T. Van Nijnatten

The diagnostic performance of sentinel lymph node biopsy in pathologically confirmed node positive breast cancer patients after neoadjuvant systemic therapy: A systematic review and meta-analysis

PURPOSE To provide a systematic review and meta-analysis of studies investigating sentinel lymph node biopsy after neoadjuvant systemic therapy in pathologically confirmed node positive breast cancer patients. METHODS Pubmed and Embase databases were searched until June 19th, 2015. All abstracts were read and data extraction was performed by two independent readers. A random-effects model was used to pool the proportion for identification rate, false-negative rate (FNR) and axillary pCR with 95% confidence intervals. Subgroup analyses affirmed potential confounders for identification rate and FNR. RESULTS A total of 997 abstracts were identified and eventually eight studies were included. Pooled estimates were 92.3% (90.8-93.7%) for identification rate, 15.1% (12.7-17.6%) for FNR and 36.8% (34.2-39.5%) for axillary pCR. After subgroup analysis, FNR is significantly worse if one sentinel node was removed compared to two or more sentinel nodes (23.9% versus 10.4%, p = 0.026) and if studies contained clinically nodal stage 1-3, compared to studies with clinically nodal stage 1-2 patients (21.4 versus 13.1%, p = 0.049). Other factors, including single tracer mapping and the definition of axillary pCR, were not significantly different. CONCLUSION Based on current evidence it seems not justified to omit further axillary treatment in every clinically node positive breast cancer patients with a negative sentinel lymph node biopsy after neoadjuvant systemic therapy.

Routine use of standard breast MRI compared to axillary ultrasound for differentiating between no, limited and advanced axillary nodal disease in newly diagnosed breast cancer patients

OBJECTIVES To compare standard breast MRI to dedicated axillary ultrasound (with or without tissue sampling) for differentiating between no, limited and advanced axillary nodal disease in breast cancer patients. METHODS All patients who underwent breast MRI and dedicated axillary ultrasound between 2009 and 2014 were eligible. Exclusion criteria were recurrent disease, neoadjuvant systemic therapy and not receiving completion axillary lymph node dissection after positive sentinel lymph node biopsy (SLNB). Two radiologists independently reassessed all MRI exams. Axillary ultrasound findings were retrospectively collected. Probability of advanced axillary nodal disease (pN2-3) given clinically node negative (cN0) or limited (cN1) findings was calculated, with corresponding negative predictive value (NPV) to exclude pN2-3 and positive predictive value (PPV) to identify axillary nodal disease. Histopathology served as gold standard. RESULTS A total of 377 cases resulted in 81.4% no, 14.4% limited and 4.2% advanced axillary nodal disease at final histopathology. Probability of pN2-3 given cN0 for breast MRI and axillary ultrasound was 0.7-0.9% versus 1.5% and probability of pN2-3 given cN1 was 11.6-15.4% versus 29.0%. When cN1 on breast MRI was observed, PPV to identify positive axillary nodal disease was 50.7% and 59.0%. CONCLUSIONS Evaluation of axillary nodal status on standard breast MRI is comparable to dedicated axillary ultrasound in breast cancer patients. In patients who underwent preoperative standard breast MRI, axillary ultrasound is only required in case of suspicious nodal findings on MRI.

Diagnostic performance of gadofosveset-enhanced axillary MRI for nodal (re)staging in breast cancer patients: results of a validation study

AIM To evaluate diagnostic performance of gadofosveset (GDF)-enhanced magnetic resonance imaging (MRI) in addition to T2-weighted (T2W) MRI for nodal (re)staging in newly diagnosed breast cancer patients. MATERIALS AND METHODS Ninety patients underwent axillary T2W- and GDF-MRI. Two radiologists independently scored each lymph node; first on T2W-MRI, subsequently adjusting their score on GDF-MRI. Diagnostic performance parameters were calculated on node-by-node and patient-by-patient validation with histopathology as the reference standard. Furthermore, learning curve analysis for reading GDF-MRI was performed. RESULTS In patient-by-patient validation, overall reader performances for T2W- and GDF-MRI were similar with area under the receiver operating characteristic curves (AUC) of 0.75 and 0.77 (p=0.731) for reader 1 and 0.79 and 0.72 (p=0.156) for reader 2. For node-by-node validation, AUC values of T2W- and GDF-MRI were 0.76 and 0.82 (p=0.018) and 0.77 and 0.77 (p=0.998) for reader 1 and 2. The AUC for reader 1 was 0.71 for first one-third of nodes evaluated, improving to 0.80 and 0.95 for the next and last one-third, respectively. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) improved from 38%, 89%, 56%, and 79% to 60%, 93%, 64%, and 92%. The AUC of reader 2 improved from 0.69 to 0.79. CONCLUSION The present study confirmed that GDF-MRI, in addition to T2W-MRI, has potential as a non-invasive method for nodal (re)staging in breast cancer.