Multiparametric monitoring of chemotherapy treatment response in locally advanced breast cancer using quantitative ultrasound and diffuse optical spectroscopy

Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.

A Nomogram for Pretreatment Prediction of Response to Induction Chemotherapy in Locally Advanced Hypopharyngeal Carcinoma

Background

Induction chemotherapy (IC) significantly improves the rate of larynx preservation; however, some patients could not benefit from it. Hence, it is of clinical importance to predict the response to IC to determine the necessity of IC. We aimed to develop a clinical nomogram for predicting the treatment response to IC in locally advanced hypopharyngeal carcinoma.

Methods

We retrospectively include a total of 127 patients with locally advanced hypopharyngeal carcinoma who underwent MRI scans prior to IC between January 2014 and December 2017. The clinical characteristics were collected, which included age, sex, tumor location, invading sites, histological grades, T-stage, N-stage, overall stage, size of the largest lymph node, neutrophil-to-lymphocyte ratio, hemoglobin concentration, and platelet count. Univariate and multivariate logistic regression was used to select the significant predictors of IC response. A nomogram was built based on the results of stepwise logistic regression analysis. The predictive performance and clinical usefulness of the nomogram were determined based on the area under the curve (AUC), calibration curve, and decision curve.

Results

Age, T-stage, hemoglobin, and platelet were four independent predictors of IC treatment response, which were incorporated into the nomogram. The AUC of the nomogram was 0.860 (95% confidence interval [CI]: 0.780-0.940), which was validated using 3-fold cross-validation (AUC, 0.864; 95% CI: 0.755-0.973). The calibration curve demonstrated good consistency between the prediction by the nomogram and actual observation. Decision curve analysis shows that the nomogram was clinically useful.

Conclusion

The proposed nomogram resulted in an accurate prediction of the efficacy of IC for patients with locally advanced hypopharyngeal carcinoma.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

BACKGROUND

Neoadjuvant chemotherapy (NAC) is the standard of care for patients with locally advanced breast cancer (LABC). The study was conducted to investigate the utility of quantitative ultrasound (QUS) carried out during NAC to predict the final tumour response in a multi-institutional setting.

METHODS

Fifty-nine patients with LABC were enrolled from three institutions in North America (Sunnybrook Health Sciences Centre (Toronto, Canada), MD Anderson Cancer Centre (Texas, USA), and Princess Margaret Cancer Centre (Toronto, Canada)). QUS data were collected before starting NAC and subsequently at weeks 1 and 4 during chemotherapy. Spectral tumour parametric maps were generated, and textural features determined using grey-level co-occurrence matrices. Patients were divided into two groups based on their pathological outcomes following surgery: responders and non-responders. Machine learning algorithms using Fisher's linear discriminant (FLD), K-nearest neighbour (K-NN), and support vector machine (SVM-RBF) were used to generate response classification models.

RESULTS

Thirty-six patients were classified as responders and twenty-three as non-responders. Among all the models, SVM-RBF had the highest accuracy of 81% at both weeks 1 and week 4 with area under curve (AUC) values of 0.87 each. The inclusion of week 1 and 4 features led to an improvement of the classifier models, with the accuracy and AUC from baseline features only being 76% and 0.68, respectively.

CONCLUSION

QUS data obtained during NAC reflect the ongoing treatment-related changes during chemotherapy and can lead to better classifier performances in predicting the ultimate pathologic response to treatment compared to baseline features alone.

Fiber-Coupled Luminescent Concentrators for Medical Diagnostics, Agriculture, and Telecommunications

While luminescent concentrators (LCs) are mainly designed to harvest sunlight and convert its energy into electricity, the same concept can be advantageous in alternative applications. Examples of such applications are demonstrated here by coupling the edge-guided light of high-performance LCs based on CuInSe_xS_2-x/ZnS quantum dots into optical fibers with emission covering visible-to-NIR spectral regions. In particular, a cost-efficient, miniature broadband light source for medical diagnostics, a spectral-conversion and light-guiding device for agriculture, and a large-area broadband tunable detector for telecommunications are demonstrated. Various design considerations and performance optimization approaches are discussed and summarized. Prototypes of the devices are manufactured and tested. Individual elements of the broadband light source show coupling efficiencies up to 1%, which is sufficient to saturate typical fiber-coupled spectrometers at a minimal integration time of 1 ms using 100 mW blue excitation. Agricultural devices are capable of delivering ∼10% of photosynthetically active radiation (per device) converted from absorbed sunlight to the lower canopy of plants, which boosted the tomato yield in a commercial greenhouse by 7% (fresh weight). Finally, large-scale prototype detectors can be used to discern time-modulated unfocused signals with an average power as low as 1 μW, which would be useful for free-space telecommunication systems. Fully optimized devices are expected to make significant impacts on speed and bandwidth of free-space telecommunication systems, medical diagnostics, and greenhouse crop yields.

Identifying an early treatment window for predicting breast cancer response to neoadjuvant chemotherapy using immunohistopathology and hemoglobin parameters

BACKGROUND

Breast cancer pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) varies with tumor subtype. The purpose of this study was to identify an early treatment window for predicting pCR based on tumor subtype, pretreatment total hemoglobin (tHb) level, and early changes in tHb following NAC.

METHODS

Twenty-two patients (mean age 56 years, range 34-74 years) were assessed using a near-infrared imager coupled with an Ultrasound system prior to treatment, 7 days after the first treatment, at the end of each of the first three cycles, and before their definitive surgery. Pathologic responses were dichotomized by the Miller-Payne system. Tumor vascularity was assessed from tHb; vascularity changes during NAC were assessed from a percentage tHb normalized to the pretreatment level (%tHb). After training the logistic prediction models using the previous study data, we assessed the early treatment window for predicting pathological response according to their tumor subtype (human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), triple-negative (TN)) based on tHb, and %tHb measured at different cycles and evaluated by the area under the receiver operating characteristic (ROC) curve (AUC).

RESULTS

In the new study cohort, maximum pretreatment tHb and %tHb changes after cycles 1, 2, and 3 were significantly higher in responder Miller-Payne 4-5 tumors (n = 13) than non-or partial responder Miller-Payne 1-3 tumors (n = 9). However, no significance was found at day 7. The AUC of the predictive power of pretreatment tHb in the cohort was 0.75, which was similar to the performance of the HER2 subtype as a single predictor (AUC of 0.78). A greater predictive power of pretreatment tHb was found within each subtype, with AUCs of 0.88, 0.69, and 0.72, in the HER2, ER, and TN subtypes, respectively. Using pretreatment tHb and cycle 1 %tHb, AUC reached 0.96, 0.91, and 0.90 in HER2, ER, and TN subtypes, respectively, and 0.95 regardless of subtype. Additional cycle 2 %tHb measurements moderately improved prediction for the HER2 subtype but did not improve prediction for the ER and TN subtypes.

CONCLUSIONS

By combining tumor subtypes with tHb, we predicted the pCR of breast cancer to NAC before treatment. Prediction accuracy can be significantly improved by incorporating cycle 1 and 2 %tHb for the HER2 subtype and cycle 1 %tHb for the ER and TN subtypes.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02092636 . Registered in March 2014.

The role of MRI in predicting Ki-67 in breast cancer: preliminary results from a prospective study

Purpose:

In the last decade contrast-enhanced magnetic resonance imaging (MRI) has gained a growing role as a complementary tool for breast cancer diagnosis. Currently the relationship between the kinetic features of a breast lesion and pathologic prognostic factors has become a popular field of research. Our aim is to verify whether breast MRI could be considered a useful tool to predict Ki-67 score, thus resulting as a breast cancer prognosis indicator.

Methods:

From June to December 2014, we enrolled patients with breast cancer who underwent preoperative dynamic contrast-enhanced MRI at the local health agency. We analyzed the time-signal intensity curves calculating the mean values of the following parameters: the basal enhancement (Ebase), the enhancement ratio (ENHratio), the maximum enhancement (Emax), and the steepest slope of the contrast enhancement curve (Smax). Scatterplots and Pearson correlation test were used to investigate the eventual associations among these parameters.

Results:

A total of 27 patients underwent breast MRI during the study period. The mean ± SD Ki-67 percentage was 27.03 ± 16.8; the mean Emax, Smax, Ebase, and ENHratio were 433.9 ± 120.2, 267.3 ± 96.8, 165.5 ± 77.1, and 187.1 ± 94.8, respectively. Scatterplots suggest a positive correlation between Ki-67 and both Emax and Smax. The correlation tests between Ki-67 and Emax, Ki-67 and Smax showed statistical significance.

Conclusions:

Our preliminary data suggest that enhancement pattern is closely linked to breast cancer proliferation, thus proving the relationship between more proliferating tumors and more rapidly enhanced lesions. This is hypothesis-generating for further studies aimed at promoting breast MRI in the early estimation of cancer prognosis and tumor in vivo response to chemotherapy.

Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography

Near-infrared diffuse optical tomography (NIR-DOT) is an emerging technology that offers hemoglobin based, functional imaging tumor biomarkers for breast cancer management. The most promising clinical translation opportunities are in the differential diagnosis of malignant vs. benign lesions, and in early response assessment and guidance for neoadjuvant chemotherapy. Accurate quantification of the tissue oxy- and deoxy-hemoglobin concentration across the field of view, as well as repeatability during longitudinal imaging in the context of therapy guidance, are essential for the successful translation of NIR-DOT to clinical practice. The ill-posed and ill-condition nature of the DOT inverse problem makes this technique particularly susceptible to model errors that may occur, for example, when the experimental conditions do not fully match the assumptions built into the image reconstruction process. To evaluate the susceptibility of DOT images to experimental errors that might be encountered in practice for a parallel-plate NIR-DOT system, we simulated 7 different types of errors, each with a range of magnitudes. We generated simulated data by using digital breast phantoms derived from five actual mammograms of healthy female volunteers, to which we added a 1-cm tumor. After applying each of the experimental error types and magnitudes to the simulated measurements, we reconstructed optical images with and without structural prior guidance and assessed the overall error in the total hemoglobin concentrations (HbT) and in the HbT contrast between the lesion and surrounding area vs. the best-case scenarios. It is found that slight in-plane probe misalignment and plate rotation did not result in large quantification errors. However, any out-of-plane probe tilting could result in significant deterioration in lesion contrast. Among the error types investigated in this work, optical images were the least likely to be impacted by breast shape inaccuracies but suffered the largest deterioration due to cross-talk between signal channels. However, errors in optical images could be effectively controlled when experimental parameters were properly estimated during data acquisition and accounted for in the image processing procedure. Finally, optical images recovered using structural priors were, in general, less susceptible to experimental errors; however, lesion contrasts were more sensitive to errors when tumor locations were used as a priori info. Findings in this simulation study can provide guidelines for system design and operation in optical breast imaging studies.

Optical Mammography in Patients with Breast Cancer Undergoing Neoadjuvant Chemotherapy: Individual Clinical Response Index

RATIONALE AND OBJECTIVES

We present an optical mammography study that aims to develop quantitative measures of pathologic response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Such quantitative measures are based on the concentrations of oxyhemoglobin ([HbO₂]), deoxyhemoglobin ([Hb]), total hemoglobin ([HbT]), and hemoglobin saturation (SO₂) in breast tissue at the tumor location and at sequential time points during chemotherapy.

MATERIALS AND METHODS

Continuous-wave, spectrally resolved optical mammography was performed in transmission and parallel-plate geometry on 10 patients before treatment initiation and at each NAC administration (mean number of optical mammography sessions: 12, range: 7-18). Data on two patients were discarded for technical reasons. The patients were categorized as responders (R, >50% decrease in tumor size), or nonresponders (NR, <50% decrease in tumor size) based on imaging and histopathology results.

RESULTS

At 50% completion of the NAC regimen (therapy midpoint), R (6/8) demonstrated significant decreases in SO₂ (-27% ± 4%) and [HbT] (-35 ± 4 µM) at the tumor location with respect to baseline values. By contrast, NR (2/8) showed nonsignificant changes in SO₂ and [HbT] at therapy midpoint. We introduce a cumulative response index as a quantitative measure of the individual patient's response to therapy. At therapy midpoint, the SO₂-based cumulative response index had a sensitivity of 100% and a specificity of 100% for the identification of R.

CONCLUSIONS

These results show that optical mammography is a promising tool to assess individual response to NAC at therapy midpoint to guide further decision making for neoadjuvant therapy.

Photoacoustic signal characterization of cancer treatment response: Correlation with changes in tumor oxygenation

Frequency analysis of the photoacoustic radiofrequency signals and oxygen saturation estimates were used to monitor the in-vivo response of a novel, thermosensitive liposome treatment. The liposome encapsulated doxorubicin (HaT-DOX) releasing it rapidly (<20 s) when the tumor was exposed to mild hyperthermia (43 °C). Photoacoustic imaging (VevoLAZR, 750/850 nm, 40 MHz) of EMT-6 breast cancer tumors was performed 30 min pre- and post-treatment and up to 7 days post-treatment (at 2/5/24 h timepoints). HaT-DOX-treatment responders exhibited on average a 22% drop in oxygen saturation 2 h post-treatment and a decrease (45% at 750 nm and 73% at 850 nm) in the slope of the normalized PA frequency spectra. The spectral slope parameter correlated with treatment-induced hemorrhaging which increased the optical absorber effective size via interstitial red blood cell leakage. Combining frequency analysis and oxygen saturation estimates differentiated treatment responders from non-responders/control animals by probing the treatment-induced structural changes of blood vessel.