, the AUROCs of five of the six students did not differ significantly compared with that of the one resident. With the assistance of AI-CAD, sensitivity significantly increased in three students, specificity in one student, accuracy in four students and AUROC in four students. Diagnostic performance of the two residents and the experienced radiologist was better with the assistance of AI-CAD. A self-learning method using a big data set of US images has potential as an ancillary tool alongside traditional training methods. With the assistance of AI-CAD, the diagnostic performance of readers with varying experience in thyroid imaging could be further improved.

The value of cytology in diagnosis of body fluids with lymphoma involvement: a report of 29 cases

Abstract Introduction/Objective Lymphoma involving body fluids (pleural, abdominal or pericardial) can be secondary or primary (such as primary effusion lymphoma). The incident rate is variable depending on the hospital setting (general or specialty hospitals), and it is generally low. Due to the large specimen volume, relatively easy collecting sample and stable cellular preservation, body fluids are good sources for diagnosis and classification of lymphoproliferative diseases. Methods/Case Report A retrospective case search from a tertiary academic medical center during 2015 to 2023 were performed for body fluid cytology with diagnosis of lymphoma. The results of cytology, ancillary cellblock, immunohistochemistry and flow cytometry were collected, and the synchronous or follow-up surgical biopsies/resections were cross examined. Results (if a Case Study enter NA) Total 29 cases of body fluids with lymphoma involvement were identified in the study period. There were 22 patients including 9 males and 13 females and age ranged from 16 to 88 years (mean 64.5 years). Only 4 patients (4/22, 18.2%) had history of lymphoma when they presented with body fluids, and the remaining 18 patients (18/22, 81.8%) presented body fluids as the initial or synchronous sign of lymphoma. 26/29 cases had cellblock or flow cytometry done and 13/29 cases had both. All 22 cases had adequate lymphoma diagnosis and classification by combined cytology and ancillary tests and included 5 high grade B cell lymphoma, 3 diffuse large B cell lymphoma, 2 Burkitt, 2 CLL/SLL, 2 small mature B cell lymphoma, NOS, 1 mantel, 1 MYC and BCL-2 double hits lymphoma, 1 primary effusion lymphoma, 1 plasma cell myeloma, 2 T lymphoblastic lymphoma, 1 anaplastic large cell lymphoma, 1 angioimmunoblastic T cell lymphoma. 11 patients had synchronous or follow-up tissue biopsies, and cytology had 100% agreement with the histology diagnosis. Conclusion The majority (81.8%) cases of body fluid involvement with lymphomas presented as the initial or synchronous sign of lymphomas in our study series indicating that high pathologic suspicion and adequate cytomorphological skills for lymphoproliferative disorders are necessary for making the diagnosis. Body fluid samples are excellent sources for diagnosis and classification of lymphomas using the available ancillary tools including immunohistochemistry, flow cytometry and molecular testing.