Influence of Anatomic Locations of T1b Melanomas and Patient Age on Outcomes.

BACKGROUND: There are no guidelines on when to more strongly recommend sentinel lymph node biopsy (SLNB) for T1b melanomas. OBJECTIVE: To examine whether anatomic locations of T1b melanomas and patient age influence metastases. METHODS: We conducted a retrospective study using data from two hospitals in Los Angeles County from January 2010 through January 2020. RESULTS: Out of 620 patients with primary melanomas, 566 melanomas were staged based on the American Joint Committee on Cancer 8th edition melanoma staging. Forty-one were T1b, of which 13 were located on the face/ear/scalp and 28 were located elsewhere. T1b melanomas located on the face/ear/scalp had an increased risk of lymph node or distant metastasis compared with other anatomic sites (31% vs 3.6%, P=0.028). For all melanomas, the risk of lymph node or distant metastasis decreased with age of 64 years or greater (P<0.001 and P=0.034). For T1b melanomas, the risk of distant metastasis increased with increasing age (P=0.047). LIMITATIONS: Data were from a single county.  Conclusion: T1b melanomas of the face/ear/scalp demonstrated a higher risk of lymph node or distant metastasis and may help guide the recommendation of SLNB, imaging, and surveillance. Younger patients may be more strongly considered for SLNB and older patients with T1b melanomas may warrant imaging.  J Drugs Dermatol. 2024;23(5):306-310. doi:10.36849/JDD.7667.

Comparison of Intraoperative Imprint Cytology versus Frozen Section for Sentinel Lymph Node Evaluation in Breast Cancer. A study along with Systematic Review and Meta-analysis of literature.

BACKGROUND: Sentinel lymph node (SLN) is the first lymph node to drain the lymph from a particular region involved by cancer. The commonly performed intraoperative methods for SLN evaluation are touch imprint cytology (TIC) and frozen section (FS). The present study aimed to determine the sensitivity, specificity and accuracy of TIC and FS with histopathological diagnosis as gold standard. MATERIALS AND METHODS: The nodes were bissected along their long axis and wet surface was imprinted on to clean glass slides followed by toluidine blue and rapid Papanicolaou staining. Subsequently the lymph node slices were cut at three levels using the cryostat machine and stained with Hematoxylin and eosin stain. The cytological and FS findings were compared and the specificity, sensitivity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of TIC and FS was evaluated taking histopathological diagnosis as gold standard. In addition, pooled sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy for touch imprint cytology and frozen section were assessed for the studies included in the meta-analysis. RESULTS: The specificity, sensitivity, diagnostic accuracy, positive predictive value and negative predictive value of touch imprint cytology were 100%, 88.2%, 90%, 100% and 60% respectively. The specificity, sensitivity, diagnostic accuracy, PPV and NPV of frozen section were 100%, 94.1%, 95%, 100% and 75% respectively. The sensitivity of TIC and FS for detection of micrometastasis was 60% and 80% respectively. The pooled sensitivity and specificity for touch imprint cytology were 85.24% (95% CI, 83.46%-86.90%), and 98.99% (95% CI, 98.69%-99.23%) respectively. The pooled sensitivity and specificity for frozen section examination were 90.45% (95% CI, 85.15%-94.34%), and 100% (95% CI, 99.24%-100%) respectively. CONCLUSION: Even though the sensitivity of FS was better than imprint cytology in detection of micrometastasis, TIC is a rapid inexpensive technique which can be utilized in remote areas in absence of cryostat machine. The sensitivity of the two techniques with respect to detection of macrometastasis was comparable. This meta-analysis highlights the accuracy of the touch imprint cytology and frozen section examination in the intra-operative detection of malignancy in breast cancer.

Association between lymph node ratio and survival outcomes in patients with oral squamous cell carcinoma.

BACKGROUND: Recent reports have shown that the Lymph node ratio (LNR) is useful for predicting the prognosis in some cancers, however there are few reports on the usefulness of LNR in predicting the prognosis of oral squamous cell carcinoma (OSCC). The predictive value of LNR for prognosis of OSCC was investigated. MATERIALS AND METHODS: The study included 152 patients with OSCC and histologically confirmed cervical lymph node metastasis who underwent neck dissection. We analyzed the relationship between LNR and overall survival (OS) and recurrence-free survival (RFS) retrospectively in these cases, with the relationship between prognosis and clinicopathological findings also examined. RESULTS: Using a receiver operating characteristics curve, the LNR cutoff value was set at 0.095, categorizing 64 and 88 cases into high LNR (≥ 0.095) and low LNR (< 0.095) groups, respectively. Regarding OS and RFS, the prognosis was significantly worse in the high LNR group compared with the low LNR group. In multivariate analysis, sex, postoperative nodal stage, and LNR merged as independent prognostic factors. CONCLUSION: This study's findings suggest that LNR may represent a prognostic indicator in OSCC with cervical lymph node metastasis.

[Fluorescence lymphography for sentinal lymph node biopsy in breast cancer]. / Sobstvennyi opyt primeneniya flyuorestsentnoi limfografii dlya biopsii signal'nykh limfouzlov pri rake molochnoi zhelezy.

OBJECTIVE: To study diagnostic value of fluorescence lymphography for sentinel lymph node biopsy in breast cancer. MATERIAL AND METHODS: The study enrolled 25 patients with breast cancer T1-2N0-1M0 between March 2023 and July 2023. Eight ones underwent neoadjuvant chemotherapy. In 3 patients, morphologically verified metastases cN1 in axillary lymph nodes regressed after treatment. After sentinel lymph node biopsy, all patients underwent standard axillary lymphadenectomy. Subareolar injection of indocyanine green 1 ml (5 mg/ml) was performed immediately before surgery. Fluorescence imaging was performed using the MARS system. RESULTS: Detection rate was 100%. Mean number of sentinel lymph nodes was 2. Metastatic lesions of sentinel lymph nodes were observed in 6 patients (24%) with micro-metastases in 2 cases. In 50% of cases, metastatic lesion did not extend beyond sentinel lymph nodes. False negative result was obtained in 1 (4%) patient. Mean number of metastases was 1.8 (max 3 in one patient). CONCLUSION: Sentinel lymph node biopsy with fluorescence lymphography is a sensitive method. The advantages of this technique are visualization of subcutaneous lymphatic vessels and skin incision for access to sentinel lymph nodes, as well as visualization of sentinel lymph nodes after skin incision.

The diagnostic value of GICA used for intraoperative lymph node FNA-Tg measurement to evaluate thyroid cancer metastases.

Objective: It is crucial to diagnose lymph node (LN) metastases (LNM) before or during thyroid carcinoma surgery. Measurement of thyroglobulin (Tg) in the fine needle aspirate washout (FNA-Tg) is useful to assist in the diagnosis of LNM for papillary thyroid carcinoma (PTC). This study aimed to assess the diagnostic performance of a new technique based on a colloidal gold-based immunochromatographic assay (GICA) for intraoperative FNA-Tg in diagnosing LNM. Clinical trial information: This study is registered with chictr.org.cn, ID: ChiCTR2200063561 (registered 11 September, 2022). Methods: This prospective study enrolled 51 PTC patients who underwent cervical LN dissection. A total of 150 LNs dissected from the central and lateral compartments were evaluated by FNA-Tg-GICA at three different time points and compared with frozen sections and the conventional Tg measurement method electrochemiluminescence immunoassay (ECLIA). Receiver operating characteristic curve (ROC) and area under the curve (AUC), cutoff value to discriminate benign and malignant LNs, sensitivity, specificity, and accuracy were provided. Results: The cutoff value of FNA-Tg to predict LNM was 110.83 ng/mL for ECLIA and 13.19 ng/mL, 38.69 ng/mL, and 77.17 ng/mL for GICA at 3, 10, and 15 min, respectively. There was no significant difference between the AUCs of GICA at different time points compared to using ECLIA and frozen sections. Besides, the diagnostic performance of GICA and ECLIA showed no significant difference in evaluating LNM from central and lateral compartments or between the TgAb-positive subgroup and TgAb-negative subgroup. Conclusion: GICA is a promising method for intraoperative FNA-Tg measurement and has high value in predicting LNM. It may be a novel alternative or supplementary method to frozen section or ECLIA.

Diagnostic Accuracy of Highest-Grade or Predominant Histological Differentiation of T1 Colorectal Cancer in Predicting Lymph Node Metastasis: A Systematic Review and Meta-Analysis.

INTRODUCTION: Treatment guidelines for colorectal cancer (CRC) suggest 2 classifications for histological differentiation-highest grade and predominant. However, the optimal predictor of lymph node metastasis (LNM) in T1 CRC remains unknown. This systematic review aimed to evaluate the impact of the use of highest-grade or predominant differentiation on LNM determination in T1 CRC. METHODS: The study protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO, registration number: CRD42023416971) and was published in OSF ( https://osf.io/TMAUN/ ) on April 13, 2023. We searched 5 electronic databases for studies assessing the diagnostic accuracy of highest-grade or predominant differentiation to determine LNM in T1 CRC. The outcomes were sensitivity and specificity. We simulated 100 cases with T1 CRC, with an LNM incidence of 11.2%, to calculate the differences in false positives and negatives between the highest-grade and predominant differentiations using a bootstrap method. RESULTS: In 42 studies involving 41,290 patients, the differentiation classification had a pooled sensitivity of 0.18 (95% confidence interval [CI] 0.13-0.24) and 0.06 (95% CI 0.04-0.09) ( P < 0.0001) and specificity of 0.95 (95% CI 0.93-0.96) and 0.98 (95% CI 0.97-0.99) ( P < 0.0001) for the highest-grade and predominant differentiations, respectively. In the simulation, the differences in false positives and negatives between the highest-grade and predominant differentiations were 3.0% (range 1.6-4.4) and -1.3% (range -2.0 to -0.7), respectively. DISCUSSION: Highest-grade differentiation may reduce the risk of misclassifying cases with LNM as negative, whereas predominant differentiation may prevent unnecessary surgeries. Further studies should examine differentiation classification using other predictive factors.

Malignant phyllodes tumour with lymph node metastasis: a diagnostic conundrum resolved by next generation DNA sequencing.

A malignant neoplasm with spindle cell and chondroid differentiation in the breast, metastatic to lymph node. In this context, a metaplastic carcinoma is typically favored given the exceptional nature of lymph node metastases in malignant phyllodes tumors (MPT). However, we demonstrate pathognomonic hotspot mutations in MED12 and the promoter of the TERT gene by targeted next-generation DNA sequencing, supporting a diagnosis of MPT.

Fine-needle aspiration biopsy of axillary lymph nodes: A reliable diagnostic tool for breast cancer staging.

BACKGROUND: Pathologic evaluation of sentinel lymph node biopsy (SLNB) samples is crucial for axillary staging in patients newly diagnosed with breast cancer. Patients with pathologic evidence of nodal metastasis scheduled for upfront surgery typically also undergo axillary lymph node dissection (ALND). Although SLNB is the gold standard method for detecting nodal metastasis, axillary lymph node fine-needle aspiration biopsy (FNAB) utility has not been thoroughly explored. METHODS: Ultrasound-guided axillary lymph node FNAB samples along with concurrent ipsilateral breast tissue samples were searched and reviewed. The control group included histologic findings of axillary dissection or intraoperative SLNB results. RESULTS: A total of 354 axillary lymph node FNAB samples with matched histology were included. Of these, 187 (52.8%) were positive for metastatic carcinoma of breast origin; 143 (40.4%) were negative for metastasis; 12 (3.4%) showed atypical cells; six (1.7%) were suspicious for metastasis; and six (1.7%) were nondiagnostic because of a lack of lymphoid tissue and malignant cells. Of the 143 negative FNAB samples, 22 (15.4%) were positive on either intraoperative SLNB or ALND. When only the positive and negative FNAB samples were accounted for (n = 330; 93.2%), overall diagnostic sensitivity and specificity were 89.4% and 99.2%, respectively. CONCLUSIONS: Although axillary SLNB is the standard procedure for detecting nodal metastasis of breast origin, axillary lymph node FNAB appears to be a suitable alternative in a significant proportion of patients. A standard SLNB should be performed in cases of negative axillary lymph node FNAB findings, particularly nodes with abnormal imaging findings.

Diagnostic value of thyroglobulin washout in fine-needle aspiration samples for diagnosis and follow-up of differentiated thyroid cancer.

Our goal was to assess the effectiveness of fine-needle aspiration thyroglobulin (FNA-Tg) in detecting malignant lymph nodes (LNs) in patients with differentiated thyroid cancer (DTC). We also aimed to determine the factors that affect the accuracy of FNA-Tg. We conducted a retrospective cohort study using the laboratory, ultrasonographic, histopathological, FNA cytology (FNA-C), and FNA-Tg results of 176 DTC patients. We used receiver operating characteristic analysis to identify the cutoff value of FNA-Tg, and binary regression analysis to compare FNA-Tg with other diagnostic parameters. Spearman correlation was utilized to identify factors that influence FNA-Tg. Our study revealed that a cutoff value of 3.14 ng/mL for FNA-Tg had a sensitivity of 91.8% and a specificity of 96.6% in detecting malignant LNs in the entire group. In the subgroup with thyroid tissue, the optimal cutoff value for FNA-Tg was determined to be 15.5 ng/mL. Additionally, FNA-C had a sensitivity of 82.4% and a specificity of 99.4% for the entire group. The combined use of FNA-Tg and FNA-C yielded a sensitivity of 100% and a specificity of 96%, which was found to be more effective than using either test alone. Serum Tg positivity and serum thyroid-stimulating hormone were positively correlated with FNA-Tg levels in detecting malignant LNs. Our study demonstrated that FNA-Tg is a reliable method for detecting LN metastases in DTC patients, with a 3.14 ng/mL cutoff value. However, each center should take into account factors such as serum thyroid-stimulating hormone, serum Tg, and the presence of thyroid tissue when interpreting FNA-Tg results and determining the appropriate cutoff level.

Contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC).

INTRODUCTION: The main objective of this study was to evaluate the contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC) and to advance a diagnostic threshold value for SUVmax in carcinomatous cervical lymph node. METHODS: 47 patients with OCSCC and suspicious cervical lymph node involvement (cN+) on FDG-PET were included in this retrospective study. The primary outcome was cervical lymph node SUVmax based on histological cervical metastatic disease (« gold standard ¼). RESULTS: Among the 77 cervical lymph nodes considered suspicious on patients' FDG-PET, 50 were really metastatic on histological examination. The lymph node SUVmax with metastatic involvement on histological examination was 4.6 ± 3.9 [2.6 - 23.7] versus 3.6 ± 1.2 [2 - 7.3] without carcinomatous involvement (p = 0.004). The lymph node size was not statistically significant according to metastatic disease (p = 0.28). DISCUSSION: A cervical lymph node SUVmax value of less than 2.6 on FDG-PET would suggest non-metastatic lymph node involvement. Supra Omohyoid Neck Dissection (SOHND) could therefore be performed in OCSCC when the SUVmax of the cervical lymph node is below this value in order to reduce the surgical morbidity of dissection of the lower internal jugular chain (Level IV).

A nomogram for preoperative differentiation of tumor deposits from lymph node metastasis in rectal cancer: A retrospective study.

The objective is to develop and validate a combined model for noninvasive preoperative differentiating tumor deposits (TDs) from lymph node metastasis (LNM) in patients with rectal cancer (RC). A total of 204 patients were enrolled and randomly divided into 2 sets (training and validation set) at a ratio of 8:2. Radiomics features of tumor and peritumor fat were extracted by using Pyradiomics software from the axial T2-weighted imaging of MRI. Rad-score based on extracted Radiomics features were calculated by combination of feature selection and the machine learning method. Factors (Rad-score, laboratory test factor, clinical factor, traditional characters of tumor on MRI) with statistical significance were integrated to build a combined model. The combined model was visualized by a nomogram, and its distinguish ability, diagnostic accuracy, and clinical utility were evaluated by the receiver operating characteristic curve (ROC) analysis, calibration curve, and clinical decision curve, respectively. Carbohydrate antigen (CA) 19-9, MRI reported node stage (MRI-N stage), tumor volume (cm3), and Rad-score were all included in the combined model (odds ratio = 3.881 for Rad-score, 2.859 for CA19-9, 0.411 for MRI-N stage, and 1.055 for tumor volume). The distinguish ability of the combined model in the training and validation cohorts was area under the summary receiver operating characteristic curve (AUC) = 0.863, 95% confidence interval (CI): 0.8-0.911 and 0.815, 95% CI: 0.663-0.919, respectively. And the combined model outperformed the clinical model in both training and validation cohorts (AUC = 0.863 vs 0.749, 0.815 vs 0.627, P = .0022, .0302), outperformed the Rad-score model only in training cohorts (AUC = 0.863 vs 0.819, P = .0283). The combined model had highest net benefit and showed good diagnostic accuracy. The combined model incorporating Rad-score and clinical factors could provide a preoperative differentiation of TD from LNM and guide clinicians in making individualized treatment strategy for patients with RC.

Sentinel lymph node assessment in melanoma: current state and future directions.

Assessment of sentinel lymph node status is an important step in the evaluation of patients with melanoma for both prognosis and therapeutic management. Pathologists have an important role in this evaluation. The methodologies have varied over time, from the evaluation of dimensions of metastatic burden to determination of the location of the tumour deposits within the lymph node to precise cell counting. However, no single method of sentinel lymph node tumour burden measurement can currently be used as a sole independent predictor of prognosis. The management approach to sentinel lymph node-positive patients has also evolved over time, with a more conservative approach recently recognised for selected cases. This review gives an overview of past and current status in the field with a glimpse into future directions based on prior experiences and clinical trials.

Identify the Clinicopathological Characteristics of Lung Carcinoma Patients Being False Negative in Folate Receptor Based Circulating Tumor Cell Detection.

In lung cancer diagnosis, folate receptor (FR)-based circulating tumor cell (CTC) has shown its ability to distinguish malignancy from benign disease to some extent. However, there are still some patients that cannot be identified by FR-based CTC detection. And studies comparing the characteristics between true positive (TP) and false negative (FN) patients are few. Thus, the study comprehensively analyzes the clinicopathological characteristics of FN and TP patients in the current study. According to inclusion and exclusion criteria, 3420 patients are enrolled. Combining the pathological diagnosis with CTC results, patients are divided into FN and TP groups, and clinicopathological characteristics are compared between two groups. Compared with TP patients, FN patients have smaller tumor, early T stage, early pathological stage, and without lymph node metastasis. Epidermal growth factor receptor (EGFR) mutation status is different between FN and TP group. And this result is also demonstrated in lung adenocarcinoma subgroup but not in lung squamous cell carcinoma subgroup. Tumor size, T stage, pathological stage, lymph node metastasis, and EGFR mutation status may influence the accuracy of FR-based CTC detection in lung cancer. However, further prospective studies are needed to confirm the findings.

Artificial Intelligence-Aided Diagnosis of Breast Cancer Lymph Node Metastasis on Histologic Slides in a Digital Workflow.

Identifying lymph node (LN) metastasis in invasive breast carcinoma can be tedious and time-consuming. We investigated an artificial intelligence (AI) algorithm to detect LN metastasis by screening hematoxylin and eosin (H&E) slides in a clinical digital workflow. The study included 2 sentinel LN (SLN) cohorts (a validation cohort with 234 SLNs and a consensus cohort with 102 SLNs) and 1 nonsentinel LN cohort (258 LNs enriched with lobular carcinoma and postneoadjuvant therapy cases). All H&E slides were scanned into whole slide images in a clinical digital workflow, and whole slide images were automatically batch-analyzed using the Visiopharm Integrator System (VIS) metastasis AI algorithm. For the SLN validation cohort, the VIS metastasis AI algorithm detected all 46 metastases, including 19 macrometastases, 26 micrometastases, and 1 with isolated tumor cells with a sensitivity of 100%, specificity of 41.5%, positive predictive value of 29.5%, and negative predictive value (NPV) of 100%. The false positivity was caused by histiocytes (52.7%), crushed lymphocytes (18.2%), and others (29.1%), which were readily recognized during pathologists' reviews. For the SLN consensus cohort, 3 pathologists examined all VIS AI annotated H&E slides and cytokeratin immunohistochemistry slides with similar average concordance rates (99% for both modalities). However, the average time consumed by pathologists using VIS AI annotated slides was significantly less than using immunohistochemistry slides (0.6 vs 1.0 minutes, P = .0377). For the nonsentinel LN cohort, the AI algorithm detected all 81 metastases, including 23 from lobular carcinoma and 31 from postneoadjuvant chemotherapy cases, with a sensitivity of 100%, specificity of 78.5%, positive predictive value of 68.1%, and NPV of 100%. The VIS AI algorithm showed perfect sensitivity and NPV in detecting LN metastasis and less time consumed, suggesting its potential utility as a screening modality in routine clinical digital pathology workflow to improve efficiency.

The Hunt for Lymph Nodes: Is Total Submission of Standard-Template and Extended-Template Pelvic Lymph Node Dissections Necessary for Detecting Metastatic Prostate Cancer?

CONTEXT.­: There are no consensus guidelines on submission of pelvic lymph node dissection (PLND) specimens for radical prostatectomies. Complete submission is only performed by a minority of laboratories. Our institution has been following this practice for standard-template and extended-template PLND. OBJECTIVE.­: To investigate the utility of total submission of PLND specimens for prostate cancer and understand its impact on patients and the laboratory. DESIGN.­: Retrospective study examining 733 cases of radical prostatectomies with PLND performed at our institution. Reports and slides with positive lymph nodes (LNs) were reviewed. Data on LN yield, cassette usage, and impact of submission of remaining fat after dissection of grossly identifiable LNs were assessed. RESULTS.­: Most cases involved submission of extra cassettes for remaining fat (97.5%, n = 697 of 715). Extended PLND yielded a higher mean number of total and positive LNs versus standard PLND (P < .001). However, extended PLND required significantly more cassettes for remaining fat (mean, 8; range, 0-44). There was poor correlation between number of cassettes submitted for PLND with total and positive LN yield and between remaining fat with LN yield. Most positive LNs were grossly identified (88.5%, n = 139 of 157) and were typically larger than those not. Only 4 cases (0.6%, n = 4 of 697) would have been understaged without complete submission of PLND. CONCLUSIONS.­: Total submission of PLND increases detection of metastasis and LN yield yet increases workload significantly with only minimal patient management impact. Hence, we recommend that meticulous gross identification and submission of all LNs be pursued without the need to submit the remaining fat of PLND.

Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node metastases diagnostic model (LNMDM) on whole slide images and to assess the clinical effect of an artificial intelligence-assisted (AI) workflow. METHODS: In this retrospective, multicentre, diagnostic study in China, we included consecutive patients with bladder cancer who had radical cystectomy and pelvic lymph node dissection, and from whom whole slide images of lymph node sections were available, for model development. We excluded patients with non-bladder cancer and concurrent surgery, or low-quality images. Patients from two hospitals (Sun Yat-sen Memorial Hospital of Sun Yat-sen University and Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China) were assigned before a cutoff date to a training set and after the date to internal validation sets for each hospital. Patients from three other hospitals (the Third Affiliated Hospital of Sun Yat-sen University, Nanfang Hospital of Southern Medical University, and the Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China) were included as external validation sets. A validation subset of challenging cases from the five validation sets was used to compare performance between the LNMDM and pathologists, and two other datasets (breast cancer from the CAMELYON16 dataset and prostate cancer from the Sun Yat-sen Memorial Hospital of Sun Yat-sen University) were collected for a multi-cancer test. The primary endpoint was diagnostic sensitivity in the four prespecified groups (ie, the five validation sets, a single-lymph-node test set, the multi-cancer test set, and the subset for a performance comparison between the LNMDM and pathologists). FINDINGS: Between Jan 1, 2013 and Dec 31, 2021, 1012 patients with bladder cancer had radical cystectomy and pelvic lymph node dissection and were included (8177 images and 20 954 lymph nodes). We excluded 14 patients (165 images) with concurrent non-bladder cancer and also excluded 21 low-quality images. We included 998 patients and 7991 images (881 [88%] men; 117 [12%] women; median age 64 years [IQR 56-72]; ethnicity data not available; 268 [27%] with lymph node metastases) to develop the LNMDM. The area under the curve (AUC) for accurate diagnosis of the LNMDM ranged from 0·978 (95% CI 0·960-0·996) to 0·998 (0·996-1·000) in the five validation sets. Performance comparisons between the LNMDM and pathologists showed that the diagnostic sensitivity of the model (0·983 [95% CI 0·941-0·998]) substantially exceeded that of both junior pathologists (0·906 [0·871-0·934]) and senior pathologists (0·947 [0·919-0·968]), and that AI assistance improved sensitivity for both junior (from 0·906 without AI to 0·953 with AI) and senior (from 0·947 to 0·986) pathologists. In the multi-cancer test, the LNMDM maintained an AUC of 0·943 (95% CI 0·918-0·969) in breast cancer images and 0·922 (0·884-0·960) in prostate cancer images. In 13 patients, the LNMDM detected tumour micrometastases that had been missed by pathologists who had previously classified these patients' results as negative. Receiver operating characteristic curves showed that the LNMDM would enable pathologists to exclude 80-92% of negative slides while maintaining 100% sensitivity in clinical application. INTERPRETATION: We developed an AI-based diagnostic model that did well in detecting lymph node metastases, particularly micrometastases. The LNMDM showed substantial potential for clinical applications in improving the accuracy and efficiency of pathologists' work. FUNDING: National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, and the Guangdong Provincial Clinical Research Centre for Urological Diseases.

A Deep Neural Network-Based Decision Support Tool for the Detection of Lymph Node Metastases in Colorectal Cancer Specimens.

The identification of lymph node metastases in colorectal cancer (CRC) specimens is crucial for the planning of postoperative treatment and can be a time-consuming task for pathologists. In this study, we developed a deep neural network (DNN) algorithm for the detection of metastatic CRC in digitized histologic sections of lymph nodes and evaluated its performance as a diagnostic support tool. First, the DNN algorithm was trained using pixel-level annotations of cancerous areas on 758 whole slide images (360 with cancerous areas). The algorithm's performance was evaluated on 74 whole slide images (43 with cancerous areas). Second, the algorithm was evaluated as a decision support tool on 288 whole slide images covering 1517 lymph node sections, randomized in 16 batches. Two senior pathologists (C.K. and C.O.) assessed each batch with and without the help of the algorithm in a 2 × 2 crossover design, with a washout period of 1 month in between. The time needed for the evaluation of each node section was recorded. The DNN algorithm achieved a median pixel-level accuracy of 0.952 on slides with cancerous areas and 0.996 on slides with benign samples. N+ disease (metastases, micrometastases, or tumor deposits) was present in 103 of the 1517 sections. The algorithm highlighted cancerous areas in 102 of these sections, with a sensitivity of 0.990. Assisted by the algorithm, the median time needed for evaluation was significantly shortened for both pathologists (median time for pathologist 1, 26 vs 14 seconds; P < .001; 95% CI, 11.0-12.0; median time for pathologist 2, 25 vs 23 seconds; P < .001; 95% CI, 2.0-4.0). Our DNN showed high accuracy for detecting metastatic CRC in digitized histologic sections of lymph nodes. This decision support tool has the potential to improve the diagnostic workflow by shortening the time needed for the evaluation of lymph nodes in CRC specimens without impairing diagnostic accuracy.

Comprehensive Assessment of ERα, PR, Ki67, P53 to Predict the Risk of Lymph Node Metastasis in Low-Risk Endometrial Cancer.

PURPOSE: According to international guidelines, selective lymph node dissection can be performed on patients with early-stage endometrial cancer. However, some patients at early stage have already occurred lymph node metastasis at the time of diagnosis. This study was aimed to find a method to predict the risk of lymph node metastasis in this part of patient. METHODS: We collected data from 571 patients as training cohort and 351 patients as validation cohort for this study. Then we performed univariate and multivariate analyses to confirm the correlation of frequently used factors and lymph node metastasis. Combined analysis of four commonly indicators (ERα, PR, P53 and Ki67) from pathological parameter sources was mainly carried out, and the combined ratio is defined as (ERα + PR)/(Ki67 + P53). Then the accuracy of the combined ratio and other factors in prediction were compared by AUC value. Also, the optimal truncation value was searched. Finally, patients followed up for more than two years were divided into groups by the threshold value, and their difference in survival was explored. RESULTS: This study showed that CA125, grade, LVSI, ERα, PR, P53, Ki67 have statistical significance (P-value <0.05). The AUC value of combined ratio is 0.876, which is the best. The best cutoff value of combined ratio is 1.38. CONCLUSION: The combined ratio cutoff value of 1.38 in this study can be used for prediction of risk of lymph node metastasis in early-stage endometrial cancer patients and provide a reference for therapeutic planning.