Pathological Lymph Node Metastasis Research Articles

Prediction of pathological response and lymph node metastasis after neoadjuvant therapy in rectal cancer through tumor and mesorectal MRI radiomic features

Establishing predictive models for the pathological response and lymph node metastasis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT) based on MRI radiomic features derived from the tumor and mesorectal compartment (MC). This study included 209 patients with LARC who underwent rectal MRI both before and after nCRT. The patients were divided into a training set (n = 146) and a test set (n = 63). Regions of interest (ROIs) for the tumor and MC were delineated on both pre- and post-nCRT MRI images. Radiomic features were extracted, and delta radiomic features were computed. The predictive endpoints were pathological complete response (pCR), pathological good response (pGR), and lymph node metastasis (LNM). Feature selection for various models involved sequentially removing features with a correlation coefficient > 0.9, and features with P-values ≥ 0.05 in univariate analysis, followed by LASSO regression on the remaining features. Logistic regression models were developed, and their performance was evaluated using the area under the receiver operating characteristic curve (AUC). Among the 209 LARC patients, the number of patients achieving pCR, pGR, and LNM were 44, 118, and 40, respectively. The optimal model for predicting each endpoint is the combined model that incorporates pre- and delta-radiomics features for both the tumor and MC. These models exhibited superior performance with AUC values of 0.874 (for pCR), 0.801 (for pGR), and 0.826 (for LNM), outperforming the MRI tumor regression grade (mrTRG) which yielded AUC values of 0.800, 0.715, and 0.603, respectively. The results demonstrate the potential utility of the tumor and MC radiomics features, in predicting treatment efficacy among LARC patients undergoing nCRT.

Solid volume ratio in predicting pathological features of cT1 lung adenocarcinoma.

More effective methods are urgently needed for predicting the pathological grade and lymph node metastasis of cT1-stage lung adenocarcinoma. We analyzed the relationships between CT quantitative parameters (including three-dimensional parameters) and pathological grade and lymph node metastasis in cT1-stage lung adenocarcinoma patients of our center between January 2015 and December 2023. A total of 343 patients were included, of which there were 233 males and 110 females, aged 61.8 ± 9.4 (30-82) years. The area under the receiver operating characteristic (ROC) curve for predicting the pathological grade of lung adenocarcinoma using the consolidation tumor ratio (CTR) and the solid volume ratio (SVR) were 0.761 and 0.777, respectively. The areas under the ROC curves (AUCs) for predicting lymph node metastasis were 0.804 and 0.873, respectively. Multivariate logistic regression analysis suggested that the SVR is an independent predictor of highly malignant lung adenocarcinoma pathology, while the SVR and pathological grade are independent predictors of lymph node metastasis. The sensitivity of predicting the pathological grading of lung adenocarcinoma based on SVR>5% is 97.2%, with a negative predictive value of 96%. The sensitivity of predicting lymph node metastasis based on SVR>47.1% is 97.3%, and the negative predictive value is 99.5%. The SVR has greater diagnostic value than the CTR in the preoperative prediction of pathologic grade and lymph node metastasis in stage cT1-stage lung adenocarcinoma patients, and the SVR may replace the diameter and CTR as better criteria for guiding surgical implementation.

Clinical Significance of Body Weight Loss During Chemotherapy for Advanced Gastric Cancer Undergoing Conversion Surgery.

The purpose of the present study was to assess the clinical impact of body weight loss (BWL) during chemotherapy in patients with initially unresectable advanced gastric cancer who underwent conversion surgery. This retrospective study included 61 patients with stage IV gastric cancer who underwent conversion surgery after chemotherapy, and body weight changes during chemotherapy were examined. Based on receiver operating characteristic (ROC) curve analysis of body weight change for disease recurrence, the cutoff value of BWL was determined. Based on the BWL cutoff value, patients were classified into two groups. Body weight change ranged from 28.2% to -21.8%. The cut-off value of BWL was set at 6% based on the ROC analysis. Of the 61 patients, 45 (74%) and 16 (26%) had <6% and ≥6% BWL, respectively. Patients with ≥6% BWL had peritoneal dissemination, pathological lymph node metastasis, residual tumor status of R1-2, and disease recurrence compared with those with <6% BWL (all p<0.05). The median survival times after conversion surgery were 21 and 63 months in the ≥6% and <6% BWL groups, respectively (p<0.01). Univariate analysis identified BWL as an independent prognostic factor (p=0.01), although histological response alone was significantly associated with survival in the multivariate analysis (p=0.02). Patients with severe BWL during chemotherapy may be excluded from the indication of conversion surgery.

Diagnostic performance of Node-RADS score for mesorectal lymph node metastasis in rectal cancer.

To explore the diagnostic performance of the Node-RADS scoring system on preoperative assessment of mesorectal lymph node metastasis (LNM) status in rectal cancer, in comparisonwith the ESGAR category and size of lymph node (LN). Preoperative clinical and MRI data of 154 rectal adenocarcinoma patients treated with radical resection surgery were retrospectively analyzed. The differences in the clinical, pathological and imaging characteristics between the pN- and pN + groups were surveyed. The correlations of Node-RADS score and ESGAR category to pN stage, LNM number and lymph node ratio (LNR) were investigated. The performances on assessing pathological LNM were compared among individual approaches. A nomogram combined the imaging and clinicalfeatures was also established and evaluated. Significant differences in CEA, tumor maximum diameter, tumor location, LN short-axis diameter, Node-RADS score and ESGAR category were found between the pN- and pN + groups. Node-RADS correlated significantly with pN stage, LNM number, and LNR (r = 0.665, 0.685, and 0.675, p < 0.001). Node-RADS had the highest AUC (0.862) for predicting pN + status, surpassing ESGAR (AUC = 0.797, p = 0.040) and LN size (AUC = 0.762, p = 0.015). The nomogram had the best diagnostic performance (AUC = 0.901), significantly outperforming Node-RADS alone (p = 0.037). The Node-RADS scoring system is comparable to the ESGAR category and surpasses short-axis diameter in preoperatively predicting LNM in rectal cancer. Integrating imaging and clinical features will lead to an enhancement in diagnostic performance. Moreover, a clear relationship was demonstrated between the Node-RADS score and the quantity-dependent pathological characteristics of LNM.

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate the risk factors for lateral lymph node metastasis and develop machine learning models combining these risk factors to improve the diagnostic performance of standard imaging. This multicentre prospective study included patients who underwent lateral lymph node dissection without preoperative treatment for rectal cancer between 2017 and 2019 in 15 Japanese institutions. First, preoperative clinicopathological factors and magnetic resonance imaging findings were evaluated using multivariable analyses for their correlation with lateral lymph node metastasis. Next, machine learning diagnostic models for lateral lymph node metastasis were developed combining these risk factors. The models were tested in a training set and in an internal validation cohort and their diagnostic performance was tested using receiver operating characteristic curve analyses. Of 212 rectal cancers, 122 patients were selected, including 232 lateral pelvic sides, 30 sides of which had pathological lateral lymph node metastasis. Multivariable analysis revealed that poorly differentiated/mucinous adenocarcinoma, extramural vascular invasion, tumour deposit and a short-axis diameter of lateral lymph node ≥ 6.0 mm were independent risk factors for lateral lymph node metastasis. Patients were randomly divided into a training cohort (139 sides) and a test cohort (93 sides) and machine learning models were computed on the basis of a combination of significant features (including: histological type, extramural vascular invasion, tumour deposit, short- and long-axis diameter of lateral lymph node, body mass index, serum carcinoembryonic antigen level, cT, cN, cM, irregular border and mixed signal intensity). The top three models with the highest sensitivity in the training cohort were as follows: support vector machine (sensitivity, 1.000; specificity, 0.773), light gradient boosting machine (sensitivity, 0.950; specificity, 0.918) and ensemble learning (sensitivity, 0.950; specificity, 0.917). The diagnostic performances of these models in the test cohort were as follows: support vector machine (sensitivity, 0.750; specificity, 0.667), light gradient boosting machine (sensitivity, 0.500; specificity, 0.852) and ensemble learning (sensitivity, 0.667; specificity, 0.864). Machine learning models combining multiple risk factors can contribute to improving diagnostic performance of lateral lymph node metastasis.

Lymph node metastasis in early invasive lung adenocarcinoma: Prediction model establishment and validation based on genomic profiling and clinicopathologic characteristics.

The presence of lymph node (LN) metastasis directly affects the treatment strategy for lung adenocarcinoma (LUAD). Next-generation sequencing (NGS) has been widely used in patients with advanced LUAD to identify targeted genes, while early detection of pathologic LN metastasis using NGS has not been assessed. Clinicopathologic features and molecular characteristics of 224 patients from Ruijin Hospital were analyzed to detect factors associated with LN metastases. Another 140 patients from Huashan Hospital were set as a test cohort. Twenty-four out of 224 patients were found to have lymph node metastases (10.7%). Pathologic LN-positive tumors showed higher mutant allele tumor heterogeneity (p < 0.05), higher tumor mutation burden (p < 0.001), as well as more frequent KEAP1 (p = 0.001), STK11 (p = 0.004), KRAS (p = 0.007), CTNNB1 (p = 0.017), TP53, and ARID2 mutations (both p = 0.02); whereas low frequency of EGFR mutation (p = 0.005). A predictive nomogram involving male sex, solid tumor morphology, higher T stage, EGFR wild-type, and TP53, STK11, CDKN2A, KEAP1, ARID2, KRAS, SDHA, SPEN, CTNNB1, DICER1 mutations showed outstanding efficiency in both the training cohort (AUC = 0.819) and the test cohort (AUC = 0.780). This study suggests that the integration of genomic profiling and clinical features identifies early-invasive LUAD patients at higher risk of LN metastasis. Improved identification of LN metastasis is beneficial for the optimization of the patient's therapy decisions.

Investigation of mediastinal lymph node dissection in clinical stage IA pure-solid non-small cell lung cancer patients

ObjectiveTo explore the independent predictors of pathological mediastinal lymph node (pN2) metastasis in clinical stage IA (cIA) pure-solid non-small cell lung cancer (NSCLC) patients, and to find an appropriate method of mediastinal lymph node dissection.MethodsThis study retrospectively evaluated 533 cIA pure-solid NSCLC patients who underwent radical resection of lung cancer (lobectomy combined with systematic lymph node dissection) from January 2014 to December 2016. The relationship between clinicopathological characteristics and pN2 metastasis was analyzed, and the independent predictors of pN2 metastasis were determined by univariate and multivariate logistic regression analysis. We defined the new factor Y as composed of preoperative cT, CEA, and NSE.ResultsThere were 72 cases (13.5%) of pN2 metastasis in cIA pure-solid NSCLC patients. Preoperative clinical tumor diameter (cT), serum CEA level, serum NSE level, and pathological status of station 10 lymph nodes were independent predictors of pN2 metastasis. Patients with cT ≤ 21.5 mm, CEA ≤ 3.85 ng/mL, NSE ≤ 13.40 ng/mL and negative station 10 lymph node group showed lower rates of pN2 metastasis. The new factor Y was an independent predictor of pN2 metastasis. Only 3 (2.1%) of 143 patients in the Y low-risk group showed pN2 metastasis.ConclusionFor patients with low risk of pN2 metastasis, it might be feasible to take lobe-specific lymph node sampling or systematic lymph node sampling. As for those with high risk of pN2 metastasis, systematic lymph node dissection would be recommended.

Prognosis of isolated locoregional recurrence after early breast cancer with immediate breast reconstruction surgery: a retrospective multi‑institutional study.

The prognosis in patients with breast cancer with isolated locoregional recurrence (ILRR) without simultaneous distant metastases after immediate breast reconstruction (IBR) remains unknown. We aimed to investigate the prognosis in this patient population. This multi-institutional retrospective observational study evaluated 3295 patients with primary breast cancer who underwent IBR at 12 Japanese medical facilities between January 1, 2008 and December 31, 2016. The outcome measures were the prognostic factors for ILRR after IBR, 5-year distant metastasis-free interval (DMFI), and 5-year overall survival (OS). Mastectomy or skin-sparing mastectomy was performed in 3295 patients. ILRR occurred in 70 patients, and the median observation period from ILRR diagnosis was 39.3months. Of the 70 patients, 9 (12.9%) had axillary lymph node recurrence (ALNR) at the time of ILRR diagnosis. The 5-year DMFI and OS rates after ILRR were 92.4% and 91.2%, respectively. Pathological lymph node metastasis at primary surgery (P = 0.041) and ALNR (P = 0.022) at ILRR were significantly associated with DMFI in the univariate analysis. ALNR was the only independent prognostic factor in the multivariate analysis (P = 0.041). Post-mastectomy radiation therapy (PMRT; P = 0.022) and ALNR (P = 0.043) were significantly associated with OS in the univariate analysis, and both PMRT (P = 0.010) and ALNR (P = 0.028) were independent prognostic factors in the multivariate analysis for OS. Although patients with breast cancer who had ILRR after IBR have favorable prognosis, ALNR may lead to poor prognosis. To the best of our knowledge, this study is the first to report the prognosis of these patients.

Diagnostic performance of Node Reporting and Data System (Node-RADS) for assessing mesorectal lymph node in rectal cancer by CT

BackgroundTo compare the diagnostic performance of the Node-RADS scoring system and lymph node (LN) size in preoperative LN assessment for rectal cancer (RC), and to investigate whether the selection of size as the primary criterion whereas morphology as the secondary criterion for LNs can be considered the preferred method for clinical assessment.MethodsPreoperative CT data of 146 RC patients treated with radical resection surgery were retrospectively analyzed. The Node-RADS score and short-axis diameter of size-prioritized LNs and the morphology-prioritized LNs were obtained. The correlations of Node-RADS score to the pN stage, LNM number and lymph node ratio (LNR) were investigated. The performances on assessing pathological lymph node metastasis were compared between Node-RADS score and short-axis diameter. A nomogram combined the Node-RADS score and clinical features was also evaluated.ResultsNode-RADS score showed significant correlation with pN stage, LNM number and LNR (Node-RADS of size-prioritized LN: r = 0.600, 0.592, and 0.606; Node-RADS of morphology-prioritized LN: r = 0.547, 0.538, and 0.527; Node-RADSmax: r = 0.612, 0.604, and 0.610; all p < 0.001). For size-prioritized LN, Node-RADS achieved an AUC of 0.826, significantly superior to short-axis diameter (0.826 vs. 0.743, p = 0.009). For morphology-prioritized LN, Node-RADS exhibited an AUC of 0.758, slightly better than short-axis diameter (0.758 vs. 0.718, p = 0.098). The Node-RADS score of size-prioritized LN was significantly better than that of morphology-prioritized LN (0.826 vs. 0.758, p = 0.038). The nomogram achieved the best diagnostic performance (AUC = 0.861) than all the other assessment methods (p < 0.05).ConclusionsThe Node-RADS scoring system outperforms the short-axis diameter in predicting lymph node metastasis in RC. Size-prioritized LN demonstrates superior predictive efficacy compared to morphology-prioritized LN. The nomogram combined the Node-RADS score of size-prioritized LN with clinical features exhibits the best diagnostic performance. Moreover, a clear relationship was demonstrated between the Node-RADS score and the quantity-dependent pathological characteristics of LNM.

The Clinical Role of Adjuvant Chemotherapy after Sublobar Resection for Non-Small-Cell Lung Cancer ≤ 20 mm with Lymph Node Metastases: A Propensity-Matched Analysis of the National Cancer Database.

Sublobar resection is a standard surgical procedure for small-sized non-small-cell lung cancer (NSCLC). However, the clinical role of adjuvant chemotherapy for small-sized NSCLC with pathological lymph node (LN) metastasis after sublobar resection is unknown. The National Cancer Database was queried for NSCLC patients between 2004 and 2018. Eligibility included sublobar resection with pathological LN metastasis, R0 resection, Charlson comorbidity score = 0, clinical stage T1a-b, and tumor size ≤ 20 mm. The Kaplan-Meier method with a log-rank test and multivariable Cox proportional hazards analyses were used for assessing survival. The samples were evaluated before and after propensity score matching (PSM) with respect to age, sex, histologic type, and pathological LN status. Of 810 patients who met the eligibility criteria, 567 (70.0%) underwent adjuvant chemotherapy. After PSM, patients with adjuvant chemotherapy had a significantly longer survival than those without (median survival: 64.3 vs. 34.0 months, hazard ratio for death: 0.61, p < 0.0001). Multivariate analyses after PSM showed that younger age (p = 0.0206), female (p = 0.0005), and adjuvant chemotherapy (p < 0.0001) were independent prognostic factors for longer survival. Adjuvant chemotherapy has a prognostic impact in patients with small-sized NSCLC and pathological lymph node metastasis who undergo sublobar resection.

Prognosis of locoregional recurrence after early breast cancer with immediate breast reconstruction.

e12595 Background: Several studies have shown no difference in the prognosis of breast cancer patients who underwent total mastectomy (MT) with or without immediate breast reconstruction (IBR), which is now a standard surgical technique in the treatment of breast cancer. While some studies have reported a poor prognosis for locoregional recurrence (LRR) following breast cancer surgery, the prognosis of LRR without simultaneous distant metastasis after IBR is not known. We conducted a multi-facility retrospective observational study to investigate the prognosis of breast cancer patients with LRR after IBR. Methods: Of the 4,726 primary breast cancer patients for whom IBR was performed at 12 Japanese medical facilities between January 1, 2008, and December 31, 2016, MT or skin-sparing mastectomy (SSM) was performed in 3,295 patients. LRR was observed in 87 of these patients, 17 of whom had distant metastasis (n=13) or metastasis to the supraclavicular or internal mammary lymph nodes (n=4) before LRR was excluded. The measured outcomes were IBR-LRR-related prognostic factors, five-year distant metastasis-free survival (DMFS), and five-year overall survival (OS). The statistical analyses employed Kaplan–Meier curves and a Cox proportional hazards model. Results: The median observation period was 39.3 months and the median age at which IBR was performed was 44 years. There were 61 cases (87.1%) of invasive cancer. Sixty-one cases (87.1%) were ER-positive, 54 (77.1%) were PR-positive, and 13 (19.7%) were HER2-positive. Fifteen cases (21.4%) had pathological lymph node metastasis (pN), 60 cases (85.7%) underwent implant reconstruction, 33 cases (47.1%) had a disease-free interval ≤ 36 months, 9 cases (12.9%) had regional lymph node recurrence (RR), and 65 cases (92.9%) underwent surgical resection to treat LRR. The five-year DMFS after LRR was 92.4%, and the five-year OS was 91.2%. The relationship between DMFS and clinical pathology factors was analyzed using a Cox proportional hazards model. Univariate analysis revealed significant differences for pN (HR 10.634, 95% CI 1.102–102.616, P=0.041) and RR (HR 9.960, 95% CI 1.400–70.862, P=0.022), and multivariate analysis indicated that RR was the only independent prognostic factor for DMFS (HR 7.834, 95% CI 1.085–56.587, P=0.041) (Table 1). Univariate analysis revealed significant differences for post-mastectomy radiation therapy (PMRT) (HR 130.676, 95% CI 1.552–412.278, P=0.023) and RR (HR 8.181, 95% CI 1.106–60.503, P=0.043), and multivariate analysis indicated that both PMRT (HR 61.281, 95% CI 2.540–1478.426, P=0.010) and RR (HR 15.687, 95% CI 1.354–181.772, P=0.028) were independent prognostic factors for OS. Conclusions: This is the first study to report the prognosis of breast cancer patients with LRR after IBR. Although these patients have a favorable prognosis overall, our results indicate that RR may be a significant factor for poor prognosis.

Significance of lateral lymph node dissection in squamous cell carcinoma of the anal canal: a retrospective cohort study.

The JCOG (Japan Clinical Oncology Group) 0212 study did not confirm the noninferiority of mesorectal excision (ME) alone to ME with LLND for rectal or anal adenocarcinomas. Furthermore, the significance of LLND for SCCs remains unknown. We evaluated the significance of lateral lymph node dissection (LLND) of squamous cell carcinoma (SCC) of the anal canal. This retrospective cohort study was conducted in 435 patients with SCCs among 1,781 patients with anal canal tumors. In 40 patients who underwent LLND, the 5-year relapse-free survival (5y-RFS) and 5-year overall survival (5y-OS) were compared between groups with positive and negative histopathological findings. In 71 patients with negative lateral lymph node metastasis in the preoperative diagnosis, the 5y-RFS, 5y-OS, and 5-year local recurrence-free survival were compared between patients who did and did not undergo LLND. The clinical and pathological T stages predicted pathological lateral pelvic lymph node metastasis. There was no statistically significant difference in 5y-RFS and 5y-OS between patients who did and did not undergo LLND. Among patients who underwent LLND, 5y-RFS in those with positive histopathological findings (15.0%) was worse than that in those without (59.2%) (p = 0.002). In patients who underwent LLND, 5y-RFS in those with positive histopathological findings than in those without LLND did not contribute to prognosis.

Prognostic factors and significance of postoperative adjuvant chemotherapy in patients with advanced gastric cancer undergoing neoadjuvant chemotherapy followed by gastrectomy.

In Japan, gastrectomy with D2 lymph node dissection and postoperative adjuvant chemotherapy are the standard treatments for locally advanced gastric cancer. Neoadjuvant chemotherapy (NAC) is not affected by postgastrectomy syndromes or postoperative complications. This multicenter retrospective study investigated the prognostic factors and significance of postoperative adjuvant chemotherapy in patients with advanced gastric cancer who underwent NAC followed by gastrectomy. Consecutive patients (n = 221) with advanced gastric cancer who underwent NAC followed by curative surgery were enrolled in this study. Prognostic factors including postoperative adjuvant chemotherapy were investigated using univariate and multivariate analyses. A multivariate analysis revealed that pathological lymph node metastasis (ypN) status and postoperative adjuvant chemotherapy were independent prognostic factors for the overall and relapse-free survival. Forty-five patients (20.4%) did not receive postoperative adjuvant chemotherapy. There were no significant differences between patients with and without adjuvant chemotherapy for all factors, except age. The most common reason for not undergoing postoperative adjuvant chemotherapy was a poor condition (n = 23). ypN status and postoperative adjuvant chemotherapy were independent prognostic factors in gastric cancer patients who underwent NAC followed by curative gastrectomy. It is important to maintain the patient's condition during NAC and the perioperative period so that they can receive postoperative adjuvant chemotherapy.

Use of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) PET/CT for lymph node assessment before radical cystectomy in bladder cancer patients.

To assess the diagnostic performance of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomograpy (PET)/computed tomography (CT) in nodal staging before radical cystectomy (RC) and pelvic lymph node dissection (PLND) for bladder cancer (BCa). This analysis was based on a cohort of 199 BCa patients undergoing RC and bilateral PLND between 2015 and 2022. Neoadjuvant chemotherapy (NAC) or immunotherapy (NAI) was administered after oncological evaluation. All patients received preoperative 18F-FDG PET/CT to assess extravesical disease. Point estimates for true negative, false negative, false positive, true positive, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of conventional imaging and PET/CT were calculated. Subgroup analysis in patients receiving neoadjuvant treatment was performed. At preoperative evaluation, 30 patients (15.1%) had 48 suspicious nodal spots on 18F-FDG PET/CT. At RC and bilateral PLND, a total of 4871 lymph nodes (LNs) were removed with 237 node metastases corresponding to 126 different regions. Pathological node metastases were found in 17/30 (57%) vs 39/169 patients (23%) with suspicious vs negative preoperative 18F-FDG PET/CT, respectively (sensitivity = 0.30, specificity = 0.91, PPV = 0.57, NPV = 0.77, accuracy = 0.74). On per-region analysis including 1367 nodal regions, LN involvement was found in 19/48 (39%) vs 105/1319 (8%) suspicious vs negative regions at PET/CT, respectively (sensitivity = 0.15, specificity = 0.98, PPV = 0.40, NPV = 0.92, ACC = 0.90). Similar results were observed for patients receiving NAC (n = 44, 32.1%) and NAI (n = 93, 67.9% [per-patient: sensitivity = 0.36, specificity = 0.91, PPV = 0.59, NPV = 0.80, accuracy = 0.77; per-region: sensitivity = 0.12, specificity = 0.98, PPV = 0.32, NPV = 0.93, ACC = 0.91]). Study limitations include its retrospective design and limited patient numbers. In eight out of 10 patients with negative preoperative 18F-FDG PET/CT, pN0 disease was confirmed at final pathology. No differences were found based on NAC vs NAI treatment. These findings suggest that 18F-FDG PET/CT could play a role in the preoperative evaluation of nodal metastases in BCa patients, although its cost-effectiveness is uncertain.

An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study

The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], P=0.023; 0.879 [0.767-0.950], P=0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both P>0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P=0.041) to the level of senior pathologists (both P>0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, P<0.0001;-34%, P<0.0001;-29%, P<0.0001; and-27%, P=0.00031). ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application. National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.

The Usefulness of Positron Emission Tomography/Computed Tomography in the Diagnosis of Metastasis in Patients with Urothelial Carcinoma — A Secondary Publication

Purpose: This study examined the usefulness of positron emission tomography (PET)/computed tomography (CT) in the diagnosis of metastasis in patients with urothelial carcinoma. Materials and methods: The subjects were patients who were newly diagnosed with urothelial carcinoma in our department on whom we performed CT and PET/CT to search for metastasis. Results: The median age of the 92 subjects was 71 years, and bladder and upper tract urothelial cancer were underlying diseases in 41 (46%) and 51 (54%) patients, respectively. In 66 (72%) of the 92 cases, no metastasis was observed by CT, while PET/CT revealed metastasis in 9 (14%). The 57 (86%) patients in whom both CT and PET/CT showed no metastasis underwent radical surgery, while 2 patients (4%) exhibited pathological lymph node metastasis. Of the 26 patients in whom CT revealed metastasis, PET/CT showed no metastasis in 3 (12%), and the absence of pathological metastasis was confirmed in all patients. Of the 23 patients found to have metastasis in both CT and PET/CT, metastasis that could not be identified by CT was discovered by performing PET/CT in 10 (43%) patients. PET/CT showed significantly higher diagnostic accuracy than CT alone (P &lt; 0.01), with sensitivities of 94.1% and 67.6%, specificities of 100% and 94.8%, and accuracy rates of 97.8% and 84.7%, respectively. Conclusions: PET/CT of patients with urothelial cancer revealed that metastases that cannot be diagnosed by CT alone are found at a significant frequency. Since these metastases can affect treatment choices in patients with urothelial cancer, PET/CT is considered to be useful in diagnosing metastases in patients with urothelial cancer.

Correlation between Ki-67 or Profilin-1 Expression Levels, Clinicopathological Characteristics and Postoperative Prognosis in Patients with Bladder Cancer.

Bladder cancer is the most common malignancy of the urinary system, and the search for new and reliable biomarkers has important clinical significance for the personalized treatment of bladder cancer. This study aims to explore the correlation between nuclear proliferation antigen (Ki-67) or Profilin-1 (PFN1) levels, clinicopathological characteristics, and postoperative prognosis in patients with bladder cancer. Patients with bladder cancer who underwent transurethral resection of bladder cancer tumor in The Fourth Affiliated Hospital of Soochow University, hospital from January 2019 to January 2021 were selected as the study group (n = 60), and patients with benign lesions of bladder cancer during the same period were selected as the control group (n = 60). The expression of Ki-67 and PFN1 in tumor and bladder tissues of the two groups was analyzed. Ki-67 recorded the patient's pathological parameters and calculated the patient's postoperative prognosis. The correlation between Ki-67 and PFN1 expression levels, pathological parameters, and postoperative prognosis was analyzed. The positive expression rates of Ki-67 and PFN1 in the study group were 63.33% and 73.33%, respectively, which were significantly higher than the positive expression rates in the control group (χ2 = 14.803, 17.757, p < 0.001). The positive expression rates of Ki-67 and PFN1 were related to histological grade, clinical stage, infiltration, and lymph node metastasis, and the differences were statistically significant (p < 0.05). Bladder cancer patients with non muscle-invasive bladder cancer (NMIBC), high-grade histological grade, Ta~T1 clinical stage, invasive, and lymph node metastasis have a higher Ki-67 positive expression rate than bladder cancer patients with muscle-invasive bladder cancer (MIBC), low-grade histological grade, T2~T4, non-invasive, and no lymph node metastasis. The high expression level of Ki-67 has little relationship with gender, age, tumor diameter, and vascular invasion (p > 0.05). The survival time and three-year survival rate of the Ki-67 positive expression group were significantly lower than those of the Ki-67 negative expression group (p < 0.05). The survival time and three-year survival rate of the PFN1 positive expression group were significantly lower than those of the PFN1 negative expression group (p < 0.05). The positive expression rates of Ki-67 and PFN1 in bladder tumor tissue are significantly higher than those in bladder tissue, and pathological pattern, histological grade, clinical stage, infiltration, and lymph node metastasis are related to the positive expression rates of Ki-67 and PFN1, and different genders, ages, tumors diameter and vascular invasion are not related to the positive expression rates of Ki-67 and PFN1. The survival time and three-year survival rates of bladder cancer patients with Ki-67 positive and PFN1 positive expression are shorter.

Radiomics Features Using Dual-energy CT for Lymph Nodes After Preoperative Chemotherapy for Esophageal Cancer.

Progress has been made in a triplet preoperative chemotherapy regimen for advanced esophageal cancer. We performed a preliminary investigation of the radiomics features of pathological lymph node metastasis after neoadjuvant chemotherapy using dual-energy computed tomography (DECT). From January to December 2022, 36 lymph nodes from 10 patients with advanced esophageal cancer who underwent contrast-enhanced DECT after neoadjuvant chemotherapy and radical surgery in our department were studied. Radiomics features were extracted from iodine-based material decomposition images at the portal venous phase constructed by DECT using MATLAB analysis software. Receiver operating characteristic (ROC) analysis and cut-off values were determined for the presence or absence of pathological metastasis. ROC for the short axis of the pathologically positive lymph nodes showed an AUC of 0.713. Long run emphasis (LRE) within gray-level run-length matrix (GLRLM) was confirmed with a high AUC of 0.812. Sensitivity and specificity for lymph nodes with a short axis >10 mm were 0.222 and 1, respectively. Sensitivity and specificity for LRE within GLRLM were 0.722 and 0.833, respectively. Sensitivity and specificity for small zone emphasis (SZE) within gray-level size zone matrix (GLSZM) were 0.889 and 0.667, and zone percentage (ZP) values within GLSZM were 0.722 and 0.778, respectively. Discrimination of existing metastases using radiomics showed significantly higher sensitivity compared to lymph node short axis >10 mm (odds ratios of LRE, SZE, and ZP: 9.1, 28, and 9.1, respectively). Evaluation of radiomics analysis using DECT may enable a more detailed evaluation of lymph node metastasis after neoadjuvant chemotherapy.

Abstract 5047: Identifying genomic features associated with pathologic lymph node metastasis in lung adenocarcinoma patients

Abstract Introduction: Lymph node metastasis evaluation in solid tumors is mainly complicated by the diagnostic yield of standard imaging modalities and tumor size contradictions. Exploring clinical/molecular features that complement the use of radiologic and bronchoscopy findings may provide significant values for a more accurate pathologic determination of nodal metastasis. Methods: We analyzed surgery-resected tumor samples from 72 treatment-naïve lung adenocarcinoma (LUAD) patients via whole-exome sequencing (WES). Mutational profiles of patients categorized based on their pathologic lymph node metastasis (pN) status were assessed, and the association between metastatic-driving features and overall survival (OS) was then explored in both the study cohort and the Cancer Genome Atlas Program (TCGA) external cohort. Results: Among all 72 patients, 41 (56.9%) were pathologically confirmed as positive for lymph node metastasis (pN-positive), while 31 (43.1%) were categorized as pN-negative. The most frequently mutated gene was TP53 in both subgroups (54.8% and 53.7%, respectively), and the aberrant KEAP1-NRF2 signaling pathway was found significantly more enriched in pN-negative patients. Copy-number variant analysis showed that chromosome 7p amplifications (X7p_amp) at the arm level and EGFR amplifications at the focal gene level were more frequently identified in pN-positive patients (P=0.008 and P=0.004, respectively). Importantly, these amplifications were associated with worse OS in both the study cohort and the TCGA external dataset. Consistent with the unfavorable prognosis, pN-positive patients demonstrated a higher chromosome instability score (CIS) (median: 0.32 vs. 0.14, P=0.14) and a lower tumor mutation burden (TMB) (median: 1.83 vs. 3.85 muts/Mb, P=0.048) compared to pN-negative patients. Conclusion: Our findings suggest that X7p_amp, particularly EGFR amplification, might be associated with pathologic involvement of lymph nodes and an unfavorable prognosis in LUAD patients. Our study highlights the importance of integrating clinical and genomic data into conventional radiologic modalities for a more accurate determination of pathologic nodal involvement. Citation Format: Shijie Wang, Zhiwei Zhou, Song Wang, Rongyun Guo, Zeming Ma, Dachuan Zhao, Liang Wang, Yinan Liu, Yuanyuan Ma, Jianzhi Zhang, Sha Wang, Yedan Chen, Haimeng Tang, Qiuxiang Ou, Jinfeng Chen. Identifying genomic features associated with pathologic lymph node metastasis in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5047.

Abstract 1025: An AI based CT scan classifier for predicting extranodal extension and nodal metastasis of HPV-associated oropharyngeal carcinoma

Abstract Background: Pathologic extranodal extension (ENE) and nodal metastasis (NM) are of prognostic significance in human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC). The pretreatment identifications of these two factors through computed tomography (CT) imaging are of clinical importance since they could guide treatment de-escalation protocols and select candidates suitable for surgery. In an effort to enhance pretreatment decision making, we developed and validated an AI model (specifically a multi-layer perceptron (MLP)-based deep learning model) to predict radiologic NM and pathologic ENE in HPV-associated OPSCC patients. Methods: Radiographic CT scans for 290 OPSCC patients treated with definitive chemoradiation were acquired from The Cancer Imaging Archive (TCIA) and divided into training (D1) and validation (D2) cohorts for NM prediction. Radiologic NM for D1 and D2 were reviewed by two radiologists. Only nodes with concordant NM judgments from both radiologists were included for analysis. An additional 46 OPSCC patients treated with surgery at Emory Winship Cancer Institute were collected to form the test cohorts (D3) for ENE prediction. The largest metastatic or normal nodes were annotated for D1 and D2 while all visible nodes with pathology confirmation of ENE from D3 were annotated. We present a novel deep-learning model utilizing U-shaped multi-layer perceptron mixer (MLP-Mixer) to capture both global and local feature representations by spatially aggregating image patch information through a procedure called token-mixing. The model was trained for 20 epochs with learning rate of0.0001 and batch size of 64. The diagnostic performance of the AI model was evaluated on D2 and D3 using accuracy and area under the ROC curve (AUROC). Results: There were 121 NM negative and 130 NM positive nodes in D1, 14 NM negative and 25 NM positive nodes in D2 and 46 ENE negative and 20 ENE positive nodes in D3. On D2 for NM prediction, the AI model achieved overall accuracy of 0.77 and AUROC of 0.78. On D3 for ENE prediction, the AI model achieved overall accuracy of 0.71, AUROC of 0.69, positive predictive value of 0.52 and negative predictive value of 0.86. Conclusions: The new AI–based deep learning model was able to identify HPV-associated OPSCC NM and ENE with satisfactory diagnostic performance and shows promise to assist clinicians in treatment decision-making. Additional, multi-site prospective validation of the approach is warranted. Citation Format: Bolin Song, Kailin Yang, Shaoyan Pan, Liping Li, Qiyun Liu, Jonathan Lee, Sarah Stock, Nabil F. Saba, Mehmet Asim Bilen, Mihir R. Patel, Anant Madabhushi. An AI based CT scan classifier for predicting extranodal extension and nodal metastasis of HPV-associated oropharyngeal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1025.