This clinical trial studies how well ultrasound/photoacoustic/elasticity (US/PA/E) imaging works for early identification of tumor response in patients with stage II-III triple-negative breast cancer receiving immunotherapy and chemotherapy before surgery (neoadjuvant). US imaging uses high-energy sound waves to look at tissues and organs inside the body. The sound waves make echoes that form pictures of the tissues and organs on a computer screen. PA imaging delivers laser light into tissue which produces ultrasonic waves which are then converted into images. Elastography (i.e., elasticity \[E\]) imaging uses sound waves to send vibrations into a specific organ and measures how fast those vibrations move. The vibrations move faster through areas of stiff tissue and a computer uses these measurements to make an image of those areas. Combined US/PA/E imaging using the Vevo F2 and Vevo LAZR-X20 devices may be safe and provide earlier information about tumor response to standard neoadjuvant immunotherapy and chemotherapy than current standard imaging.
Age ≥ 18 years
Patients with stage II-III triple negative breast cancer, per American Society of Clinical Oncology-College of American Pathologists (ASCO-CAP) guidelines
Deemed clinically appropriate for KEYNOTE-522 regimen based on performance status and laboratory findings
No signs of metastatic disease
Acute bacterial or fungal infection requiring intravenous (IV) antibiotics at time of registration
Is pregnant or breastfeeding or expecting to conceive or father children within the projected duration of the trial
Single group
Elastography
Procedure/SurgeryUndergo PA/E imaging using the Vevo LAZR-X20 device
Magnetic Resonance Imaging
Procedure/SurgeryUndergo breast MRI
Photoacoustic Imaging
Procedure/SurgeryUndergo PA/E imaging using the Vevo LAZR-X20 device
Ultrasound Imaging
Procedure/SurgeryUndergo US imaging using the Vevo F2 device
Pembrolizumab
DrugWeekly carboplatin + paclitaxel +every three- week pembrolizumab X12 weeks, followed by every three-week doxorubicin + cyclophosphamide (AC) + pembrolizumab X 4 cycles).
Carboplatin
DrugWeekly carboplatin + paclitaxel +every three- week pembrolizumab X12 weeks, followed by every three-week doxorubicin + cyclophosphamide (AC) + pembrolizumab X 4 cycles).
Paclitaxel
DrugWeekly carboplatin + paclitaxel +every three- week pembrolizumab X12 weeks, followed by every three-week doxorubicin + cyclophosphamide (AC) + pembrolizumab X 4 cycles).
Doxorubicin
DrugWeekly carboplatin + paclitaxel +every three- week pembrolizumab X12 weeks, followed by every three-week doxorubicin + cyclophosphamide (AC) + pembrolizumab X 4 cycles).
Cyclophosphamide
DrugWeekly carboplatin + paclitaxel +every three- week pembrolizumab X12 weeks, followed by every three-week doxorubicin + cyclophosphamide (AC) + pembrolizumab X 4 cycles).
Serial changes in the ultrasound/photoacoustic/elasticity (US/PA/E) imaging biomarkers
Will evaluate serial changes in the US/PA/E imaging biomarkers (primarily deoxy hemoglobin) over the course of the treatment and their association with clinical response as assessed by comparison of baseline and pre surgical magnetic resonance imaging. Summary statistics and data visualization will be applied to describe the biomarker data at each time point, along with the changing patterns during the treatment period. A paired t-test or Wilcoxon signed rank test will test the magnitude change of optical images at week-3 from baseline. A linear and/or non-linear mixed effect model will be considered to model the longitudinal data and test the trend of change.
Correlation between the early changes documented in US/PA/E protocol and the probability of achieving pathologic complete response (pCR)
Will compare the correlation between the early changes documented in US/PA/E protocol and the probability of achieving pCR, defined as pT0/T1s, pN0. To predict the status of clinical response (Aim 1) or pCR (Aim 2), the value of the biomarker at each timepoint and their change relative to the baseline value (e.g fold-change or percentage of change) will be treated as continuous variables, and receiver operator characteristics analysis will be applied to assess the overall prediction performance in terms of the area under the curve, and to identify the optimal cut-off value and/or the optimal timepoint that results in the best prediction performance in terms of the sensitivity and specificity.
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Emory University
Lead sponsor
National Cancer Institute (NCI)
Collaborator
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