Dataset Information

Feasibility of preoperative tattooing of percutaneously biopsied axillary lymph node: an experimental pilot study.

ABSTRACT: Background:In the last three decades, axillary lymph node dissection (ALND) has been replaced by sentinel lymph node biopsy (SLNB) in all clinically node-negative patients. However, when SLNB alone is performed in clinically node-positive patients who are rendered node-negative by neoadjuvant chemotherapy, the procedure has a high false-negative rate and other complementary procedures have been described to improve its reliability. Preoperative tattooing of the suspicious lymph node with India ink at the time of biopsy, in addition to sentinel lymph node biopsy, is a reasonable alternative. The objective of our study is to determine, in clinically node-positive patients, the feasibility of tattooing suspicious axillary lymph node at the time of percutaneous needle biopsy and its retrieval at the time of surgery. Methods:A prospective experimental study will be conducted divided into two phases-phases I and II. In phase I, 10 patients committed to undergo upfront surgery (without neoadjuvant chemotherapy) will have a suspicious lymph node tattooed by injecting India ink at the time of core needle biopsy. All patients will undergo a SLNB, during which the axilla will be inspected to determine if the tattooed lymph node can be visualized. Routine microscopic examination will follow, and concordance between the sentinel and tattooed node will also be established. In phase II, the process will be repeated for 30 patients who undergo surgery after neoadjuvant chemotherapy. The analysis will be performed in Stata version 12. Discussion:There is a need to identify and test the techniques for the down-staged axilla in post-neoadjuvant chemotherapy patients, which are not only practical and limit the number of invasive procedures necessary but are representative of the new axillary status and help limit the extent of axillary surgery without negatively impacting outcomes. We propose that, for the patient undergoing neoadjuvant chemotherapy with a biopsy-proven disease in the axilla, this could be achieved by India ink which allows marking, identification, and retrieval of the biopsied lymph node. Retrieval of this previously biopsied lymph node along with sentinel nodes, if found to be representative of the status of the remainder of the axilla, could potentially eliminate the need for routine axillary lymph node dissection and thus limit morbidity. Trial Registration:ClinicalTrials.gov, NCT03939598. Retrospectively registered on 7 May 2019.

SUBMITTER: Sattar AK

PROVIDER: S-EPMC7513507 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Feasibility of preoperative tattooing of percutaneously biopsied axillary lymph node: an experimental pilot study.

Sattar Abida K AK Ali Basim B Masroor Imrana I Afzal Shaista S Tariq Mohammad Usman MU Idrees Romana R Uzzaman Maseeh M Khalid Wardah W

Pilot and feasibility studies 20200924

<h4>Background</h4>In the last three decades, axillary lymph node dissection (ALND) has been replaced by sentinel lymph node biopsy (SLNB) in all clinically node-negative patients. However, when SLNB alone is performed in clinically node-positive patients who are rendered node-negative by neoadjuvant chemotherapy, the procedure has a high false-negative rate and other complementary procedures have been described to improve its reliability. Preoperative tattooing of the suspicious lymph node with ...[more]

PMID: 32983557

Similar Datasets

Project description:IntroductionThe axillary lymph node (ALN) status of breast cancer patients is an important prognostic indicator. The use of primary breast mass features for the prediction of ALN status is rare. Two nomograms based on preoperative ultrasound (US) images of breast tumors and ALNs were developed for the prediction of ALN status.MethodsA total of 743 breast cancer cases collected from 2016 to 2019 at the Second Affiliated Hospital of Harbin Medical University were randomly divided into a training set (n = 523) and a test set (n = 220). A primary tumor feature model (PTFM) and ALN feature model (ALNFM) were separately generated based on tumor features alone, and a combination of features was used for the prediction of ALN status. Logistic regression analysis was used to construct the nomograms. A receiver operating characteristic curve was plotted to obtain the area under the curve (AUC) to evaluate accuracy, and bias-corrected AUC values and calibration curves were obtained by bootstrap resampling for internal and external verification. Decision curve analysis was applied to assess the clinical utility of the models.ResultsThe AUCs of the PTFM were 0.69 and 0.67 for the training and test sets, respectively, and the bias-corrected AUCs of the PTFM were 0.67 and 0.67, respectively. Moreover, the AUCs of the ALNFM were 0.86 and 0.84, respectively, and the bias-corrected AUCs were 0.85 and 0.81, respectively. Compared with the PTFM, the ALNFM showed significantly improved prediction accuracy (p < 0.001). Both the calibration and decision curves of the ALNFM nomogram indicated greater accuracy and clinical practicality. When the US tumor size was ≤21.5 mm, the Spe was 0.96 and 0.92 in the training and test sets, respectively. When the US tumor size was greater than 21.5 mm, the Sen was 0.85 in the training set and 0.87 in the test set. Our further research showed that when the US tumor size was larger than 35 mm, the Sen was 0.90 in the training set and 0.93 in the test set.ConclusionThe ALNFM could effectively predict ALN status based on US images especially for different US tumor size.

Project description:BACKGROUND:Preoperative detection of lymph node (LN) metastasis is critical for planning treatments in colon cancer (CC). The clinical diagnostic criteria based on the size of the LNs are not sensitive to determine metastasis using CT images. In this retrospective study, we investigated the potential value of CT texture features to diagnose LN metastasis using preoperative CT data and patient characteristics by developing quantitative prediction models. METHODS:A total of 390 CC patients, undergone surgical resection, were enrolled in this monocentric study. 390 histologically validated LNs were collected from patients and randomly separated into training (312 patients, 155 metastatic and 157 normal LNs) and test cohorts (78 patients, 39 metastatic and 39 normal LNs). Six patient characteristics and 146 quantitative CT imaging features were analyzed and key variables were determined using either exhaustive search or least absolute shrinkage algorithm. Two kernel-based support vector machine classifiers (patient-characteristic model and radiomic-derived model), generated with 10-fold cross-validation, were compared with the clinical model that utilizes long-axis diameter for diagnosis of metastatic LN. The performance of the models was evaluated on the test cohort by computing accuracy, sensitivity, specificity, and area under the receiver operating curve (AUC). RESULTS:The clinical model had an overall diagnostic accuracy of 64.87%; specifically, accuracy of 65.38% and 62.82%, sensitivity of 83.87% and 84.62%, and specificity of 47.13% and 41.03% for training and test cohorts, respectively. The patient-demographic model obtained accuracy of 67.31% and 73.08%, the sensitivity of 62.58% and 69.23%, and specificity of 71.97% and 76.23% for training and test cohorts, respectively. Besides, the radiomic-derived model resulted in an accuracy of 81.09% and 79.49%, sensitivity of 83.87% and 74.36%, and specificity of 78.34% and 84.62% for training and test cohorts, respectively. Furthermore, the diagnostic performance of the radiomic-derived model was significantly higher than clinical and patient-demographic models (p?<?0.02) according to the DeLong method. CONCLUSIONS:The texture of the LNs provided characteristic information about the histological status of the LNs. The radiomic-derived model leveraging LN texture provides better preoperative diagnostic accuracy for the detection of metastatic LNs compared to the clinically accepted diagnostic criteria and patient-demographic model.

Dataset Information

Feasibility of preoperative tattooing of percutaneously biopsied axillary lymph node: an experimental pilot study.

Publications

Feasibility of preoperative tattooing of percutaneously biopsied axillary lymph node: an experimental pilot study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets