Micrometastases or isolated tumor cells and the outcome of breast cancer

Prognostic significance of micronest in cancer stroma in resected lung squamous cell carcinoma

Tumor budding in the cancer stroma has been reported to be a prognostic factor in non-small cell lung cancer. Micronest in cancer stroma (MICS) is often observed as a formation that is larger and more conspicuous than budding, but its clinicopathologic significance is unclear. In this study, we aimed to examine the clinicopathological significance of MICS in lung squamous cell carcinoma (LSqCC). A total of 198 consecutive patients with pathologically diagnosed LSqCC (anyT N0-1M0) were enrolled in this study. MICS were defined as those that met the following criteria: (1) consisting of 5-200 tumor cells or less than 200 μm in diameter and (2) more than 200 μm away from the adjacent main lesion. The prognostic impact of the presence or absence of MICS and the characteristics of MICS-forming cancer cells were evaluated by immunohistochemistry (IHC). MICS was observed in 57 patients (28.8%), and overall survival (OS) and recurrence-free survival (RFS) were significantly shorter in the MICS-positive group (OS: 44.4% vs. 84.4%, p < 0.001; RFS: 30.0% vs. 82.6%, p < 0.001). Univariate and multivariate analyses revealed that the presence of MICS was an independent poor prognostic factor for OS (hazard ratio [HR] 3.54, p < 0.001) and RFS (HR 4.99, p < 0.001). Immunohistochemistry showed that the expression levels of the cell-cell adhesion molecule E-cadherin and hypoxia-induced protein GLUT-1 were significantly decreased in cancer cells forming MICS lesions compared to the tumor component excluding MICS within the same tumor (non-MICS lesions). Our data show that MICS is a distinct morphological feature with important biological and prognostic significance.

Structural Defect-Enabled Magnetic Neutrality Nanoprobes for Ultra-High-Field Magnetic Resonance Imaging of Isolated Tumor Cells in Vivo

The identification of metastasis "seeds," isolated tumor cells (ITCs), is of paramount importance for the prognosis and tailored treatment of metastatic diseases. The conventional approach to clinical ITCs diagnosis through invasive biopsies is encumbered by the inherent risks of overdiagnosis and overtreatment. This underscores the pressing need for noninvasive ITCs detection methods that provide histopathological-level insights. Recent advancements in ultra-high-field (UHF) magnetic resonance imaging (MRI) have ignited hope for the revelation of minute lesions, including the elusive ITCs. Nevertheless, currently available MRI contrast agents are susceptible to magnetization-induced strong T2-decaying effects under UHF conditions, which compromises T1 MRI capability and further impedes the precise imaging of small lesions. Herein, this study reports a structural defect-enabled magnetic neutrality nanoprobe (MNN) distinguished by its paramagnetic properties featuring an exceptionally low magnetic susceptibility through atomic modulation, rendering it almost nonmagnetic. This unique characteristic effectively mitigates T2-decaying effect while concurrently enhancing UHF T1 contrast. Under 9 T MRI, the MNN demonstrates an unprecedentedly low r2/r1 value (≈1.06), enabling noninvasive visualization of ITCs with an exceptional detection threshold of ≈0.16 mm. These high-performance MNNs unveil the domain of hitherto undetectable minute lesions, representing a significant advancement in UHF-MRI for diagnostic purposes and fostering comprehensive metastasis research.

Clinical implementation of artificial-intelligence-assisted detection of breast cancer metastases in sentinel lymph nodes: the CONFIDENT-B single-center, non-randomized clinical trial

Pathologists' assessment of sentinel lymph nodes (SNs) for breast cancer (BC) metastases is a treatment-guiding yet labor-intensive and costly task because of the performance of immunohistochemistry (IHC) in morphologically negative cases. This non-randomized, single-center clinical trial (International Standard Randomized Controlled Trial Number:14323711) assessed the efficacy of an artificial intelligence (AI)-assisted workflow for detecting BC metastases in SNs while maintaining diagnostic safety standards. From September 2022 to May 2023, 190 SN specimens were consecutively enrolled and allocated biweekly to the intervention arm (n = 100) or control arm (n = 90). In both arms, digital whole-slide images of hematoxylin-eosin sections of SN specimens were assessed by an expert pathologist, who was assisted by the 'Metastasis Detection' app (Visiopharm) in the intervention arm. Our primary endpoint showed a significantly reduced adjusted relative risk of IHC use (0.680, 95% confidence interval: 0.347-0.878) for AI-assisted pathologists, with subsequent cost savings of ~3,000 €. Secondary endpoints showed significant time reductions and up to 30% improved sensitivity for AI-assisted pathologists. This trial demonstrates the safety and potential for cost and time savings of AI assistance.

A novel nomogram and survival analysis for different lymph node status in breast cancer based on the SEER database

INTRODUCTION

The axillary lymph node status (ALNS) and internal mammary lymph nodes (IMLN) expression associated with breast cancer are closely linked to prognosis. This study aimed to establish a nomogram to predict survival at 3, 5, and 10 years in patients with various lymph node statuses.

METHODS

We obtained data from patients with breast cancer between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER database). Chi-square analysis was performed to test for differences in the pathological characteristics of the groups, and Kaplan-Meier analysis and the log-rank test were used to plot and compare the correlation between overall survival (OS) and breast cancer specific survival (BCSS). The log-rank test was used for the univariate analysis, and statistically significant characteristics were included in the multivariate and Cox regression analyses. Finally, Independent factor identification was included in constructing the nomogram using R studio 4.2.0; area under curve (AUC) values were calculated, and receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA) curves were plotted for evaluation.

RESULTS

A total of 279,078 patients were enrolled and analysed, demonstrating that the isolated tumour cells (ITC) group had clinicopathological characteristics similar to those of micrometastases (Mic). Multivariate analysis was performed to identify each subgroup's independent risk factors and construct a nomogram. The AUC values were 74.7 (95% CI 73.6-75.8), 72.8 (95% CI 71.9-73.8), and 71.2 (95% CI 70.2-72.2) for 3-, 5-, and 10-year OS, respectively, and 82.2 (95% CI 80.9-83.6), 80.1 (95% CI 79.0-81.2), and 75.5 (95% CI 74.3-76.8) for BCSS in overall breast cancer cases, respectively. AUC values for 3-, 5-, and 10-year OS in the ITC group were 64.8 (95% CI 56.5-73.2), 67.7 (95% CI 62.0-73.4), and 65.4 (95% CI 60.0-70.7), respectively. For those in the Mic group, AUC values for 3-, 5-, and 10-year OS were 72.9 (95% CI 70.7-75.1), 72.4 (95% CI 70.6-74.1), and 71.3 (95% CI 69.6-73.1), respectively, and AUC values for BCSS were 77.8 (95% CI 74.9-80.7), 75.7 (95% CI 73.5-77.9), and 70.3 (95% CI 68.0-72.6), respectively. In the IMLN group, AUC values for 3-, 5-, and 10-year OS were 75.2 (95% CI 71.7-78.7), 73.4 (95% CI 70.0-76.8), and 74.0 (95% CI 69.6-78.5), respectively, and AUC values for BCSS were 76.6 (95% CI 73.0-80.3), 74.1 (95% CI 70.5-77.7), and 74.7 (95% CI 69.8-79.5), respectively. The ROC, calibration, and DCA curves verified that the nomogram had better predictability and benefits.

CONCLUSION

This study is the first to investigate the predictive value of different axillary lymph node statuses and internal mammary lymph node metastases in breast cancer, providing clinicians with additional aid in treatment decisions.

Prognosis of isolated tumor cells and use of molecular classification in early stage endometrioid endometrial cancer

OBJECTIVE

We assessed the prognosis and molecular subtypes of early stage endometrioid endometrial cancer with isolated tumor cells within sentinel lymph nodes (SLNs) compared with node negative disease.

METHODS

Patients diagnosed with stage IA, IB, or II endometrioid endometrial cancer and primary surgical management were identified from January 1, 2007 to December 31, 2019. All SLNs underwent ultrastaging according to the institutional protocol. Patients with cytokeratin positive cells, micrometastases, and macrometastases were excluded. Clinical, pathology, and molecular subtype data were reviewed.

RESULTS

Overall, 1214 patients with early stage endometrioid endometrial cancer met the inclusion criteria, of whom 1089 (90%) had node negative disease and 125 (10%) had isolated tumor cells. Compared with node negative disease, the presence of isolated tumor cells had a greater association with deep myometrial invasion, lymphovascular space invasion, receipt of adjuvant therapy, and adjuvant chemotherapy with or without radiation (p<0.01). There was no significant difference in survival rates between patients with isolated tumor cells and node negative disease (3 year progression free survival rate 94% vs 91%, respectively, p=0.21; 3 year overall survival rate 98% vs 96%, respectively, p=0.45). Progression free survival did not significantly differ among patients with isolated tumor cells who received no adjuvant therapy or chemotherapy with or without radiation (p=0.31). There was no difference in the distribution of molecular subtypes between patients with isolated tumor cells (n=28) and node negative disease (n=194; p=0.26). Three year overall survival rates differed significantly when stratifying the entire cohort by molecular subtype (p=0.04).

CONCLUSIONS

Patients with isolated tumor cells demonstrated less favorable uterine pathologic features and received more adjuvant treatment with similar survival compared with patients with nodenegative disease. Among the available data, molecular classification did not have a significant association with the presence of isolated tumor cells, although copy number-high status was a poor prognostic indicator in early stage endometrioid endometrial cancer.

Diagnostic value of one-step nucleic acid amplification for sentinel lymph node metastasis in cytokeratin 19-positive tumors: evidence from bioinformatics and meta-analysis

Background

The status of the sentinel lymph nodes (SLNs) was an important prognostic factor in varies cancers. A one-step nucleic acid amplification (OSNA) assay, a molecular-based whole-node analysis method based on CK19 mRNA copy number, was developed to diagnose lymph node metastases. We aimed to evaluate the value of OSNA for the diagnosis of sentinel lymph node metastasis in CK19 positive cancers. CK19 mRNA and protein expression for pan-caner analysis were obtained from TCGA and the Human protein atlas database.

Methods

Two researchers independently searched the PubMed, Cochrane Library and Web of Science databases for qualified articles published before December 1, 2023. A meta-analysis was performed using MetaDisc and STATA. Risk bias and quality assessments of the included studies were evaluated, and a subgroup analysis was performed. Ten cancer types were found to be CK19 positively expressed and 7 of 10 had been reported to use OSNA for SLN detection.

Results

After literature review, there were 61 articles included in the meta-analysis, which consisted of 7115 patients with 18007 sentinel lymph nodes. The pooled sensitivity and specificity of OSNA were 0.87 and 0.95 in overall patients. Moreover, we found the background CK19 expression in normal tissue affected the diagnostic accuracy of OSNA. In breast cancer, we performed subgroup analysis. OSNA exhibited to be a stable method across different population groups and various medical centers. In addition, when 250 copies/μl was chosen as the cutoff point of CK19 mRNA, there were a relatively higher sensitivity and AUC in detecting SLN micro-metastasis than 5000 copies/μl.

Discussion

OSNA can predict the occurrence of SLN metastasis accurately in CK19 positive cancers, especially in breast cancer, colorectal cancer, lung cancer, gastric cancer and endometrial cancer. Our study warrants future studies investigating the clinical application of OSNA in pancreatic, ovarian and bladder cancers.

Rare Presentation of Papillary Carcinoma Within a Sentinel Lymph Node in a Patient With Ductal Carcinoma in Situ of the Breast: A Challenging but Useful Case Report Discussion Regarding Displacement or True Metastasis?

Papillary carcinoma of the breast is a rare histologic subtype of invasive breast cancer. In contrast, ductal carcinoma in situ (DCIS) is a noninvasive, nonobligate precursor to invasive mammary carcinoma, confined within the terminal duct lobular unit of the breast and surrounded by an intact myoepithelial cell layer at the stromal/epithelial interface. We present an unusual case in which a patient with only DCIS of the breast exhibited papillary carcinoma within a sentinel lymph node, leading to questions about the origin of the lymph node lesion-whether it represents a true metastasis or iatrogenic displacement during diagnostic procedures. This case underscores the diagnostic challenges and clinical implications associated with such rare presentations.

Macrophages Promote Subtype Conversion and Endocrine Resistance in Breast Cancer

BACKGROUND

The progression of tumors from less aggressive subtypes to more aggressive states during metastasis poses challenges for treatment strategies. Previous studies have revealed the molecular subtype conversion between primary and metastatic tumors in breast cancer (BC). However, the subtype conversion during lymph node metastasis (LNM) and the underlying mechanism remains unclear.

METHODS

We compared clinical subtypes in paired primary tumors and positive lymph nodes (PLNs) in BC patients and further validated them in the mouse model. Bioinformatics analysis and macrophage-conditioned medium treatment were performed to investigate the role of macrophages in subtype conversion.

RESULTS

During LNM, hormone receptors (HRs) were down-regulated, while HER2 was up-regulated, leading to the transformation of luminal A tumors towards luminal B tumors and from luminal B subtype towards HER2-enriched (HER2-E) subtype. The mouse model demonstrated the elevated levels of HER2 in PLN while retaining luminal characteristics. Among the various cells in the tumor microenvironment (TME), macrophages were the most clinically relevant in terms of prognosis. The treatment of a macrophage-conditioned medium further confirmed the downregulation of HR expression and upregulation of HER2 expression, inducing tamoxifen resistance. Through bioinformatics analysis, MNX1 was identified as a potential transcription factor governing the expression of HR and HER2.

CONCLUSION

Our study revealed the HER2-E subtype conversion during LNM in BC. Macrophages were the crucial cell type in TME, inducing the downregulation of HR and upregulation of HER2, probably via MNX1. Targeting macrophages or MNX1 may provide new avenues for endocrine therapy and targeted treatment of BC patients with LNM.

Diagnostic value of applying preoperative breast ultrasound and clinicopathologic features to predict axillary lymph node burden in early invasive breast cancer: a study of 1247 patients

BACKGROUND

Since the Z0011 trial, the assessment of axillary lymph node status has been redirected from the previous assessment of the occurrence of lymph node metastasis alone to the assessment of the degree of lymph node loading. Our aim was to apply preoperative breast ultrasound and clinicopathological features to predict the diagnostic value of axillary lymph node load in early invasive breast cancer.

METHODS

The 1247 lesions were divided into a high lymph node burden group and a limited lymph node burden group according to axillary lymph node status. Univariate and multifactorial analyses were used to predict the differences in clinicopathological characteristics and breast ultrasound characteristics between the two groups with high and limited lymph node burden. Pathological findings were used as the gold standard.

RESULTS

Univariate analysis showed significant differences in ki-67, maximum diameter (MD), lesion distance from the nipple, lesion distance from the skin, MS, and some characteristic ultrasound features (P < 0.05). In multifactorial analysis, the ultrasound features of breast tumors that were associated with a high lymph node burden at the axilla included MD (odds ratio [OR], 1.043; P < 0.001), shape (OR, 2.422; P = 0.0018), hyperechoic halo (OR, 2.546; P < 0.001), shadowing in posterior features (OR, 2.155; P = 0.007), and suspicious lymph nodes on axillary ultrasound (OR, 1.418; P = 0.031). The five risk factors were used to build the predictive model, and it achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.702.

CONCLUSION

Breast ultrasound features and clinicopathological features are better predictors of high lymph node burden in early invasive breast cancer, and this prediction helps to develop more effective treatment plans.

Exploring the Potential of Artificial Intelligence in Breast Ultrasound

Breast ultrasound has emerged as a valuable imaging modality in the detection and characterization of breast lesions, particularly in women with dense breast tissue or contraindications for mammography. Within this framework, artificial intelligence (AI) has garnered significant attention for its potential to improve diagnostic accuracy in breast ultrasound and revolutionize the workflow. This review article aims to comprehensively explore the current state of research and development in harnessing AI's capabilities for breast ultrasound. We delve into various AI techniques, including machine learning, deep learning, as well as their applications in automating lesion detection, segmentation, and classification tasks. Furthermore, the review addresses the challenges and hurdles faced in implementing AI systems in breast ultrasound diagnostics, such as data privacy, interpretability, and regulatory approval. Ethical considerations pertaining to the integration of AI into clinical practice are also discussed, emphasizing the importance of maintaining a patient-centered approach. The integration of AI into breast ultrasound holds great promise for improving diagnostic accuracy, enhancing efficiency, and ultimately advancing patient's care. By examining the current state of research and identifying future opportunities, this review aims to contribute to the understanding and utilization of AI in breast ultrasound and encourage further interdisciplinary collaboration to maximize its potential in clinical practice.

External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer

BACKGROUND

The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment.

METHODS

We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds.

RESULTS

A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22-1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62-0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51-0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors.

CONCLUSIONS

PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.

Clinical relevance of sentinel lymph node biopsy in early ovarian cancer

The first-line treatment for early ovarian cancer typically involves primary debulking surgery aimed at maximal cytoreduction, alongside adjuvant chemotherapy if clinically indicated. Nodal assessment involving pelvic and para-aortic lymph node dissection is typically performed during the primary debulking surgery. However, the survival benefit of lymphadenectomy in patients with early ovarian cancer has not been well established, and the procedure is associated with longer operation time and higher perioperative complications. With the emergence of minimally invasive surgery as a potential alternative to laparotomy for early ovarian cancer, sentinel lymph node biopsy has been evaluated in this setting. In this review, we summarized the current literature regarding sentinel lymph node biopsy in patients with early ovarian cancer, focusing on the clinical relevance of this method, including its detection rate and diagnostic accuracy. Additionally, we discuss the current status of clinical trials investigating sentinel lymph node biopsy in early ovarian cancer cases.

Recommandations francophones pour la pratique clinique concernant la prise en charge des cancers du sein de Saint-Paul-de-Vence 2022-2023

With more than 60,000 new cases of breast cancer in mainland France in 2023 and 8% of all cancer deaths, breast cancer is the leading cancer in women in terms of incidence and mortality. While the number of new cases has almost doubled in 30 years, the percentage of patients at all stages alive at 5 years (87%) and 10 years (76%) testifies to the major progress made in terms of screening, characterisation and treatment. However, this progress, rapid as it is, needs to be evaluated and integrated into an overall strategy, taking into account the characteristics of the disease (stage and biology), as well as those of the patients being treated. These are the objectives of the St Paul-de-Vence recommendations for clinical practice. We report here the summary of the votes, discussions and conclusions of the Saint-Paul-de-Vence 2022-2023 RPCs.

Impact of analysis of the sentinel lymph node by one-step nucleic acid amplification (OSNA) compared to conventional histopathology on axillary and systemic treatment: data from the Dutch nationwide cohort of breast cancer patients

PURPOSE

The outcome of the sentinel lymph node in breast cancer patients affects adjuvant treatment. Compared to conventional histopathology, analysis by one-step nucleic acid amplification (OSNA) harvests more micrometastasis, potentially inducing overtreatment. In this study we investigated the impact of OSNA analysis on adjuvant treatment, compared to histopathological analysis.

METHODS

Data from T1-3 breast cancer patients with sentinel nodes analysed between January 2016 and December 2019 by OSNA (OSNA group, n = 1086) from Zuyderland Medical Centre, the Netherlands, were compared to concurrent data from the Netherlands Cancer Registry (NKR) where sentinel nodes were examined by histology (histology group, n = 35,143). Primary outcomes were micro- or macrometastasis, axillary treatments (axillary lymph node dissection (ALND) or axillary radiotherapy (ART)), chemotherapy, and endocrine therapy. Statistics with Pearson Chi-square.

RESULTS

In the OSNA group more micrometastasis (14.9%) were detected compared to the histology group (7.9%, p < 0.001). No difference in axillary treatment between groups was detected (14.3 vs. 14.4%). In case of mastectomy and macrometastasis, ALND was preferred over ART in the OSNA group (14.9%) compared to the histology group (4.4%, p < 0.001). In cases of micrometastasis, no difference was seen. There was no difference in administration of adjuvant chemotherapy between groups. Endocrine treatment was administrated less often in the OSNA group compared to the histology group (45.8% vs. 50.8%, p < 0.002).

CONCLUSION

More micrometastasis were detected by OSNA compared to histopathology, but no subsequent increase in adjuvant axillary and systematic treatment was noticed. When performing mastectomy and OSNA, there was a preference for ALND compared to ART.

Negative Survival Impact of Occult Lymph Node Involvement in Small HER2-Positive Early Breast Cancer Treated by Up-Front Surgery

(1) Background: The independent negative prognostic value of isolated tumor cells or micro-metastases in axillary lymph nodes has been established in triple-negative breast cancers (BC). However, the prognostic significance of pN0(i+) or pN1mi in HER2-positive BCs treated by primary surgery remains unexplored. Therefore, our objective was to investigate the impact of pN0(i+) or pN1mi in HER2-positive BC patients undergoing up-front surgery on their outcomes. (2) Methods: We retrospectively analyzed 23,650 patients treated in 13 French cancer centers from 1991 to 2013. pN status was categorized as pN0, pN0(i+), pN1mi, and pNmacro. The effect of pN0(i+) or pN1mi on outcomes was investigated both in the entire cohort of patients and in pT1a-b tumors. (3) Results: Of 1771 HER2-positive BC patients included, pN status distributed as follows: 1047 pN0 (59.1%), 60 pN0(i+) (3.4%), 118 pN1mi (6.7%), and 546 pN1 macro-metastases (30.8%). pN status was significantly associated with sentinel lymph node biopsy, axillary lymph node dissection, age, ER status, tumor grade, and size, lymphovascular invasion, adjuvant systemic therapy (ACt), and radiation therapy. With 61 months median follow-up (mean 63.2; CI 95% 61.5-64.9), only pN1 with macro-metastases was independently associated with a negative impact on overall, disease-free, recurrence-free, and metastasis-free survivals in multivariate analysis. In the pT1a-b subgroup including 474 patients, RFS was significantly decreased in multivariate analysis for pT1b BC without ACt (HR 2.365, 1.04-5.36, p = 0.039) and for pN0(i+)/pN1mi patients (HR 2.518, 1.03-6.14, p = 0.042). (4) Conclusions: Survival outcomes were not adversely affected by pN0(i+) and pN1mi in patients with HER2-positive BC. However, in the case of pT1a-b HER2-positive BC, a negative impact on RFS was observed specifically for patients with pN0(i+) and pN1mi diseases, particularly among those with pT1b tumors without ACt. Our findings highlight the importance of considering the pN0(i+) and pN1mi status in the decision-making process when discussing trastuzumab-based ACt for these patients.

Role of lymphatic invasion in predicting biochemical recurrence after radical prostatectomy

Objective

Lymphatic invasion in prostate cancer is associated with poor prognosis. However, there is no consensus regarding the clinical and prognostic value of lymphatic invasion. This study aimed to investigate the prognostic value of lymphatic invasion in biochemical recurrence (BCR) and compare the recurrence rates between patients with lymphatic invasion and lymph node metastasis.

Methods

We retrospectively analyzed 2,207 patients who underwent radical prostatectomy (RP) without pelvic lymph node dissection (PLND) and 742 patients who underwent RP with PLND for clinically localized or locally advanced prostate cancer, between 1993 and 2020, at Seoul National University Hospital. Kaplan-Meier analysis was performed to estimate BCR-free survival (BCRFS) using the log-rank test. The Cox proportional hazards model was used to identify the significant factors for BCR. Propensity score matching was performed with a 1:2 ratio to match age, initial PSA level, pathological T stage, and Gleason score to exclude confounding effects.

Results

Of the 2,207 patients who underwent RP without PLND, lymphatic invasion (L1Nx) was observed in 79 (3.5%) individuals. Among the 742 patients who underwent RP with PLND, lymph node metastases were found in 105 patients (14.2%). In patients with lymph node metastasis, lymphatic invasion was observed in 50 patients (47.6%), whereas lymphatic invasion was observed in 53 patients (8.3%) among those without lymph node metastasis. In patients who underwent RP without PLND, Kaplan-Meier analysis showed significantly poorer BCR-free survival in the L1Nx group than in the L0Nx group (p < 0.001). In patients who underwent RP with PLND, the L1N0, L0N1, and L1N1 groups showed significantly worse prognoses than the L0N0 group (p < 0.001). However, there was no significant difference in BCRFS between the L1N0 and lymph node metastasis groups, including the L0N1 and L1N1 groups. After propensity score matching at a 1:2 ratio, the L1Nx group showed significantly poorer outcomes in terms of BCRFS than the L0Nx group (p = 0.05). In addition, the L1N0 group showed a significantly worse prognosis than the L0N0 group after propensity score matching.

Conclusion

Lymphatic invasion in radical prostatectomy specimens is an independent prognostic factor, which can complement lymph node status for predicting biochemical recurrence. Considering lymphatic invasion as an adverse pathological finding, similar to lymph node metastasis, adjuvant therapy could be considered in patients with lymphatic invasion.

Prognosis and local treatment strategies of breast cancer patients with different numbers of micrometastatic lymph nodes

BACKGROUND

Lymph node micrometastasis is an important prognostic factor in breast cancer, but patients with different numbers of involved lymph nodes are all divided into the same N1mi stage without distinction. We designed this study to compare the prognosis and local treatment recommendations of N1mi breast cancer patients with different numbers of micrometastatic lymph nodes.

PATIENTS AND METHODS

A total of 27,032 breast cancer patients with T1-2N1miM0 stage from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2019) who underwent breast surgery were included in this retrospective study. Patients were divided into three groups for prognosis comparison according to the number of micrometastatic lymph nodes: N1mi with 1 (Nmi = 1), 2 (Nmi = 2), or more (Nmi ≥ 3) involved lymph nodes. We explored the characteristics and survival outcomes of the population receiving different local treatments, including different axillary surgery types and whether receiving radiotherapy or not. Univariate and multivariate Cox proportional hazards regression analysis were used to compare the overall survival (OS) and breast cancer-specific survival (BCSS) in different groups. Stratified analyses and interaction analyses were also applied to explore the predictive significance of different involved lymph nodes numbers. Propensity score matching (PSM) method was utilized to balance the differences between groups.

RESULTS

Univariate and multivariate Cox regression analysis indicated that nodal status was an independent prognostic factor. After adjustment for other prognostic factors, there was a significant difference in prognosis between Nmi = 1 group and Nmi = 2 group [adjusted hazard ratio (HR) 1.145, 95% confidence interval (CI): 1.047-1.251, P = 0.003], and patients with Nmi ≥ 3 group had a significantly poorer prognosis (adjusted HR 1.679, 95% CI 1.589-2.407; P < 0.001). The proportion of N1mi patients only underwent sentinel lymph nodes biopsy (SLNB) gradually increased from 2010 (P_trend < 0.001). After adjusting for other factors, N1mi patients who underwent axillary lymph nodes dissection (ALND) was associated with significant survival benefit than SLNB (adjusted HR 0.932, 95%CI 0.874-0.994; P = 0.033), the same goes for receiving radiotherapy (adjusted HR 1.107, 95%CI 1.030-1.190; P = 0.006). Further stratified analysis showed that in the SLNB subgroup, radiotherapy was associated with a significant survival benefit (HR 1.695, 95%CI 1.534-1.874; P < 0.001), whereas in the ALND subgroup, there was no significant prognostic difference with or without radiotherapy (HR 1.029, 95%CI 0.933-1.136; P = 0.564).

CONCLUSION

Our study indicates that the increasing number of lymph node micrometastases was associated a worse prognosis of N1mi breast cancer patients. In addition, ALND does provide a significant survival benefit for these patients, while the benefit from local radiotherapy may be of even greater importance.

Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI

BACKGROUND

Previous studies have explored the potential on radiomics features of primary breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of deep learning (DL) to identify ALN metastasis remains unclear.

PURPOSE

To investigate the potential of the proposed attention-based DL model for the preoperative differentiation of ALN metastasis in breast cancer on dynamic contrast-enhanced MRI (DCE-MRI).

STUDY TYPE

Retrospective.

POPULATION

A total of 941 breast cancer patients who underwent DCE-MRI before surgery were included in the training (742 patients), internal test (83 patients), and external test (116 patients) cohorts.

FIELD STRENGTH/SEQUENCE

A 3.0 T MR scanner, DCE-MRI sequence.

ASSESSMENT

A DL model containing a 3D deep residual network (ResNet) architecture and a convolutional block attention module, named RCNet, was proposed for ALN metastasis identification. Three RCNet models were established based on the tumor, ALN, and combined tumor-ALN regions on the images. The performance of these models was compared with ResNet models, radiomics models, the Memorial Sloan-Kettering Cancer Center (MSKCC) model, and three radiologists (W.L., H.S., and F. L.).

STATISTICAL TESTS

Dice similarity coefficient for breast tumor and ALN segmentation. Accuracy, sensitivity, specificity, intercorrelation and intracorrelation coefficients, area under the curve (AUC), and Delong test for ALN classification.

RESULTS

The optimal RCNet model, that is, RCNet-tumor+ALN , achieved an AUC of 0.907, an accuracy of 0.831, a sensitivity of 0.824, and a specificity of 0.837 in the internal test cohort, as well as an AUC of 0.852, an accuracy of 0.828, a sensitivity of 0.792, and a specificity of 0.853 in the external test cohort. Additionally, with the assistance of RCNet-tumor+ALN , the radiologists' performance was improved (external test cohort, P < 0.05).

DATA CONCLUSION

DCE-MRI-based RCNet model could provide a noninvasive auxiliary tool to identify ALN metastasis preoperatively in breast cancer, which may assist radiologists in conducting more accurate evaluation of ALN status.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Best treatment options for occult breast cancer: A meta-analysis

Objectives

Occult breast cancer (OBC) is a rare malignant breast tumor. Because of the rare cases and limited clinical experience, a huge therapeutic difference has existed all over the world and standardized treatments have yet been established.

Methods

A meta-analysis was conducted using MEDLINE and Embase databases to identify the choice of OBC surgical procedures in all studies: (1) patients undergoing axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) only; (2) patients undergoing ALND with radiotherapy (RT); (3) patients undergoing ALND with breast surgery (BS); (4) patients undergoing ALND with RT and BS; and (5) patients undergoing observation or RT only. The primary endpoints were mortality rates, the second endpoints were distant metastasis and locoregional recurrence.

Results

Among the 3,476 patients, 493 (14.2%) undergo ALND or SLNB only; 632 (18.2%) undergo ALND with RT; 1483 (42.7%) undergo ALND with BS; 467 (13.4%) undergo ALND RT and BS, and 401 (11.5%) undergo observation or RT only. After comparing the multiple groups, both groups 1 and 3 have higher mortality rates than group 4 (30.7% vs. 18.6%, p < 0.0001; 25.1% vs. 18.6%, p = 0.007), and group 1 has higher mortality rates than groups 2 and 3 (30.7% vs.14.7%, p < 0.00001; 30.7 vs. 19.4%, p < 0.0001). Group (1 + 3) had a prognosis advantage over group 5 (21.4% vs. 31.0%, p < 0.00001). There was no significant difference both in the distant recurrence rates and locoregional rates between group (1 + 3) and group (2 + 4) (21.0% vs. 9.7%, p = 0.06; 12.3% vs. 6.5%, p = 0.26).

Conclusion

On the basis of this meta-analysis, our study indicates that BS including modified radical mastectomy (MRM) and breast-conserving surgery (BCS) combined RT may appear as the optimal surgical approach in patients with OBC. RT cannot prolong both the time of distant metastasis and the local recurrences.

Non-invasive Assessment of Axillary Lymph Node Metastasis Risk in Early Invasive Breast Cancer Adopting Automated Breast Volume Scanning-Based Radiomics Nomogram: A Multicenter Study

OBJECTIVE

The aim of the work described here was to develop a non-invasive tool based on the radiomics and ultrasound features of automated breast volume scanning (ABVS), clinicopathological factors and serological indicators to evaluate axillary lymph node metastasis (ALNM) in patients with early invasive breast cancer (EIBC).

METHODS

We retrospectively analyzed 179 ABVS images of patients with EIBC at a single center from January 2016 to April 2022 and divided the patients into training and validation sets (ratio 8:2). Additionally, 97 ABVS images of patients with EIBC from a second center were enrolled as the test set. The radiomics signature was established with the least absolute shrinkage and selection operator. Significant ALNM predictors were screened using univariate logistic regression analysis and further combined to construct a nomogram using the multivariate logistic regression model. The receiver operating characteristic curve assessed the nomogram's predictive performance.

DISCUSSION

The constructed radiomics nomogram model, including ABVS radiomics signature, ultrasound assessment of axillary lymph node (ALN) status, convergence sign and erythrocyte distribution width (standard deviation), achieved moderate predictive performance for risk probability evaluation of ALNs in patients with EIBC. Compared with ultrasound, the nomogram model was able to provide a risk probability evaluation tool not only for the ALNs with positive ultrasound features but also for micrometastatic ALNs (generally without positive ultrasound features), which benefited from the radiomics analysis of multi-sourced data of patients with EIBC.

CONCLUSION

This ABVS-based radiomics nomogram model is a pre-operative, non-invasive and visualized tool that can help clinicians choose rational diagnostic and therapeutic protocols for ALNM.

Diagnostic accuracy of frozen section and patterns of nodal spread in high grade endometrial cancer: A secondary outcome of the SENTOR prospective cohort study

OBJECTIVES

The study aimed to define the accuracy of intraoperative frozen section (FS) for the detection of metastases in sentinel lymph node biopsy (SLNB) and describe the pattern of lymph node (LN) spread and relation to molecular classifiers in patients with high-grade endometrial cancer (EC).

METHODS

We performed a secondary outcome of clinicopathologic data from the Sentinel Lymph Node Biopsy versus Lymphadenectomy for Intermediate- and High-Grade Endometrial Cancer Staging (SENTOR) prospective cohort study evaluating SLNB in patients with clinical stage I high-grade EC (ClinicalTrials.gov ID: NCT01886066). The primary outcome was the sensitivity of FS of the sentinel lymph node (SLN) specimen, compared to a standardized ultrastaging protocol. Secondary outcomes included the pattern and characteristics of LN spread.

RESULTS

There were 126 patients with high-grade EC with a median age of 66 years (range:44-86) and a median Body Mass Index (BMI) of 26.9 kg/m² (range:17.6-49.3). FS was performed on surgical specimens from 212 hemipelves; SLNs were identified in 202 specimens (95.7%) and fatty tissue alone was identified in 10 specimens (4.7%). Of the 202 hemipelves in which SLNs were identified, 24 were positive for metastatic disease on final pathology. Initial FS correctly identified only 12, yielding a sensitivity of 50% (12/24, 95% CI 29.6-70.4) and a negative predictive value of 94% (178/190, 95% CI 89-96.5). A total of 24 patients (19%) had LN metastases: 16 (13%) had isolated pelvic metastases, 7 (6%) had both pelvic and para-aortic metastases and 1 (0.8%) had an isolated para-aortic metastasis.

CONCLUSIONS

Intraoperative FS of SLNs in high-grade EC patients has poor sensitivity. Since isolated para-aortic metastases are rare, para-aortic lymphadenectomy may be omitted in patients in which SLNs were successfully mapped to the pelvis.

A novel computational predictive biological approach distinguishes Integrin β1 as a salient biomarker for breast cancer chemoresistance

Chemoresistance is a primary cause of breast cancer treatment failure, and protein-protein interactions significantly contribute to chemoresistance during different stages of breast cancer progression. In pursuit of novel biomarkers and relevant protein-protein interactions occurring during the emergence of breast cancer chemoresistance, we used a computational predictive biological (CPB) approach. CPB identified associations of adhesion molecules with proteins connected with different breast cancer proteins associated with chemoresistance. This approach identified an association of Integrin β1 (ITGB1) with chemoresistance and breast cancer stem cell markers. ITGB1 activated the Focal Adhesion Kinase (FAK) pathway promoting invasion, migration, and chemoresistance in breast cancer by upregulating Erk phosphorylation. FAK also activated Wnt/Sox2 signaling, which enhanced self-renewal in breast cancer. Activation of the FAK pathway by ITGB1 represents a novel mechanism linked to breast cancer chemoresistance, which may lead to novel therapies capable of blocking breast cancer progression by intervening in ITGB1-regulated signaling pathways.

Macroscopic and multiple metastases in sentinel lymph node biopsy are respectively associated with poor prognosis in early oral cancer

BACKGROUND

A multicenter, randomized controlled phase III trial was conducted on sentinel lymph node biopsy (SLNB) and elective neck dissection for T1 (depth of invasion ≥ 4 mm)-T2N0M0 oral cavity squamous cell carcinoma. This study identified factors associated with poor prognosis in patients who underwent SLNB based on a subgroup analysis of this trial.

METHODS

We analyzed 418 sentinel lymph nodes (SLNs) from 132 patients who underwent SLNB. The metastatic SLNs were classified into three categories based on size-isolated tumor cells: < 0.2 mm, micrometastasis: ≥ 0.2 mm and < 2 mm, and macrometastasis: ≥ 2 mm. Three groups were formed based on the number of metastatic SLNs: no metastasis, 1 metastatic node, and ≥ 2 metastatic nodes. The size and number of metastatic SLNs on survival were evaluated using Cox proportional hazard models.

RESULTS

Patients with macrometastasis and ≥ 2 metastatic SLNs had worse overall survival (OS) and disease-free survival (DFS) after adjustment for potential confounders (HR for OS: macrometastasis, 4.85; 95% CI 1.34-17.60; ≥ 2 metastatic SLN, 3.63; 95% CI 1.02-12.89; HR for DFS: macrometastasis, 2.94; 95% CI 1.16-7.44; ≥ 2 metastatic SLN, 2.97; 95% CI 1.18-7.51).

CONCLUSIONS

In patients who underwent SLNB, a poorer prognosis was associated with macrometastasis or having ≥ 2 metastatic SLNs.

Artificial Intelligence for Breast US

US is a widely available, commonly used, and indispensable imaging modality for breast evaluation. It is often the primary imaging modality for the detection and diagnosis of breast cancer in low-resource settings. In addition, it is frequently employed as a supplemental screening tool via either whole breast handheld US or automated breast US among women with dense breasts. In recent years, a variety of artificial intelligence systems have been developed to assist radiologists with the detection and diagnosis of breast lesions on US. This article reviews the background and evidence supporting the use of artificial intelligence tools for breast US, describes implementation strategies and impact on clinical workflow, and discusses potential emerging roles and future directions.

Anatomical site and size of sentinel lymph node metastasis predicted additional axillary tumour burden and breast cancer survival

AIMS

Sentinel lymph node (SLN) biopsy is the current standard assessment for tumour burden in axillary lymph node (ALN). However, not all SLN+ patients have ALN metastasis. The prognostic implication of SLN features is not clear. We aimed to evaluate predictive factors for ALN metastasis and the clinical value of SLN features.

METHODS AND RESULTS

A total of 228 SLN+ and 228 SLN- (with matched year and grade) cases were included. Clinicopathological features in SLN, ALN and primary tumours, treatment data and survival data were analysed according to ALN status and outcome. Except for larger tumour size and the presence of LVI (both P < 0.001), no significant differences were found in SLN- and SLN+ cases. Only 31.8% of SLN+ cases with ALN dissection had ALN metastasis. The presence of macrometastases (MaM), extranodal extension (ENE), deeper level of tumour invasion in SLN and more SLN+ nodes were associated with ALN metastasis (P ≤ 0.025). Moreover, isolated tumour cells (ITC) and level of tumour invasion in SLN were independent adverse prognostic features for disease-free survival and breast cancer-specific survival, respectively. Interestingly, cases with ITC located in the subcapsular region have better survival than those in cortex (OS: χ²  = 4.046, P = 0.044).

CONCLUSIONS

Our study identified features in SLN, i.e. the level of tumour invasion at SLN and tumour size in SLN as useful predictors for both ALN metastasis and breast cancer outcome. The presence of ITC, particularly those with a deeper invasion in SLN, portended a worse prognosis. Proper attention should be taken for their management.

Imaging evaluation of lymphoma in pregnancy with review of clinical assessment and treatment options

Lymphoma-related malignancies can be categorized as Hodgkin's lymphoma (HL) or non-Hodgkin's lymphoma (NHL) based on histologic characteristics. Although quite rare during pregnancy, HL and NHL are the fourth and fifth most common malignancies during the pregnancy period, respectively. Given the rarity of lymphoma among pregnant patients, radiologists are usually unfamiliar with the modifications required for staging and treatment of this population, even those who work at centers with busy obstetrical services. Therefore, this manuscript serves to not only review the abdominopelvic imaging features of lymphoma in pregnancy, but it also discusses topics including birthing parent and fetal lymphoma-related prognosis, both antenatal and postpartum, current concepts in the management of pregnancy-related lymphoma, as well as the current considerations regarding birthing parent onco-fertility.

Breast cancer: emerging principles of metastasis, adjuvant and neoadjuvant treatment from cancer registry data

PURPOSE

Growing primary breast cancers (PT) can initiate local recurrences (LR), regional lymph nodes (pLN) and distant metastases (MET). Components of these progressions are initiation, frequency, growth duration, and survival. These characteristics describe principles which proposed molecular concepts and hypotheses must align with.

METHODS

In a population-based retrospective modeling approach using data from the Munich Cancer Registry key steps and factors associated with metastasis were identified and quantified. Analysis of 66.800 patient datasets over four time periods since 1978, reliable evidence is obtained even in small subgroups. Together with results of clinical trials on prevention and adjuvant treatment (AT) principles for the MET process and AT are derived.

RESULTS

The median growth periods for PT/MET/LR/pLN comes to 12.5/8.8/5/3.5 years, respectively. Even if 30% of METs only appear after 10 years, a pre-diagnosis MET initiation principle not a delayed one should be true. The growth times of PTs and METs vary by a factor of 10 or more but their ratio is robust at about 1.4. Principles of AT are 50% PT eradication, the selective and partial eradication of bone and lung METs. This cannot be improved by extending the duration of the previously known ATs.

CONCLUSION

A paradigm of ten principles for the MET process and ATs is derived from real world data and clinical trials indicates that there is no rationale for the long-term application of endocrine ATs, risk of PTs by hormone replacement therapies, or cascading initiation of METs. The principles show limits and opportunities for innovation also through alternative interpretations of well-known studies. The outlined MET process should be generalizable to all solid tumors.

Sentinel Lymph Node Mapping in Presumed Low- and Intermediate-Risk Endometrial Cancer Management (SLIM): A Multicenter, Prospective Cohort Study in The Netherlands

The aim was to investigate the incidence of sentinel lymph node (SLN) metastases and the contribution of SLN mapping in presumed low- and intermediate-risk endometrial cancer (EC). A multicenter, prospective cohort study in presumed low- and intermediate-risk EC patients was performed. Patients underwent SLN mapping using cervical injections of indocyanine green and a minimally invasive hysterectomy with bilateral salpingo-oophorectomy. The primary outcome was the incidence of SLN metastases, leading to adjusted adjuvant treatment. Secondary outcomes were the SLN detection rate and the occurrence of complications. Descriptive statistics and univariate general linear model analyses were used. A total of 152 patients were enrolled, with overall and bilateral SLN detection rates of 91% and 61%, respectively. At final histology, 78.9% of patients (n = 120) had truly low- and intermediate-risk EC. Macro- and micro-metastases were present in 11.2% (n = 17/152), and three patients had isolated tumor cells (2.0%). Nine patients (5.9%) had addition of adjuvant radiotherapy based on SLN metastases only. In 2.0% of patients with high-risk disease, adjuvant therapy was more limited due to negative SLNs. This study emphasizes the importance of SLN mapping in presumed early-stage, grade 1 and 2 EC, leading to individualized adjuvant management, resulting in less undertreatment and overtreatment.

Artificial Intelligence in Breast Ultrasound: From Diagnosis to Prognosis-A Rapid Review

BACKGROUND

Ultrasound (US) is a fundamental diagnostic tool in breast imaging. However, US remains an operator-dependent examination. Research into and the application of artificial intelligence (AI) in breast US are increasing. The aim of this rapid review was to assess the current development of US-based artificial intelligence in the field of breast cancer.

METHODS

Two investigators with experience in medical research performed literature searching and data extraction on PubMed. The studies included in this rapid review evaluated the role of artificial intelligence concerning BC diagnosis, prognosis, molecular subtypes of breast cancer, axillary lymph node status, and the response to neoadjuvant chemotherapy. The mean values of sensitivity, specificity, and AUC were calculated for the main study categories with a meta-analytical approach.

RESULTS

A total of 58 main studies, all published after 2017, were included. Only 9/58 studies were prospective (15.5%); 13/58 studies (22.4%) used an ML approach. The vast majority (77.6%) used DL systems. Most studies were conducted for the diagnosis or classification of BC (55.1%). At present, all the included studies showed that AI has excellent performance in breast cancer diagnosis, prognosis, and treatment strategy.

CONCLUSIONS

US-based AI has great potential and research value in the field of breast cancer diagnosis, treatment, and prognosis. More prospective and multicenter studies are needed to assess the potential impact of AI in breast ultrasound.

The prognostic significance of further axillary dissection for sentinel lymph node micrometastases in female breast cancer: A competing risk analysis using the SEER database

BACKGROUND

Sentinel lymph node (SLN) biopsy has been widely recognized as an excellent surgical and staging procedure for early-stage breast cancer, and its development has greatly improved the detection of micrometastases. However, the axillary treatment of micrometastasis has been the subject of much debate.

METHODS

We identified 427,131 women diagnosed with breast cancer from 2010 to 2018 in the Surveillance, Epidemiology, and End Results (SEER) database. Patients whose nodal status was micrometastases (pTxN1miM0) were classified into two groups: the SLNB only group and SLNB with complete ALND group, and we used these classifications to carry out propensity-score matching (PSM) analysis. The primary and secondary endpoints were OS and BCSS, respectively. We then implemented the Kaplan-Meier method and Cox proportional hazard model and used Fine and Gray competitive risk regression to identify factors associated with the risk of all-cause mortality.

RESULTS

After the PSM, 1,833 pairs were included in total. The SLNB with complete ALND showed no significant difference in OS (HR=1.04, 95% CI: 0.84-1.28, P=0.73) or BCSS (HR= 1.03, 95% CI: 0.79-1.35, P=0.82) compared to the SLNB only group, and axillary treatment was not associated with breast cancer-specific death (BCSD) (HR=1.13, 95% CI: 0.86-1.48, P=0.400) or other cause-specific death (OCSD) (HR=0.98, 95% CI:0.70-1.38, P=0.920). There was no statistically significant difference in the cumulative incidence of BCSD (Grey's test, P=0.819) or OCSD (Grey's test, P=0.788) for between the two groups either. For different molecular subtypes, patients in the SLNB only group showed no statistically significant differences from those in the SLNB with complete ALND group with Luminal A (HR=1.00, 95% CI:0.76-1.32, P=0.98) or Luminal B (HR=0.82, 95% CI:0.42-1.62, P=0.55) but similar OS to HER2-enriched (HR=1.58, 95% CI:0.81-3.07, P=0.19) or triple negative breast cancers (HR=1.18, 95% CI:0.76-1.81, P=0.46).

CONCLUSIONS

Our results suggest that in early breast cancer patients with micrometastasis, complete ALND does not seem to be required and that SLNB suffices to control locoregional and distant disease, with no significant adverse effects on survival compared to complete ALND.

Lymph Node Ratio in Head and Neck Cancer with Submental Flap Reconstruction

This study aimed to investigate the relationship between the lymph node ratio (LNR) and survival results of patients with head and neck squamous cell carcinoma (HNSCC) reconstructed by a submental artery flap (SMAF) to limit tumor size. This study retrospectively recruited 49 patients with HNSCC who underwent both primary resection and neck dissection with SMAF reconstruction. The LNR was the ratio of the number of metastatic lymph nodes to the sum number of examined lymph nodes. A LNR of 0.04 was the best cut-off value for HNSCC-specific death on receiver operating curve analysis. Patients with LNRs > 0.04 were univariately related to cancer-specific, disease-free, distant metastasis-free, and locoregional recurrence-free survival than those with LNRs ≤ 0.04 by log-rank test. In a Cox’s proportional hazards model with hazard ratio (HR) and 95% confidence interval (CI) adjusting for pathological stage, extranodal extension and or surgical margins, the LNR (>0.04/≤0.04) predicted multivariate shorter cancer-specific (HR = 9.24, 95% CI = 1.49−176), disease-free (HR = 3.44, 95% CI = 1.23−10.3), and distant metastasis-free (HR = 9.76, 95% CI = 1.57−187) survival. In conclusion, LNR for patients of HNSCC with SMAF reconstruction for limited tumor size was a prognostic factor for survival outcomes.

Long-term survival after sentinel lymph node biopsy or axillary lymph node dissection in pN0 breast cancer patients: a population-based study

PURPOSE

Findings from randomized clinical trials have shown that survival in patients with sentinel lymph node (SLN)-negative breast cancer is noninferior with SLN biopsy (SLNB) alone versus further axillary lymph node dissection (ALND). However, the long-term outcome of these two surgical approaches in pN0 breast cancer patients in real-world setting remains uncertain.

METHODS

We included patients diagnosed with pathologically staged T1-2N0M0 breast cancer between 2000 and 2015 in surveillance, epidemiology, and end results 18-registry database. Patients were considered to have undergone SLNB alone if they had ≤ 5 examined lymph nodes (ELNs), and ALND if they had ≥ 10 ELNs. The outcomes included overall survival (OS) and breast cancer-specific survival. Propensity score analyses by weighting and matching and multivariable Cox regression analysis were performed to minimize treatment selection bias.

RESULTS

We included 309,430 patients (253,501 SLNB and 55,929 ALND). In the weighted cohort, ALND was associated with significantly lower OS (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.10-1.16) and BCSS (HR 1.16; 95% CI 1.10-1.22) compared with SLNB alone. Both the propensity score-matching model and multivariable Cox model demonstrated a survival benefit for SLNB when compared with ALND. Subgroup analyses for key variables did not change these findings.

CONCLUSION

We found statistically significant differences in OS and BCSS between SLNB and ALND, though the magnitude of these differences was small. Our findings further support that SLNB alone should be the standard of care for patients who do not have metastatic lymph nodes identified during breast cancer surgery.

Prediction model of axillary lymph node status using automated breast ultrasound (ABUS) and ki-67 status in early-stage breast cancer

Background

Automated breast ultrasound (ABUS) is a useful choice in breast disease diagnosis. The axillary lymph node (ALN) status is crucial for predicting the clinical classification and deciding on the treatment of early-stage breast cancer (EBC) and could be the primary indicator of locoregional recurrence. We aimed to establish a prediction model using ABUS features of primary breast cancer to predict ALN status.

Methods

A total of 469 lesions were divided into the axillary lymph node metastasis (ALNM) group and the no ALNM (NALNM) group. Univariate analysis and multivariate analysis were used to analyze the difference of clinical factors and ABUS features between the two groups, and a predictive model of ALNM was established. Pathological results were as the gold standard.

Results

Ki-67, maximum diameter (MD), posterior feature shadowing or enhancement and hyperechoic halo were significant risk factors for ALNM in multivariate logistic regression analysis (P < 0.05). The four risk factors were used to build the predictive model, and it achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.791 (95% CI: 0.751, 0.831). The accuracy, sensitivity and specificity of the prediction model were 72.5%, 69.1% and 75.26%. The positive predictive value (PPV) and negative predictive value (NPV) were 66.08% and 79.93%, respectively. Distance to skin, MD, margin, shape, internal echo pattern, orientation, posterior features, and hyperechoic halo showed significant differences between stage I and stage II (P < 0.001).

Conclusion

ABUS features and Ki-67 can meaningfully predict ALNM in EBC and the prediction model may facilitate a more effective therapeutic schedule.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10034-3.

Deep Learning Mechanism for Predicting the Axillary Lymph Node Metastasis in Patients with Primary Breast Cancer

The second largest cause of mortality worldwide is breast cancer, and it mostly occurs in women. Early diagnosis has improved further treatments and reduced the level of mortality. A unique deep learning algorithm is presented for predicting breast cancer in its early stages. This method utilizes numerous layers to retrieve significantly greater amounts of information from the source inputs. It could perform automatic quantitative evaluation of complicated image properties in the medical field and give greater precision and reliability during the diagnosis. The dataset of axillary lymph nodes from the breast cancer patients was collected from Erasmus Medical Center. A total of 1050 images were studied from the 850 patients during the years 2018 to 2021. For the independent test, data samples were collected for 100 images from 95 patients at national cancer institute. The existence of axillary lymph nodes was confirmed by pathologic examination. The feed forward, radial basis function, and Kohonen self-organizing are the artificial neural networks (ANNs) which are used to train 84% of the Erasmus Medical Center dataset and test the remaining 16% of the independent dataset. The proposed model performance was determined in terms of accuracy (Ac), sensitivity (Sn), specificity (Sf), and the outcome of the receiver operating curve (Roc), which was compared to the other four radiologists' mechanism. The result of the study shows that the proposed mechanism achieves 95% sensitivity, 96% specificity, and 98% accuracy, which is higher than the radiologists' models (90% sensitivity, 92% specificity, and 94% accuracy). Deep learning algorithms could accurately predict the clinical negativity of axillary lymph node metastases by utilizing images of initial breast cancer patients. This method provides an earlier diagnostic technique for axillary lymph node metastases in patients with medically negative changes in axillary lymph nodes.

Isolated tumour cells in a sentinel lymph node of apparent early-stage ovarian cancer: Ultrastaging of all other 27 lymph nodes

•

Sentinel node is a promising possibility for retroperitoneal lymphatic staging in apparently early ovarian cancer.

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We describe a patient with Isolated tumor cells (ITCs) in one sentinel node with all the other nodes negative at ultrastaging.

•

It is likely that the technique of sentinel node in early ovarian cancer is able to identify the real lymphatic drainage of the ovary.

•

This report represents a proof of concept in support of the use of sentinel node in apparently early ovarian cancer.

Sentinel lymph node (SLN) biopsy in apparent early-stage ovarian cancer may spare the surgical staging with extensive retroperitoneal dissection and its associated morbidity. However, SLN biopsy in ovarian cancer is still experimental and under investigation. A 46-year-old post-menopausal woman with bilateral apparent stage IC1 endometrioid ovarian cancer underwent surgical staging by SLN biopsy and subsequent comprehensive laparoscopic pelvic and para-aortic lymphadenectomy. Out of 4 SLNs submitted to ultrastaging, one was positive for isolated tumour cells (ITCs). We submitted to ultra-staging all the other 24 pelvic and para-aortic non-SLNs, which were reported negative for disease. This is the first reported case of comprehensive lymphadenectomy after SLN biopsy with universal ultrastaging of all non-SLNs in ovarian cancer. The presence of ITCs in only one SLN, with all other 27 lymph nodes negative at ultrastaging, is consistent with the SLN concept and the assumption of a reliable lymphatic pathway in ovarian cancer.

Fast cross-staining alignment of gigapixel whole slide images with application to prostate cancer and breast cancer analysis

Joint analysis of multiple protein expressions and tissue morphology patterns is important for disease diagnosis, treatment planning, and drug development, requiring cross-staining alignment of multiple immunohistochemical and histopathological slides. However, cross-staining alignment of enormous gigapixel whole slide images (WSIs) at single cell precision is difficult. Apart from gigantic data dimensions of WSIs, there are large variations on the cell appearance and tissue morphology across different staining together with morphological deformations caused by slide preparation. The goal of this study is to build an image registration framework for cross-staining alignment of gigapixel WSIs of histopathological and immunohistochemical microscopic slides and assess its clinical applicability. To the authors' best knowledge, this is the first study to perform real time fully automatic cross staining alignment of WSIs with 40× and 20× objective magnification. The proposed WSI registration framework consists of a rapid global image registration module, a real time interactive field of view (FOV) localization model and a real time propagated multi-level image registration module. In this study, the proposed method is evaluated on two kinds of cancer datasets from two hospitals using different digital scanners, including a dual staining breast cancer data set with 43 hematoxylin and eosin (H&E) WSIs and 43 immunohistochemical (IHC) CK(AE1/AE3) WSIs, and a triple staining prostate cancer data set containing 30 H&E WSIs, 30 IHC CK18 WSIs, and 30 IHC HMCK WSIs. In evaluation, the registration performance is measured by not only registration accuracy but also computational time. The results show that the proposed method achieves high accuracy of 0.833 ± 0.0674 for the triple-staining prostate cancer data set and 0.931 ± 0.0455 for the dual-staining breast cancer data set, respectively, and takes only 4.34 s per WSI registration on average. In addition, for 30.23% data, the proposed method takes less than 1 s for WSI registration. In comparison with the benchmark methods, the proposed method demonstrates superior performance in registration accuracy and computational time, which has great potentials for assisting medical doctors to identify cancerous tissues and determine the cancer stage in clinical practice.

Update on sentinel node pathology in breast cancer

Pathologic examination of the sentinel lymph nodes (SLNs) in patients with breast cancer has been impacted by the publication of practicing changing trials over the last decade. With evidence from the ACOSOG Z0011 trial to suggest that there is no significant benefit to axillary lymph node dissection (ALND) in early-stage breast cancer patients with up to 2 positive SLNs, the rate of ALND, and in turn, intraoperative evaluation of SLNs has significantly decreased. It is of limited clinical significance to pursue multiple levels and cytokeratin immunohistochemistry to detect occult small metastases, such as isolated tumor cells and micrometastases, in this setting. Patients treated with neoadjuvant therapy, who represent a population with more extensive disease and aggressive tumor biology, were not included in Z0011 and similar trials, and thus, the evidence cannot be extrapolated to them. Recent trials have supported the safety and accuracy of sentinel lymph node biopsy (SLNB) in these patients when clinically node negative at the time of surgery. ALND remains the standard of care for any amount of residual disease in the SLNs and intraoperative evaluation of SLNs is still of value for real time surgical decision making. Given the potential prognostic significance of residual small metastases in treated lymph nodes, as well as the decreased false negative rate with the use of cytokeratin immunohistochemistry (IHC), it may be reasonable to maintain a low threshold for the use of cytokeratin IHC in post-neoadjuvant cases. Further recommendations for patients treated with neoadjuvant therapy await outcomes data from ongoing clinical trials. This review will provide an evidence-based discussion of best practices in SLN evaluation.

Longitudinal lymph node step-sectioning for the identification of metastatic disease in canine mast cell tumor

Lymph node (LN) metastasis in canine mast cell tumor (MCT) can affect prognosis and postsurgical treatment recommendations; however, routine histological single-section examination may underestimate the incidence of metastases. This prospective study aimed at determining whether longitudinal step-sectioning of the entire LN allows for a more reliable detection of metastases. Dogs with MCT undergoing resection of the primary tumor and regional lymphadenectomy were enrolled. Formalin-fixed LNs were bisected longitudinally, both halves were embedded in paraffin and histological sections prepared at 200 μm steps. The nodal mast cells were classified according to the Weishaar classification. First-section evaluation (FSE; ie, examination of the first section obtained from the blocks) and whole LN step-section evaluation (SSE) were compared. Fifty-eight LNs were included. The median number of sections per LN was 6 (range, 3–28). FSE with toluidine blue (TB) revealed 27 (47%) nonmetastatic (HN0), 14 (24%) premetastatic (HN1), 9 (15%) early metastatic (HN2), and 8 (14%) overtly metastatic (HN3) LNs. SSE with TB resulted in upgrading the LN status in 2 cases (HN2 to HN3; HN0 to HN1). Evaluation of the first section plus an additional step-section resulted in 100% accuracy. Compared with SSE with TB, the accuracy of FSE with HE was 98% for HN3 LNs and 74% for HN2 LNs. FSE appears to reliably allow for the detection of LN metastasis in MCT, although examination of a further parallel section at a 200 μm step may increase the accuracy. A metachromatic stain is recommended for the identification of early metastases.

Deep learning prediction of axillary lymph node status using ultrasound images

OBJECTIVE

To investigate the ability of our convolutional neural network (CNN) to predict axillary lymph node metastasis using primary breast cancer ultrasound (US) images.

METHODS

In this IRB-approved study, 338 US images (two orthogonal images) from 169 patients from 1/2014-12/2016 were used. Suspicious lymph nodes were seen on US and patients subsequently underwent core-biopsy. 64 patients had metastatic lymph nodes. A custom CNN was utilized on 248 US images from 124 patients in the training dataset and tested on 90 US images from 45 patients. The CNN was implemented entirely of 3 × 3 convolutional kernels and linear layers. The 9 convolutional kernels consisted of 6 residual layers, totaling 12 convolutional layers. Feature maps were down-sampled using strided convolutions. Dropout with a 0.5 keep probability and L2 normalization was utilized. Training was implemented by using the Adam optimizer and a final SoftMax score threshold of 0.5 from the average of raw logits from each pixel was used for two class classification (metastasis or not).

RESULTS

Our CNN achieved an AUC of 0.72 (SD ± 0.08) in predicting axillary lymph node metastasis from US images in the testing dataset. The model had an accuracy of 72.6% (SD ± 8.4) with a sensitivity and specificity of 65.5% (SD ± 28.6) and 78.9% (SD ± 15.1) respectively. Our algorithm is available to be shared for research use. (https://github.com/stmutasa/MetUS).

CONCLUSION

It's feasible to predict axillary lymph node metastasis from US images using a deep learning technique. This can potentially aid nodal staging in patients with breast cancer.

Thorny ground, rocky soil: Tissue-specific mechanisms of tumor dormancy and relapse

Disseminated tumor cells (DTCs) spread systemically yet distinct patterns of metastasis indicate a range of tissue susceptibility to metastatic colonization. Distinctions between permissive and suppressive tissues are still being elucidated at cellular and molecular levels. Although there is a growing appreciation for the role of the microenvironment in regulating metastatic success, we have a limited understanding of how diverse tissues regulate DTC dormancy, the state of reversible quiescence and subsequent awakening thought to contribute to delayed relapse. Several themes of microenvironmental regulation of dormancy are beginning to emerge, including vascular association, co-option of pre-existing niches, metabolic adaptation, and immune evasion, with tissue-specific nuances. Conversely, DTC awakening is often associated with injury or inflammation-induced activation of the stroma, promoting a proliferative environment with DTCs following suit. We review what is known about tissue-specific regulation of tumor dormancy on a tissue-by-tissue basis, profiling major metastatic organs including the bone, lung, brain, liver, and lymph node. An aerial view of the barriers to metastatic growth may reveal common targets and dependencies to inform the therapeutic prevention of relapse.

Distribution pattern and pathologic analysis of metastatic sentinel and non-sentinel lymph nodes in lymphatic basin dissection for clinical T2/T3 oral cancer with clinical N0 status

OBJECTIVE

The localization pattern of metastatic sentinel lymph node (SN) and non-SNs and pathologic analysis of metastatic lymph nodes in SN lymphatic basin dissection (SLBD) were investigated in patients with cT2/T3cN0 oral squamous cell carcinoma (OSCC).

METHODS

This prospective multicenter trial involved 10 institutions nationwide in Japan. A total of 57 patients were enrolled. The lateral neck was divided into 5 lymphatic basins. The lymphatic basin containing SNs was defined as the SN lymphatic basin. All patients underwent SLBD with backup selective neck dissection (I-III) combined with primary tumor removal. When SNs were found outside of levels I-III, including in the contralateral neck, SLBD was performed by removing the compartments containing SNs separately. SN metastasis was classified as isolated tumor cells (ITCs), micrometastasis, or macrometastasis. ITCs are defined as a lesion no larger than 0.2 mm in largest dimension and are classified as pN0.

RESULTS

SN metastasis was observed in 22 cases. All metastatic lymph nodes, including false-negative cases, were detected in the SN lymphatic basin. Isolated tumor cells in the SNs did not affect prognosis, whereas micrometastasis tended to have poor prognosis. After adjusting for other risk factors, a positive SN remained a significant predictor of poor 5-year overall survival in pT2-4 OSCC.

CONCLUSION

SLBD for intraoperative SN biopsy is a sufficient therapeutic procedure and is valuable for determining pathologic nodal stage in OSCC. SN positivity was demonstrated to be an independent predictor of poor prognosis in patients with pT2-4 disease undergoing SLBD with backup selective neck dissection (I-III).

Prognostic impact of lymph node harvest for patients with node-negative esophageal squamous cell carcinoma: a large-scale multicenter study

Background

We examined the association between the number of resected lymph nodes and survival to determine the optimal lymphadenectomy for thoracic esophageal squamous cell carcinoma (ESCC) patients with negative lymph node.

Methods

We included 1,836 patients from Chinese three high-volumed hospitals with corresponding clinicopathological characters such as gender, age, tumor location, tumor grade and TNM stage of patients. The median follow-up of included patients was 45.7 months (range, 1.03-117.3 months). X-Tile plot was used to identify the lowest number of lymphadenectomy. The multivariate model's construction was in use of parameters with clinical significance for survival and a nomogram based on clinical variable with P<0.05 in Cox regression analysis. Both two models were validated using a cohort extracted from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database between 1975 and 2016 (n=951).

Results

More lymphadenectomy numbers were significantly associated with better survival in patients both in training cohort [hazard ratio (HR) =0.980; 95% confidence interval (CI): 0.971-0.988; P<0.001] and validation cohort (HR =0.980; 95% CI: 0.968-0.991; P=0.001). Cut-off point analysis determined the lowest number of 9 for thoracic ESCC patients in N0 stage through training cohort (C-index: 0.623; sensitivity: 80.7%; 1 - specificity: 72.5%) when compared with 10 in validation cohort (C-index: 0.643; sensitivity: 78.2%; 1 - specificity: 63.0%). The cut-off points of 9 were examined in training cohort and validated in the divided cohort from validation cohort (all P<0.05). Meanwhile, nomograms for both cohorts were constructed and the calibration curves for both cohorts agreed well with the actual observations in terms of predicting 3- and 5-year survival, respectively.

Conclusions

Larger number for lymphadenectomy was associated with better survival in thoracic ESCC patients in N0 stage. Nine was what we got as the lowest number for lymphadenectomy in pN0 ESCC patients through this study, and our result should be confirmed further.

Should the management of radiation therapy for breast cancer be standardized? Results of a survey on current French practices in breast radiotherapy

Background

Breast cancer is the most frequent cancer in women in France. Its management has evolved considerably in recent years with a focus on reducing iatrogenic toxicity. The radiotherapy indications are validated in multidisciplinary consultation meetings; however, questions remain outstanding, particularly regarding hypofractionated radiotherapy, partial breast irradiation, and irradiation of the internal mammary chain and axillary lymph node area.

Materials and methods

An online survey was sent to 47 heads of radiotherapy departments in France. The survey consisted of 22 questions concerning indications for irradiation of the supraclavicular, internal mammary and axillary lymph node areas; irradiation techniques and modalities; prescribed doses; and fractionation.

Results

Twenty-four out of 47 centers responded (response rate of 51%). This survey demonstrated a wide variation in the prescribed dose regimen, monoisocentric radiotherapy, and indications of irradiation of the lymph node areas.

Conclusion

This survey provides insight into the current radiotherapy practice for breast cancer in France. It shows the need to standardize practices.

Omitting SLNB in Breast Cancer: Is a Nomogram the Answer?

BACKGROUNDS

Sentinel lymph node biopsy (SLNB) is standard care as a staging procedure in patients with invasive breast cancer. The axillary recurrence rate, even after positive SLNB, is low. This raises serious doubts regarding the clinical value of SLNB in early breast cancer. The purpose of this study is to select patients with low suspected axillary burden in whom SLNB might be omitted.

PATIENTS AND METHODS

We retrospectively analyzed 2015 primary breast cancer patients between 2007 and 2015, with 982 patients allocated to the training and 961 to the validation cohort. Variables associated with nodal disease were analyzed and used to build a nomogram for predicting nodal disease.

RESULTS

A total of 32.8% of patients had macrometastatic disease. A predictive model was constructed based on age, cN0, morphology, grade, multifocality, and tumor size with an area under the receiver operating characteristic curve (AUC) of 0.83. Considering a false-negative rate of 5%, 32.8% of patients could be spared axillary surgery. In a subanalysis of patients with relatively favorable characteristics, 26.8% had less than 5% chance of macrometastases.

CONCLUSIONS

We present a model with excellent predictive value that can select one-third of patients in whom SLNB is deemed not necessary because of less than 5% chance of nodal involvement. Whether missing 1 in 20 patients with macrometastatic disease is worthwhile balanced against preventing side-effects of the SLN procedure remains to be established. A number of ongoing large prospective trials evaluating the outcome of omitting SLNB are awaited. Meanwhile, this nomogram may be used for individual decision-making.

Prognostic significance of occult lymph node metastases in breast cancer: a meta-analysis

Background

Occult metastases in axillary lymph nodes have been reported to be associated with poor prognosis in patients with breast cancer. However, studies on the prognostic value of occult metastases have shown controversial results. This meta-analysis aimed to evaluate the prognostic significance of occult lymph node metastases in breast cancer.

Methods

Studies published until May, 2020, which retrospectively examined negative lymph nodes by stepsectioning and/or immunohistochemistry, were retrieved from MEDLINE, EMBASE, CNKI, and Cochrane Library databases. The pooled Relative Risk (RR) with 95% confidence interval (95% CI) for overall survival (OS) and disease-free survival (DFS) were calculated to examine the associations between occult metastases and prognosis.

Results

Patients with occult metastases in axillary lymph nodes had poorer five-year DFS (RR = 0.930; 95% CI = 0.907–0.954) and OS (RR = 0.972; 95% CI = 0.954–0.990). Furthermore, the DFS (RR = 0.887; 95% CI = 0.810–0.972) and OS (RR = 0.896; 95% CI = 0.856–0.939) of patients with occult metastases were significantly lower after a ten-year follow-up.

Conclusions

Occult metastases in the axillary lymph nodes are associated with poorer DFS andOS of patients with breast cancer. Occult metastases might serve as a predictive factor of survival outcomes in patients with breast cancer.