Detection Of Lymph Node Metastases Research Articles

Artificial Intelligence Helps Pathologists Increase Diagnostic Accuracy and Efficiency in the Detection of Breast Cancer Lymph Node Metastases.

The detection of lymph node metastases is essential for breast cancer staging, although it is a tedious and time-consuming task where the sensitivity of pathologists is suboptimal. Artificial intelligence (AI) can help pathologists detect lymph node metastases, which could help alleviate workload issues. We studied how pathologists' performance varied when aided by AI. An AI algorithm was trained using more than 32 000 breast sentinel lymph node whole slide images (WSIs) matched with their corresponding pathology reports from more than 8000 patients. The algorithm highlighted areas suspicious of harboring metastasis. Three pathologists were asked to review a dataset comprising 167 breast sentinel lymph node WSIs, of which 69 harbored cancer metastases of different sizes, enriched for challenging cases. Ninety-eight slides were benign. The pathologists read the dataset twice, both digitally, with and without AI assistance, randomized for slide and reading orders to reduce bias, separated by a 3-week washout period. Their slide-level diagnosis was recorded, and they were timed during their reads. The average reading time per slide was 129 seconds during the unassisted phase versus 58 seconds during the AI-assisted phase, resulting in an overall efficiency gain of 55% (P<0.001). These efficiency gains are applied to both benign and malignant WSIs. Two of the 3 reading pathologists experienced significant sensitivity improvements, from 74.5% to 93.5% (P≤0.006). This study highlights that AI can help pathologists shorten their reading times by more than half and also improve their metastasis detection rate.

Comparison of diagnostic value of quantitative parameters from FAPI and FDG PET/CT in the detection of mediastinal lymph node metastasis in non-small cell lung cancer

Comparison of diagnostic value of quantitative parameters from FAPI and FDG PET/CT in the detection of mediastinal lymph node metastasis in non-small cell lung cancer

68Ga]Ga-FAPI-46 PET/CT for penile cancer - a feasibility study.

Penile cancer is a rare entity and has a good prognosis in localized stage. Delayed surgical treatment of lymphatic disease is associated with poor overall survival but conventional imaging cannot detect occult lymph node metastasis sufficiently. Imaging cancer related fibroblasts has shown promising results as non-invasive staging tool in various tumor entities but has not yet been evaluated in penile cancer. In this single-center pilot study, patients planned for surgical treatment for penile cancer underwent preoperatively [68Ga]Ga-FAPI-46 PET/CT. Post-operative histopathology was compared to [68Ga]Ga-FAPI-46 PET/CT results. From January 2022 to June 2022, a total number 11 patients with histopathologically proven penile cancer underwent surgery and received [68Ga]Ga-FAPI-46 PET/CT prior therapy. 8 primary tumor sites and 4 lymph node regions were analyzed. FAPI uptake was increased on primary tumor site (SUVmax 16.2 (9.1 - 25.8)). Histopathological proven lymph node regions showed highly increased FAPI uptakes (SUVmax 17.9 (16.4 - 23.5) on [68Ga]Ga-FAPI-46 PET/CT. In this first pilot cohort, there were no false-positive FAPI uptake which might allow the detection of occult lymph node metastasis by [68Ga]Ga-FAPI-46 PET/CT and might consequently lead to omitting lymph node regions during surgery that had no increased FAPI uptake pre-operatively.

Abstract IA022: AI in bladder cancer pathology and research: What can we expect and what not?

Abstract Artificial intelligence (AI) applications are rapidly evolving, disruptive technologies that recently attracted tremendous public awareness including euphoria, bull runs at stock exchanges but also criticism and skepticism. Pathology, a crucial clinical diagnostic discipline, faces significant challenges despite its critical role and broad scope. A notable issue is the declining interest among medical graduates in pursuing further training in Surgical Pathology and Molecular Pathology. This disinterest is compounded by a trend towards part-time work and the aging demographic in Western industrial nations, which increases the demand for precise cancer diagnoses, molecular pathology and advanced oncological treatments. As the need for skilled pathologists grows, the availability of these professionals is steadily decreasing. Furthermore, political policies in heavily regulated healthcare systems (e.g., Germany) are exacerbating the shortage by limiting residency and specialist training positions despite the growing need. Adding to the reluctance among medical graduates to consider pathology as discipline is the looming “threat”” of replacing the field with Artificial Intelligence (AI) technologies. However, historical precedents suggest that necessity often spurs significant innovation. AI's role in pathology is expanding, reshaping the field with new technological advancements. AI, broadly encompassing various computational algorithms designed to perform tasks typically requiring human intelligence such as learning, reasoning, and pattern recognition, is now being applied extensively across different domains including medical diagnostics. Recent implementations in pathology include AI-driven algorithms that automate processes such as the Gleason grading of prostate biopsies, lymph node metastasis detection, detection of molecular bladder cancer subtypes or grading of kidney cancer showing high accuracy levels, speed and reproducibility in delivering results. These tools, while they do not replace pathologists, significantly reduce their workload by automating routine tasks, thus freeing up time for more complex diagnostic activities or simply dealing with the increasing workload. Despite the exciting possibilities, the use of AI in predicting molecular alterations, such as FGFR3 mutations in bladder cancer, faces limitations due to insufficient sensitivity and specificity, indicating that such technologies are not yet suitable for screening purposes. In conclusion, AI is increasingly vital in addressing the challenges of modern pathology, particularly in compensating for the shortage of pathologists. As technology advances, its integration into clinical practice offers promising solutions to enhance diagnostic accuracy and efficiency in uropathology, paving the way for more personalized and effective patient care. Citation Format: Markus Eckstein. AI in bladder cancer pathology and research: What can we expect and what not? [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA022.

Clinically Applicable Pan-Origin Cancer Detection for Lymph Nodes via AI-Based Pathology.

Lymph node metastasis is one of the most common ways of tumour metastasis. The presence or absence of lymph node involvement influences the cancer's stage, therapy, and prognosis. The integration of artificial intelligence systems in the histopathological diagnosis of lymph nodes after surgery is urgent. Here, we propose a pan-origin lymph node cancer metastasis detection system. The system is trained by over 700 whole slide images and is composed of two deep learning models to locate the lymph nodes and detect cancers. It achieved a area under the receiver operating characteristic (ROC) curve (AUC) of 0.958, with a 95.2% sensitivity and 72.2% specificity, on 1,402 whole-slide images (WSIs) from 49 organs at the National Cancer Center, China. Moreover, we demonstrated that the system could perform robustly with 1,051 WSIs from 52 organs from another medical center, with a AUC of 0.925. Our research represents a step forward in a pan-origin lymph node metastasis detection system, providing accurate pathological guidance by reducing the probability of missed diagnosis in routine clinical practice.

Abstract PS05-03: MagSense® HER2, a Molecularly Targeted Magnetic Resonance Imaging Agent for the Detection of Axillary Nodal Metastasis in Subjects with Human Epidermal Growth Factor Receptor 2 Positive (HER2+) Breast Cancer

Abstract Background Precise nodal staging is critical in guiding systemic and regional treatments including surgery in the management of breast cancer. Regional nodal assessment includes axillary imaging (mostly by ultrasound) and lymph node sampling. Since imaging findings suggestive of nodal metastasis are based on size and morphologic changes and not specific to tumor type, pathologic confirmation through either biopsy or removal of sentinel lymph node (SLN) remains the gold standard. Imagion is developing the MagSense® HER2 Imaging Agent (MSH2IA), an anti-human epidermal growth factor receptor 2 (HER2) conjugated with iron oxide nanoparticles, for the detection of nodal metastasis in HER2+ breast cancer patients. MSH2IA is currently being investigated in a first-in-human phase 1 study (ACTRN12621000126819) in HER2+ breast cancer patients who are diagnosed to have suspicious nodes by conventional imaging. Methods The key objectives of the phase 1 study are safety and tolerability of MSH2IA and confirmation that MSH2IA drains to the axillary lymph nodes. The study also explores MSH2IA’s ability to detect metastatic nodes when used with magnetic resonance imaging (MRI), with tumor status assessed by standard tissue histopathology. All eligible subjects receive a 22.5 mg (iron equivalent) subareolar or peritumoral injection of MSH2IA. MRI of the axilla are obtained before and 24 to 72 hours after MSH2IA injection. Core biopsy or dissection of a node suspicious by ultrasound is obtained for histopathology assessments. After completing the first cohort of 6 subjects, the protocol was amended to include the insertion of an MRI compatible clip in a node suspicious by ultrasound to localize the suspicious node for core biopsy and postdose MRI scan. Review of MRI scans and histopathology are performed in respective central laboratories. Results Thirteen participants with HER2+ breast cancer have completed the study. MSH2IA appears safe and well tolerated. The imaging agent, as administered, is detectable by MRI and pathology, confirming that MSH2IA drains to the lymph nodes via the chosen route of administration. In postdose MRI scans, study central radiologists reported distinct and differentiable MRI appearance in morphologically normal and suspicious nodes. The presence of a distinct postdose MR image appearance was confirmed by a group of independent radiologists in a separate blinded review. While normal nodes appeared with homogeneous hypointensity, morphologically suspicious nodes showed partial irregular darkening and/or speckled heterogeneous hypointensity. In evaluable subjects, histopathology of the core biopsies obtained from the clipped nodes confirmed the presence of HER2+ nodal metastasis, providing preliminary evidence for node-level concordance between MRI vs pathology observations. Safety, imaging, and pathology results from all available subjects will be presented. This phase 1 study in Australia will be closing enrollment by July 31, 2023. A phase 2 study in the United States and elsewhere is being planned with the objectives of optimizing dose, schedule, and imaging parameters for best diagnostic performance for clinical utility. Conclusion Available data from the ongoing phase 1 study show that MSH2IA appears safe and drains to the axillary lymph nodes. MSH2IA displays a distinct and differentiable MRI appearance in nodes morphologically highly suspicious for tumor, which is confirmed to be HER2+ metastasis by histopathology by node level concordance. This data provides preliminary proof of principle for the mechanism of molecularly targeted MR imaging and suggests that MSH2IA has the potential to provide tumor-specific MR imaging not currently available in conventional axillary imaging. Citation Format: Jane Fox, Shanta Velaiutham, Natalie Yang, Eddie lau, Kowsi Murugappan, Beena Kumar, Alex Laslowski, Koushik Govindarajan, Steven Reich, Stephen Thomas, Nitika Neha, Marie Zhang, Isaac Bright. MagSense® HER2, a Molecularly Targeted Magnetic Resonance Imaging Agent for the Detection of Axillary Nodal Metastasis in Subjects with Human Epidermal Growth Factor Receptor 2 Positive (HER2+) Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-03.

Abstract PO4-27-10: A Systematic Review and Meta-analysis of Diagnostic Performance of Fluorescein Guided Sentinel Lymph Node Biopsy in Early Breast Cancer

Abstract Background: Evaluation of axillary lymph nodes status in cN0 axilla is performed by sentinel lymph node biopsy (SLNB) utilizing a combination of radioactive isotope and blue dye. There is a paucity of radioactive tracer in many countries of transitional economies. Hence, alternatives to isotope have been explored, viz. indocyanine green (ICG), superparamagnetic iron oxide nanoparticles and Fluorescein Sodium (FS). This systematic review and meta-analysis, evaluates the diagnostic performance of Fluorescein Sodium guided SLNB. Objectives: The objective was to evaluate the diagnostic performance of Fluorescein Sodium for sentinel lymph node biopsy in early breast cancer. Methods: PRISMA 2020 guidelines were followed for this meta-analysis. Eligibility criteria: Studies where SLNB was performed using Fluorescein Sodium for breast carcinoma. Information sources: PubMed, EMBASE, Cochrane library and online clinical trial registers Risk of bias: Articles were assessed for risk of bias using the QUADAS-2 tool. Synthesis of results: The main summary measures were pooled detection rate and pooled false negative rate using random effects model. In order to describe heterogeneity, we constructed summary receiver operating characteristic (SROC) curves with 95% prediction regions, estimated using bivariate meta-analysis with a test level random effect only, and forest plots. Calculations were performed using the Meta-Disc v1.4 program (available from https://metadisc.software.informer.com/1.4/). Results: Out of 45 studies found on initial systematic search, 7 studies were found eligible and were included in the meta-analysis based on data on 332 patients. The pooled detection rate was 93.2% (95% confidence interval [CI] 87% to 97%).). The heterogeneity (I2 value) of the pooled detection rate was 71%. Five validation studies were included for pooling the false negative rate (FNR) and included a total of 211 patients. The pooled FNR was 5.6% (95% CI; 2.9 to 9.07). Five validation studies were included for sensitivity, specificity, diagnostic odds ratio, LR+ and LR- meta-analysis. With regards to the identification of SLN the pooled sensitivity was 80% [(95% CI, 68% to 89%); I2=79.8]; specificity was 98% [(95% CI, 95% to 100%); I2=0.0]. The likelihood ratio for a positive test LR+ was 23.2 [(95% CI, 5.91 to 95.18); I2=0.0] and likelihood ratio for a negative test a LR- of 0.41 [(95% CI, 0.16 to 1.05); I2=88.1]. The diagnostic Odds ratio OR was 76.94 (95% CI, 15.88 to 372.79). Diagnostic accuracy as measured by SROC was 99.08%. Q index was 0.96. Publication bias for pooled detection rate as per Egger’s test was -2.2 (p= 0.66) and for FNR was 1.85 (p=0.29). Visual inspection of summary ROC curve and of forest plots did not show significant heterogeneity. Conclusion: Fluorescein guided SLNB is an affordable option for detection of lymph node metastases in cN0 patients with early breast cancer. It achieves a high detection rate of 93% with a false negative rate of 5.6% for the detection of axillary lymph node metastasis. We recommend larger multinational trials to confirm its high detection rate with low false negativity. Citation Format: Sanjay Kumar Yadav, Bharath S, Sarada Khadka, Dhananjaya Sharma, Chandan Kumar Jha, Gaurav Agarwal, Manju Singh, Anurag Srivastava, Amit Goyal. A Systematic Review and Meta-analysis of Diagnostic Performance of Fluorescein Guided Sentinel Lymph Node Biopsy in Early Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-27-10.

Preoperative assessment of lymph nodal metastases with [68Ga]Ga-DOTATOC PET radiomics for improved surgical planning in well-differentiated pancreatic neuroendocrine tumours.

Accurate identification of lymph node (LN) metastases is pivotal for surgical planning of pancreatic neuroendocrine tumours (PanNETs); however, current imaging techniques have sub-optimal diagnostic sensitivity. Aim of this study is to investigate whether [68Ga]Ga-DOTATOC PET radiomics might improve the identification of LN metastases in patients with non-functioning PanNET (NF-PanNET) referred to surgical intervention. Seventy-two patients who performed preoperative [68Ga]Ga-DOTATOC PET between December 2017 and March 2022 for NF-PanNET. [68Ga]Ga-DOTATOC PET qualitative assessment of LN metastases was measured using diagnostic balanced accuracy (bACC), sensitivity (SN), specificity (SP), positive and negative predictive values (PPV, NPV). SUVmax, SUVmean, Somatostatin receptor density (SRD), total lesion SRD (TLSRD) and IBSI-compliant radiomic features (RFs) were obtained from the primary tumours. To predict LN involvement, these parameters were engineered, selected and used to train different machine learning models. Models were validated using tenfold repeated cross-validation and control models were developed. Models' bACC, SN, SP, PPV and NPV were collected and compared (Kruskal-Wallis, Mann-Whitney). LN metastases were detected in 29/72 patients at histology. [68Ga]Ga-DOTATOC PET qualitative examination of LN involvement provided bACC = 60%, SN = 24%, SP = 95%, PPV = 78% and NPV = 65%. The best-performing radiomic model provided a bACC = 70%, SN = 77%, SP = 61%, PPV = 60% and NPV = 83% (outperforming the control model, p < 0.05*). In this study, [68Ga]Ga-DOTATOC PET radiomics allowed to increase diagnostic sensitivity in detecting LN metastases from 24 to 77% in NF-PanNET patients candidate to surgery. Especially in case of micrometastatic involvement, this approach might assist clinicians in a better patients' stratification.

A systematic review and meta-analysis of diagnostic performance of fluorescein-guided sentinel lymph node biopsy in early breast cancer.

Evaluation of axillary lymph nodes status in cN0 axilla is performed by sentinel lymph node biopsy (SLNB) utilizing a combination of radioactive isotope and blue dye or alternative to isotope like Indocyanine green (ICG). Both are very resource-intensive; which has prompted development of low-cost technique of Fluorescein Sodium (FS)-guided SLNB. This systematic review and meta-analysis evaluate the diagnostic performance of FS-guided SLNB in early breast cancer. The objective was to evaluate the diagnostic performance of FS for sentinel lymph node biopsy. Eligibility criteria: Studies where SLNB was performed using FS. PubMed, EMBASE, Cochrane library and online clinical trial registers. Risk of bias: Articles were assessed for risk of bias using the QUADAS-2 tool. The main summary measures were pooled Sentinel Lymph Node Identification Rate (SLN-IR) and pooled False Negative Rate (FNR) using random-effects model. A total of 45 articles were retrieved by the initial systematic search. 7 out of the 45 studies comprising a total of 332 patients were included in the meta-analysis. The pooled SLN-IR was 93.2% (95% confidence interval [CI], 0.87-0.97; 87% to 97%). Five validation studies were included for pooling the false negative rate and included a total of 211 patients. The pooled FNR was 5.6% (95% confidence interval [CI], 2.9-9.07). Fluorescein-guided SLNB is a viable option for detection of lymph node metastases in clinically node negative patients with early breast cancer. It achieves a high pooled Sentinel Lymph Node Identification Rate (SLN-IR) of 93% with a false negative rate of 5.6% for the detection of axillary lymph node metastasis.

Fast-Track Development and Multi-institutional Clinical Validation of an Artificial Intelligence Algorithm for Detection of Lymph Node Metastasis in Colorectal Cancer

Lymph node metastasis (LNM) detection can be automated using artificial intelligence (AI)-based diagnostic tools. Only limited studies have addressed this task for colorectal cancer (CRC). This study aimed to develop of a clinical-grade digital pathology tool for LNM detection in CRC using the original fast-track framework.The training cohort included 432 slides from one department. A segmentation algorithm detecting 8 relevant tissue classes was trained. The test cohorts consisted of materials from 5 pathology departments digitized by 4 different scanning systems.A high-quality, large training data set was generated within 7 days and a minimal amount of annotation work using fast-track principles. The AI tool showed very high accuracy for LNM detection in all cohorts, with sensitivity, negative predictive value, and specificity ranges of 0.980 to 1.000, 0.997 to 1.000, and 0.913 to 0.990, correspondingly. Only 5 of 14,460 analyzed test slides with tumor cells over all cohorts were classified as false negative (3/5 representing clusters of tumor cells in lymphatic vessels).A clinical-grade tool was trained in a short time using fast-track development principles and validated using the largest international, multi-institutional, multiscanner cohort of cases to date, showing very high precision for LNM detection in CRC. We are releasing a part of the test data sets to facilitate academic research.

Head-to-head comparison of the diagnostic performance between 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in colorectal cancer: a systematic review and meta-analysis.

This study aimed to compare the detection rates of 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in colorectal cancer. A systematic search of major medical databases was conducted to identify studies up to September 2023. The primary outcome assessed was the detection rate of 68Ga-FAPI-04 PET/CT and 18F-FDG PET/CT in the primary tumor. Pooled risk ratios with a 95% CI were calculated using random-effect models to adjust for heterogeneity. Eight studies were included in the meta-analysis. 68Ga-FAPI-04 PET/CT has higher uptakes in lymph nodes, bone, and peritoneal metastasis compared with 18F-FDG PET/CT. The detection rate of 68Ga-FAPI-04 PET/CT based on lesion was better for lymph node metastasis (RR = 0.63, 95% CI 0.47-0.84, P = 0.002) and peritoneal metastasis (RR = 0.52, 95% CI 0.32-0.85, P = 0.009), both imaging modalities had essentially the same diagnostic efficacy in primary tumor (RR = 0.99, 95% CI 0.96-1.02, P = 0.49). 68Ga-FAPI-04 as a highly promising PET/CT tracer was superior to 18F-FDG PET/CT in colorectal cancer, especially in detecting lymph node metastases and peritoneal metastases.

Establishment and validation of a risk score model based on EUS: assessment of lymph node metastasis in early gastric cancer

Lymph node metastasis significantly affects the prognosis of early gastric cancer patients. Endoscopic ultrasonography (EUS) plays a crucial role in the preoperative assessment of early gastric cancer. This study evaluated the efficacy of EUS in identifying lymph node metastasis in early gastric cancer patients and developed a risk score model to aid in choosing the best treatment options. We retrospectively analyzed the effectiveness of EUS for detecting lymph node metastasis in early gastric cancer patients. A risk score model for predicting lymph node metastasis preoperatively was created using independent risk factors identified through binary logistic regression analysis and subsequently validated. Receiver operating characteristic (ROC) curves were generated for both the development and validation cohorts. The overall accuracy of EUS in identifying lymph node metastasis was 85.3%, although its sensitivity (29.2%) and positive predictive value (38.7%) were relatively low. Patients were categorized based on preoperative risk factors for lymph node metastasis, including tumor size ≥20 mm, lymph nodes ≥10 mm, BMI ≥24 kg/m2, and lymph node metastasis on CT scans. A 7-point risk score model was developed to assess the likelihood of lymph node metastasis. The areas under the ROC curve (AUCs) for the development and validation sets were 0.842 and 0.837, respectively, with sensitivities of 64% and 79%, respectively. We developed a practical risk score model based on preoperative factors to help EUS predict lymph node metastasis in early gastric cancer patients, guiding the selection of optimal treatment approaches for these patients.

Microcomputed tomography as a diagnostic tool for detection of lymph node metastasis in non-small cell lung cancer: A decision-support approach for pathological examination “A pilot study for method validation”

BackgroundNon-small cell lung cancer (NSCLC) patients without lymph node (LN) metastases (pN0) may exhibit different survival rates, even when their T stage is similar. This divergence could be attributed to the current pathology practice, wherein LNs are examined solely in two-dimensional (2D). Unfortunately, adhering to the protocols of 2D pathological examination does not ensure the exhaustive sampling of all excised LNs, thereby leaving room for undetected metastatic foci in the unexplored depths of tissues. The employment of micro-computed tomography (micro-CT) facilitates a three-dimensional (3D) evaluation of all LNs without compromising sample integrity. In our study, we utilized quantitative micro-CT parameters to appraise the metastatic status of formalin-fixed paraffin-embedded (FFPE) LNs. MethodsMicro-CT scans were conducted on 12 FFPEs obtained from 8 NSCLC patients with histologically confirmed mediastinal LN metastases. Simultaneously, whole-slide images from these FFPEs underwent scanning, and 47 regions of interest (ROIs) (17 metastatic foci, 11 normal lymphoid tissues, 10 adipose tissues, and 9 anthracofibrosis) were marked on scanned images. Quantitative structural variables obtained via micro-CT analysis from tumoral and non-tumoral ROIs, were analyzed. ResultSignificant distinctions were observed in linear density, connectivity, connectivity density, and closed porosity between tumoral and non-tumoral ROIs, as indicated by kappa coefficients of 1, 0.90, 1, and 1, respectively. Receiver operating characteristic analysis substantiated the differentiation between tumoral and non-tumoral ROIs based on thickness, linear density, connectivity, connectivity density, and the percentage of closed porosity. ConclusionsQuantitative micro-CT parameters demonstrate the ability to distinguish between tumoral and non-tumoral regions of LNs in FFPEs. The discriminatory characteristics of these quantitative micro-CT parameters imply their potential usefulness in developing an artificial intelligence algorithm specifically designed for the 3D identification of LN metastases while preserving the FFPE tissue.

Incidence of sentinel lymph node metastases in apparent early-stage endometrial cancer: a multicenter observational study

ObjectiveUltrastaging is accurate in detecting nodal metastases, but increases costs and may not be necessary in certain low-risk subgroups. In this study we examined the risk of nodal involvement detected...

Role of ultrasound in detection of lymph nodes metastasis in gynecological cancers: systematic review and meta-analysis.

To assess the diagnostic performance of transvaginal ultrasound (TVUS) for preoperative evaluation of lymph node metastasis in gynecological cancers. A systematic review and meta-analysis was performed. All studies published between January 1990 to May 2023 evaluating the role of ultrasound for detecting lymph node metastasis (index test) in gynecological cancers, using histopathological analysis, as reference standard were included. Quality was assessed using QUADAS-2. Pooled sensitivity, specificity and diagnostic odds ratio of TVUS were estimated. The search identified 2638 citations. Eight studies comprising 967 women were included. The mean prevalence of pelvic lymph nodes metastasis was 24.2%, [14%-65.6%]. The risk of bias was low for most domains assessed. Overall pooled sensitivity, specificity and diagnostic odds ratio of TVUS were 41% (95% confidence interval [CI] =26%-58%), 98% (95%CI=93%-99%) and 32 (95%CI=14-72), respectively. Heterogeneity in TVUS evaluation was high between studies, both for sensitivity and specificity. No publication bias was found (p=0.46). TVUS showed a high-pooled specificity for the detection of pelvic lymph node metastasis in gynecological cancers. However, pooled sensitivity was low. This article is protected by copyright. All rights reserved.

68Ga-FAPI-04 PET/CT in Non-Small Cell Lung Cancer: Accurate Evaluation of Lymph Node Metastasis and Correlation with Fibroblast Activation Protein Expression.

Fibroblast activation protein (FAP) is a promising diagnostic and therapeutic target in various solid tumors. This study aimed to assess the diagnostic efficiency of 68Ga-labeled FAP inhibitor (FAPI)-04 PET/CT for detecting lymph node metastasis in non-small cell lung cancer (NSCLC) and to investigate the correlation between tumor 68Ga-FAPI-04 uptake and FAP expression. Methods: We retrospectively enrolled 136 participants with suspected or biopsy-confirmed NSCLC who underwent 68Ga-FAPI-04 PET/CT for initial staging. The diagnostic performance of 68Ga-FAPI-04 for the detection of NSCLC was evaluated. The final histopathology or typical imaging features were used as the reference standard. The SUVmax and SUVmean, 68Ga-FAPI-avid tumor volume (FTV), and total lesion FAP expression (TLF) were measured and calculated. FAP immunostaining of tissue specimens was performed. The correlation between 68Ga-FAPI-04 uptake and FAP expression was assessed using the Spearman correlation coefficient. Results: Ninety-one participants (median age, 65 y [interquartile range, 58-70 y]; 69 men) with NSCLC were finally analyzed. In lesion-based analysis, the diagnostic sensitivity and positive predictive value of 68Ga-FAPI-04 PET/CT for detection of the primary tumor were 96.70% (88/91) and 100% (88/88), respectively. In station-based analysis, the diagnostic sensitivity, specificity, and accuracy for the detection of lymph node metastasis were 72.00% (18/25), 93.10% (108/116), and 89.36% (126/141), respectively. Tumor 68Ga-FAPI-04 uptake (SUVmax, SUVmean, FTV, and TLF) correlated positively with FAP expression (r = 0.470, 0.477, 0.582, and 0.608, respectively; all P ≤ 0.001). The volume parameters FTV and TLF correlated strongly with FAP expression in 31 surgical specimens (r = 0.700 and 0.770, respectively; both P < 0.001). Conclusion: 68Ga-FAPI-04 PET/CT had excellent diagnostic efficiency for detecting lymph node metastasis, and 68Ga-FAPI-04 uptake showed a close association with FAP expression in participants with NSCLC.

Papillary thyroid carcinoma: ≤ 10mm does not always mean pN0. A multicentric real-world study.

The incidence of papillary thyroid carcinoma (PTC) is increasing and PTC ≤ 10mm (PTMC) accounts for most new diagnoses. PTMCs are not always low risk, as detection of lymph nodes metastasis (LNM) may occur. The purpose of the study was to analyze the clinical pattern, frequency, and independent risk factors of patients with PTMC and LNM. From January 2022 to June 2023, PTCs managed at CTO Hospital, Rome; Policlinico Vanvitelli, Naples; and Garibaldi Nesima Hospital, Catania were included. PTC management followed the same diagnostic-therapeutic procedures according to the ATA guidelines. Variables such as age, sex, maximum diameter, histologic evidence of LNM (HELNM +), Hashimoto's thyroiditis (HT), multifocality, capsule invasion, and histological subtype were considered. PTCs were divided according to HELNM and size. Two hundred ninety-eight PTCs were included. PTMCs were 136 (45.6%) and LNM occurred in 27.2% of them. In the HELNM + group, analysis of PTMC vs 'MacroPTC' (PTC > 10mm) did not show any statistical difference. Multivariate regression revealed that young age (OR 0.93; CI 95% 0.90-0.96; p < 0.01) and male sex (male OR 3.44; CI 95% 1.16-10.20; p = 0.03) were the only independent risk factors for HELNM + in PTMC. The risk of LNM in PTMC is not negligible; therefore, a careful evaluation by an expert thyroidologist is mandatory for patients with small thyroid nodule, especially in younger and male patients before excluding surgery. In the future, new tools are needed to detect early PTMC with LNM before surgery.

Head-to-head comparison of 18F-FDG PET/CT and 18F-FDG PET/MRI for lymph node metastasis staging in non-small cell lung cancer: a meta-analysis.

The current meta-analysis aimed to compare the diagnostic performance of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) with 18F-FDG PET/magnetic resonance imaging (MRI) in non-small cell lung cancer (NSCLC) lymph node metastasis staging. We searched the PubMed, Web of Science, and Embase databases for relevant articles between November 1992 and September 2022. Studies evaluating the head-to-head comparison of 18F-FDG PET/CT and 18F-FDG PET/MRI for lymph node metastasis in patients with NSCLC were included. The quality of each study was assessed using the Quality Assessment of Diagnostic Performance Studies-2 tool. The analysis includes six studies with a total of 434 patients. The pooled sensitivity of 18F-FDG PET/CT and 18F-FDG PET/MRI was 0.78 [95% confidence interval (CI): 0.59-0.90] and 0.84 (95% CI: 0.68-0.93), and the pooled specificity was 0.87 (95% CI: 0.72-0.94) and 0.87 (95% CI: 0.80-0.92), respectively. The accuracy of 18F-FDG PET/CT and 18F-FDG PET/MRI was 0.81 (95% CI: 0.71-0.90) and 0.84 (95% CI: 0.75-0.92), respectively. When the pre-test probability was set at 50%, the post-test probability for 18F-FDG PET/CT could increase to 85%, and the post-test probability for 18F-FDG PET/MRI could increase to 87%. 18F-FDG PET/CT and 18F-FDG PET/MRI have similar diagnostic performance in detecting lymph node metastasis in NSCLC. However, the results of this study were from a small sample study, and further studies with larger sample sizes are needed.

A comparison study of 68gallium-prostate-specific membrane antigen positron emission tomography-computed tomography and multiparametric magnetic resonance imaging for locoregional staging of prostate cancer.

Prostate cancer (PCa) is the most common malignancy in men aged 50 years and older and the second cause of cancer death among men. Accurate staging of PCa preoperatively is of high importance for treatment decisions and patient management. Conventional imaging modalities (ultrasound, computed tomography [CT], and magnetic resonance imaging) are inaccurate for the staging of PCa. Newer modality multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scan show promising results for the staging of PCa. Only fewer studies are available for comparison of these modalities with histopathology as reference. The objective of our study is to evaluate the diagnostic accuracy of independent 68gallium PSMA (68Ga-PSMA) PET-CT compared with mpMRI for preoperative staging of PCa, using histopathology as the reference standard. From August 2021 to December 2022, 30 patients of biopsy-proven PCa were prospectively enrolled as per eligibility criteria. Preoperatively, 68Ga-PSMA PET scan and mpMRI were done in all the patients. Extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node metastasis (LNM) were investigated separately. Subsequently, the patients underwent robotic-assisted radical prostatectomy with bilateral pelvic lymph node dissection. mpMRI prostate was more sensitive (66.66%) but less specific than PSMA PET-CT (55.55%) for ECE. mpMRI and PSMA PET-CT both had similar sensitivity (83.3%) and specificity (87.5%) for SVI. PSMA PET-CT was more sensitive (85.71%) and specific (95.6%) than mpMRI prostate (62.5% and 91.30%, respectively) for LNM. PSMA PET-CT is more specific for the detection of ECE and more sensitive and specific for the detection of LNM than mpMRI, and similar for the detection of SVI. mpMRI provides only local staging, while PSMA PET-CT provides information about local, regional, and distal staging. Overall, PSMA PET-CT is superior to mpMRI for locoregional staging of PCa.

Analysis of biopsy pathology and risk factors of lymph node metastasis in prostate cancer.

To explore the relationship between biopsy pathology and lymph node metastasis in patients with prostate cancer (PCa), and to identify risk factors of lymph node metastasis (LNM). Patients diagnosed with prostate cancer were respective screened between Jan 2015 and May 2022. Patients diagnosed PCa via 13-core ultrasound-guided biopsies and underwent radical prostatectomy and lymph node dissection were identified. The clinicopathological characteristics of the patients were recorded. Relationships between LNM and non-LNM were analyzed using chi-square and independent samples t-test. Logistic regression model was fitted to analyze the risk factors of lymph node metastases. Two hundreds and fifteen patients were included, sixty-seven patients had lymph node metastasis. Gleason scores in LNM group were higher than that in non-LNM group (8.5 ± 0.9 VS 7.5 ± 1.5, p < 0.001), positive biopsy in non-LNM group was significantly lower than that in LNM group (p < 0.001), Binary logistic regression analysis indicated number of positive biopsy and number of removed lymph nodes increased the risks of LNM (odds ratio, OR = 1.28, 95% confidence interval, CI = 1.16-1.42, p < 0.001; OR = 1.11, 95% CI = 1.06-1.17, p < 0.001; respectively). Number of positive biopsy in internal gland but not external gland was significant associated with LNM (OR = 1.66, 95% CI = 1.34-2.06, p < 0.001; OR = 1.19, 95% CI = 0.88-1.61, p = 0.262; respectively). The patients with lymph nodes dissection more than 13 were about four times more likely to detect lymph node metastasis than those fewer than 13 (OR = 3.92, 95% CI = 2.10-7.33, p < 0.001). The risk of lymph node metastasis increased with the number of positive prostate biopsy cores, and tumors in the internal gland were more likely to cause lymph node metastasis. In addition, lymph node metastasis was more likely to be found when the number of lymph nodes dissection was greater than 13.