Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy

Ultrasound-based radiomics-clinical nomogram for noninvasive prediction of residual cancer burden grading in breast cancer

PURPOSE

To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients.

METHODS

This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram.

RESULTS

A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort.

CONCLUSIONS

Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy

Significance

Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes.

Aim

We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT.

Approach

Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers.

Results

Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p = 0.042 ). In addition, the change in normalized tumor StO 2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p = 0.038 ). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI.

Conclusions

These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning

Objective

Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).

Materials and methods

Several deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes.

Results

Amongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network.

Conclusion

Deep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism.

Noninvasive hemoglobin quantification across different cohorts using a wearable diffuse reflectance spectroscopy system

Quantifying hemoglobin is vital yet invasive through blood draws. We developed a wearable diffuse reflectance spectroscopy device comprising control and sensor boards with photodiodes and light-emitting diodes to noninvasively determine hemoglobin. Neural networks enabled recovery of optical parameters for chromophore fitting to calculate hemoglobin. Testing healthy and elderly subjects revealed strong correlation (r=0.9) between our system and invasive methods after data conversion. Bland-Altman analysis demonstrated tight 95% limits of agreement from -1.98 to 1.98 g/dL between the DRS and invasive hemoglobin concentrations. By spectroscopically isolating hemoglobin absorption, interference from melanin was overcome. Our device has the potential for future integration into wearable technology, enabling hemoglobin level tracking.

In Vivo Raman Spectroscopy Reveals Biochemical Composition of the Esophageal Tissue in Pediatric Eosinophilic Esophagitis

INTRODUCTION

Biochemical alterations in the esophagus of patients with eosinophilic esophagitis (EoE) are poorly understood. We used Raman spectroscopy through a pediatric endoscope to identify key Raman features reflective of the esophageal biochemical composition to differentiate between children with EoE from non-EoE controls and between children with active (aEoE) and inactive EoE (iEoE).

METHODS

Spectral measurements were obtained using a customized pediatric endoscope-compatible fiber-optic Raman probe in real time during an esophagogastroduodenoscopy. Chemometric analysis was performed to identify key Raman features associated with EoE. Pearson correlation analysis was used to assess relationship between the key Raman features and EoE activity indices. Their diagnostic utility was ascertained using the receiver operator characteristic curve analysis.

RESULTS

Forty-three children were included in the study (EoE = 32 [74%] and non-EoE control = 11 [26%]; aEoE = 20 [63%] and iEoE = 12 [37%]). Raman intensities assigned to lipids, proteins, and glycogen:protein ratio accurately distinguished children with EoE from those without EoE and aEoE from iEoE. They significantly correlated with EoE activity indices. The Raman peak ratio for lipids had 90.6% sensitivity, 100% specificity, and an area under the curve of 0.95 to differentiate children with EoE from non-EoE controls. The glycogen:protein ratio had 70% sensitivity, 91.7% specificity, and an area under the curve of 0.75 to distinguish children with aEoE from iEoE.

DISCUSSION

Real-time intraendoscopy Raman spectroscopy is an effective method for identifying spectral markers reflective of the esophageal biochemical composition in children with EoE. This technique may aid in the diagnosis and monitoring of EoE and help to elucidate EoE pathogenesis.

Massively parallel, real-time multispeckle diffuse correlation spectroscopy using a 500 × 500 SPAD camera

Diffuse correlation spectroscopy (DCS) is a promising noninvasive technique for monitoring cerebral blood flow and measuring cortex functional activation tasks. Taking multiple parallel measurements has been shown to increase sensitivity, but is not easily scalable with discrete optical detectors. Here we show that with a large 500 × 500 SPAD array and an advanced FPGA design, we achieve an SNR gain of almost 500 over single-pixel mDCS performance. The system can also be reconfigured to sacrifice SNR to decrease correlation bin width, with 400 ns resolution being demonstrated over 8000 pixels.

Characterizing tourniquet induced hemodynamics during total knee arthroplasty using diffuse optical spectroscopy

Tourniquet use creates a reduced blood surgical field during total knee arthroplasty (TKA), however, prolonged ischemia may cause postoperative tourniquet complications. To understand the effects of tourniquet-induced ischemia, we performed a prospective observational study using quantitative broadband diffuse optical spectroscopy (DOS) to measure tissue hemodynamics and water and lipid concentrations before, during, and after tourniquet placement in subjects undergoing TKA. Data was collected for 6 months and, of the total subjects analyzed (n = 24), 22 were primary TKAs and 2 were revision TKA cases. We specifically investigated tourniquet-induced hemodynamics based upon subject-specific tissue composition and observed a significant relationship between the linear rate of deoxygenation after tourniquet inflation and water/lipid ratio (W/L, p < 0.0001) and baseline somatic tissue oxygen saturation, StO2 (p = 0.05). Subjects with a low W/L ratio exhibited a lower tissue metabolic rate of oxygen consumption, (tMRO2 ) (p = 0.008). Changes in deoxyhemoglobin [HbR] (p = 0.009) and lipid fraction (p = 0.001) were significantly different between high and low W/L subject groups during deoxygenation. No significant differences were observed for hemodynamics during reperfusion and total tourniquet time was neither significantly related to the hemodynamic hyperemic response (p = 0.73) nor the time to max StO2 after tourniquet release (p = 0.57). In conclusion, we demonstrate that DOS is capable of real-time monitoring of tissue hemodynamics distal to the tourniquet during TKA, and that tissue composition should be considered. DOS may help surgeons stratify hemodynamics based upon tissue composition and eventually aid the preoperative risk assessment of vascular occlusions from tourniquet use during TKA.

Survival After Breast-Conserving Surgery Compared with that After Mastectomy in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

BACKGROUND

Breast-conserving surgery (BCS) plus radiotherapy (BCS + RT) has been shown to improve survival compared with mastectomy in patients with early breast cancer; however, whether this superiority is maintained in breast cancer patients receiving neoadjuvant chemotherapy (NCT) is unclear. We evaluated and compared the survival outcomes after BCS + RT and mastectomy in Korean women with breast cancer treated with NCT.

METHODS

We evaluated 1641 patients who received NCT before surgery (BCS or mastectomy). We performed propensity score matching to minimize potential bias due to factors other than the surgical method and compared the 5-year, disease-free survival (DFS), distant metastasis-free survival (DMFS), and overall survival (OS) rates before and after exact matching.

RESULTS

Among the 1641 patients, 839 (51.1%) underwent BCS + RT and 802 (48.9%) underwent mastectomy. Patients who underwent mastectomy had larger tumors and more frequently had positive nodes. For BCS+RT and mastectomy, the unadjusted 5-year DFS, 5-year DMFS, and 5-year OS rates were 87.0% and 73.1%, 89.5% and 77.0%, and 91.8% and 81.0%, respectively (all p < 0.05 = 0.000). After PSM, 5-year DFS, 5-year DMFS, and 5-year OS rates for BCS + RT and mastectomy were 87.6% and 69.1%, 89.7% and 76.0%, and 89.1% and 75.7%, respectively (all p < 0.05). In both unadjusted and adjusted analyses accounting for various confounding factors, BCS + RT was significantly associated with improved DFS (p < 0.05), DMFS (p < 0.05), and OS (p < 0.05) rates compared with mastectomy.

CONCLUSIONS

BCS + RT does not impair DFS and OS in patients treated with NCT. Tumor biology and treatment response are significant prognostic indicators. Our results suggest that BCS + RT may be preferred in most breast cancer patients when both BCS and mastectomy are suitable.

In Vivo Validation of Diffuse Optical Imaging with a Dual-Direction Measuring Module of Parallel-Plate Architecture for Breast Tumor Detection

We demonstrate a working prototype of an optical breast imaging system involving parallel-plate architecture and a dual-direction scanning scheme designed in combination with a mammography machine; this system was validated in a pilot study to demonstrate its application in imaging healthy and malignant breasts in a clinical environment. The components and modules of the self-developed imaging system are demonstrated and explained, including its measuring architecture, scanning mechanism, and system calibration, and the reconstruction algorithm is presented. Additionally, the evaluation of feature indices that succinctly demonstrate the corresponding transmission measurements may provide insight into the existence of malignant tissue. Moreover, five cases are presented including one subject without disease (a control measure), one benign case, one suspected case, one invasive ductal carcinoma, and one positive case without follow-up treatment. A region-of-interest analysis demonstrated significant differences in absorption between healthy and malignant breasts, revealing the average contrast between the abnormalities and background tissue to exceed 1.4. Except for ringing artifacts, the average scattering property of the structure densities was 0.65–0.85 mm−1.

Portable, handheld, and affordable blood perfusion imager for screening of subsurface cancer in resource-limited settings

Existing procedures of screening subsurface cancers are either prohibitively resource-intensive and expensive or are unable to provide direct quantitative estimates of the relevant physiological parameters for accurate classification accommodating interpatient variabilities and overlapping clinical manifestations. Here, we introduce a handheld and inexpensive blood perfusion imager that provides a noninvasive in situ screening approach for distinguishing precancer, cancer, and normal scenarios by precise quantitative estimation of the localized blood circulation in the tissue over an unrestricted region of interest without any unwarranted noise in the data, augmented by machine learning–based classification. Clinical trials in minimally resourced settings have established the efficacy of the method in differentiating cancerous and precancerous stages of suspected oral abnormalities, as verified by gold-standard biopsy reports.

Precise information on localized variations in blood circulation holds the key for noninvasive diagnostics and therapeutic assessment of various forms of cancer. While thermal imaging by itself may provide significant insights on the combined implications of the relevant physiological parameters, viz. local blood perfusion and metabolic balance due to active tumors as well as the ambient conditions, knowledge of the tissue surface temperature alone may be somewhat inadequate in distinguishing between some ambiguous manifestations of precancer and cancerous lesions, resulting in compromise of the selectivity in detection. This, along with the lack of availability of a user-friendly and inexpensive portable device for thermal-image acquisition, blood perfusion mapping, and data integration acts as a deterrent against the emergence of an inexpensive, contact-free, and accurate in situ screening and diagnostic approach for cancer detection and management. Circumventing these constraints, here we report a portable noninvasive blood perfusion imager augmented with machine learning–based quantitative analytics for screening precancerous and cancerous traits in oral lesions, by probing the localized alterations in microcirculation. With a proven overall sensitivity >96.66% and specificity of 100% as compared to gold-standard biopsy-based tests, the method successfully classified oral cancer and precancer in a resource-limited clinical setting in a double-blinded patient trial and exhibited favorable predictive capabilities considering other complementary modes of medical image analysis as well. The method holds further potential to achieve contrast-free, accurate, and low-cost diagnosis of abnormal microvascular physiology and other clinically vulnerable conditions, when interpreted along with complementary clinically evidenced decision-making perspectives.

Plasma Proteome Signature to Predict the Outcome of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

The plasma proteome of 51 non-metastatic breast cancer patients receiving neoadjuvant chemotherapy (NCT) was prospectively analyzed by high-resolution mass spectrometry coupled with nano-flow liquid chromatography using blood drawn at the time of diagnosis. Plasma proteins were identified as potential biomarkers, and their correlation with clinicopathological variables and survival outcomes was analyzed. Of 51 patients, 20 (39.2%) were HR+/HER2-, five (9.8%) were HR+/HER2+, five (9.8%) were HER2+, and 21 (41.2%) were triple-negative subtype. During a median follow-up of 52.0 months, there were 15 relapses (29.4%) and eight deaths (15.7%). Four potential biomarkers were identified among differentially expressed proteins: APOC3 had higher plasma concentrations in the pathological complete response (pCR) group, whereas MBL2, ENG, and P4HB were higher in the non-pCR group. Proteins statistically significantly associated with survival and capable of differentiating low- and high-risk groups were MBL2 and P4HB for disease-free survival, P4HB for overall survival, and MBL2 for distant metastasis-free survival (DMFS). In the multivariate analysis, only MBL2 was a consistent risk factor for DMFS (HR: 9.65, 95% CI 2.10-44.31). The results demonstrate that the proteomes from non-invasive sampling correlate with pCR and survival in breast cancer patients receiving NCT. Further investigation may clarify the role of these proteins in predicting prognosis and thus their therapeutic potential for the prevention of recurrence.

Accurately calibrated frequency domain diffuse optical spectroscopy compared against chemical analysis of porcine adipose tissue

Frequency domain diffuse optical spectroscopy (fdDOS) is a noninvasive technique to estimate tissue composition and hemodynamics. While fdDOS has been established as a valuable modality for clinical research, comparison of fdDOS with direct chemical analysis (CA) methods has yet to be reported. To compare the two approaches, we propose a procedure to confirm accurate calibration by use of liquid emulsion and solid silicone phantoms. Tissue fat (FAT) and water (H₂ O) content of two ex vivo porcine tissue samples were optically measured by fdDOS and compared to CA values. We show an average H₂ O error (fdDOS minus CA) and SD of 1.9 ± 0.2% and -0.9 ± 0.2% for the two samples. For FAT, we report a mean error of -9.3 ± 1.3% and 0.8 ± 1.3%. We also measured various body sites of a healthy human subject using fdDOS with results suggesting that accurate calibration may improve device sensitivity.

Coherent confocal light scattering spectroscopic microscopy evaluates cancer progression and aggressiveness in live cells and tissue

The observation of biological structures in live cells beyond the diffraction limit with super-resolution fluorescence microscopy is limited by the ability of fluorescence probes to permeate live cells and the effect of these probes, which are often toxic, on cellular behavior. Here we present a coherent confocal light scattering and absorption spectroscopic microscopy that for the first time enables the use of large numerical aperture optics to characterize structures in live cells down to 10 nm spatial scales, well beyond the diffraction limit. Not only does this new capability allow high resolution microscopy with light scattering contrast, but it can also be used with almost any light scattering spectroscopic application which employs lenses. We demonstrate that the coherent light scattering contrast based technique allows continuous temporal tracking of the transition from non-cancerous to an early cancerous state in live cells, without exogenous markers. We also use the technique to sense differences in the aggressiveness of cancer in live cells and for label free identification of different grades of cancer in resected tumor tissues.

Prediction of chemotherapy response in breast cancer patients at pre-treatment using second derivative texture of CT images and machine learning

•

Textural and second derivative textural features of CT images can be used in conjunction with machine learning models to predict breast cancer response to chemotherapy prior to the start of treatment.

•

The proposed predictive model separates the patients at pre-treatment into two cohorts (responders/non-responders) with significantly different survival.

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The proposed methodology is a step forward towards the precision oncology paradigm for breast cancer patients.

Although neoadjuvant chemotherapy (NAC) is a crucial component of treatment for locally advanced breast cancer (LABC), only about 70% of patients respond to it. Effective adjustment of NAC for individual patients can significantly improve survival rates of those resistant to standard regimens. Thus, the early prediction of NAC outcome is of great importance in facilitating a personalized paradigm for breast cancer therapeutics. In this study, quantitative computed tomography (qCT) parametric imaging in conjunction with machine learning techniques were investigated to predict LABC tumor response to NAC. Textural and second derivative textural (SDT) features of CT images of 72 patients diagnosed with LABC were analysed before the initiation of NAC to quantify intra-tumor heterogeneity. These quantitative features were processed through a correlation-based feature reduction followed by a sequential feature selection with a bootstrap 0.632+ area under the receiver operating characteristic (ROC) curve (AUC0.632+) criterion. The best feature subset consisted of a combination of one textural and three SDT features. Using these features, an AdaBoost decision tree could predict the patient response with a cross-validated AUC0.632+ accuracy, sensitivity and specificity of 0.88, 85%, 88% and 75%, respectively. This study demonstrates, for the first time, that a combination of textural and SDT features of CT images can be used to predict breast cancer response NAC prior to the start of treatment which can potentially facilitate early therapy adjustments.

High optode-density wearable diffuse optical probe for monitoring paced breathing hemodynamics in breast tissue

SIGNIFICANCE

Diffuse optical imaging (DOI) provides in vivo quantification of tissue chromophores such as oxy- and deoxyhemoglobin (HbO2 and HHb, respectively). These parameters have been shown to be useful for predicting neoadjuvant treatment response in breast cancer patients. However, most DOI devices designed for the breast are nonportable, making frequent longitudinal monitoring during treatment a challenge. Furthermore, hemodynamics related to the respiratory cycle are currently unexplored in the breast and may have prognostic value.

AIM

To design, fabricate, and validate a high optode-density wearable continuous wave diffuse optical probe for the monitoring of breathing hemodynamics in breast tissue.

APPROACH

The probe has a rigid-flex design with 16 dual-wavelength sources and 16 detectors. Performance was characterized on tissue-simulating phantoms, and validation was performed through flow phantom and cuff occlusion measurements. The breasts of N  =  4 healthy volunteers were measured while performing a breathing protocol.

RESULTS

The probe has 512 unique source-detector (S-D) pairs that span S-D separations of 10 to 54 mm. It exhibited good performance characteristics: μa drift of 0.34%/h, μa precision of 0.063%, and mean SNR  ≥  24  dB up to 41 mm S-D separation. Absorption contrast was detected in flow phantoms at depths exceeding 28 mm. A cuff occlusion measurement confirmed the ability of the probe to track expected hemodynamics in vivo. Breast measurements on healthy volunteers during paced breathing revealed median signal-to-motion artifact ratios ranging from 8.1 to 8.7 dB. Median ΔHbO2 and ΔHHb amplitudes ranged from 0.39 to 0.67  μM and 0.08 to 0.12  μM, respectively. Median oxygen saturations at the respiratory rate ranged from 82% to 87%.

CONCLUSIONS

A wearable diffuse optical probe has been designed and fabricated for the measurement of breast tissue hemodynamics. This device is capable of quantifying breathing-related hemodynamics in healthy breast tissue.

Real-Time Handheld Probe Tracking and Image Formation Using Digital Frequency-Domain Diffuse Optical Spectroscopy

OBJECTIVE

Frequency-domain diffuse optical spectroscopic imaging (FD-DOS) is a non-invasive method for measuring absolute concentrations of tissue chromophores such as oxy- and deoxy-hemoglobin in vivo. The utility of FD-DOS for clinical applications such as monitoring chemotherapy response in breast cancer has previously been demonstrated, but challenges for further clinical translation, such as slow acquisition speed and lack of user feedback, remain. Here, we propose a new high speed FD-DOS instrument that allows users to freely acquire measurements over the tissue surface, and is capable of rapidly imaging large volumes of tissue.

METHODS

We utilize 3D monocular probe tracking combined with custom digital FD-DOS hardware and a high-speed data processing pipeline for the instrument. Results are displayed during scanning over the surface of the sample using a probabilistic Monte Carlo light propagation model.

RESULTS

We show this instrument can measure absorption and scattering coefficients with an error of 7% and 1% respectively, with 0.7 mm positional accuracy. We demonstrate the equivalence of our visualization methodology with a standard interpolation approach, and demonstrate two proof-of-concept in vivo results showing superficial vasculature in the human forearm and surface contrast in a healthy human breast.

CONCLUSION

Our new FD-DOS system is able to compute chromophore concentrations in real-time (1.5 Hz) in vivo.

SIGNIFICANCE

This method has the potential to improve the quality of FD-DOS image scans while reducing measurement times for a variety of clinical applications.

Changes in Diffuse Optical Tomography Images During Early Stages of Neoadjuvant Chemotherapy Correlate with Tumor Response in Different Breast Cancer Subtypes

PURPOSE

This study's primary objective was to evaluate the changes in optically derived parameters acquired with a diffuse optical tomography breast imaging system (DOTBIS) in the tumor volume of patients with breast carcinoma receiving neoadjuvant chemotherapy (NAC).

EXPERIMENTAL DESIGN

In this analysis of 105 patients with stage II-III breast cancer, normalized mean values of total hemoglobin ([Formula: see text]), oxyhemoglobin ([Formula: see text]), deoxy-hemoglobin concentration ([Formula: see text]), water, and oxygen saturation ([Formula: see text]) percentages were collected at different timepoints during NAC and compared with baseline measurements. This report compared changes in these optical biomarkers measured in patients who did not achieve a pathologic complete response (non-pCR) and those with a pCR. Differences regarding molecular subtypes were included for hormone receptor-positive and HER2-negative, HER2-positive, and triple-negative breast cancer.

RESULTS

At baseline, [Formula: see text] was higher for pCR tumors (3.97 ± 2.29) compared with non-pCR tumors (3.00 ± 1.72; P = 0.031). At the earliest imaging point after starting therapy, the mean change of [Formula: see text] compared with baseline ([Formula: see text]) was statistically significantly higher in non-pCR (1.23 ± 0.67) than in those with a pCR (0.87 ± 0.61; P < 0.0005), and significantly correlated to residual cancer burden classification (r = 0.448; P < 0.0005). [Formula: see text] combined with HER2 status was proposed as a two-predictor logistic model, with AUC = 0.891; P < 0.0005; and 95% confidence interval, 0.812-0.969.

CONCLUSIONS

This study demonstrates that DOTBIS measured features change over time according to tumor pCR status and may predict early in the NAC treatment course whether a patient is responding to NAC.

Optical scattering as an early marker of apoptosis during chemotherapy and antiangiogenic therapy in murine models of prostate and breast cancer

Monitoring of the in vivo tumor state to track therapeutic response in real time may help to evaluate new drug candidates, maximize treatment efficacy, and reduce the burden of overtreatment. Current preclinical tumor imaging methods have largely focused on anatomic imaging (e.g., MRI, ultrasound), functional imaging (e.g., FDG-PET), and molecular imaging with exogenous contrast agents (e.g., fluorescence optical tomography). Here we utalize spatial frequency domain imaging (SFDI), a noninvasive, label-free optical technique, for the wide-field quantification of changes in tissue optical scattering in preclinical tumor models during treatment with chemotherapy and antiangiogenic agents. Optical scattering is particularly sensitive to tissue micro-architectural changes, including those that occur during apoptosis, an early indicator of response to cytotoxicity induced by chemotherapy, thermotherapy, cryotherapy, or radiation therapy. We utilized SFDI to monitor responses of PC3/2G7 prostate tumors and E0771 mammary tumors to treatment with cyclophosphamide or the antiangiogenic agent DC101 for up to 49 days. The SFDI-derived scattering amplitude was highly correlated with cleaved caspase-3, a marker of apoptosis (ρ_p = 0.75), while the exponent of the scattering wavelength-dependence correlated with the cell proliferation marker PCNA (ρ_p = 0.69). These optical parameters outperformed tumor volume and several functional parameters (e.g., oxygen saturation and hemoglobin concentration) as an early predictive biomarker of treatment response. Quantitative diffuse optical scattering is thus a promising new early marker of treatment response, which does not require radiation or exogenous contrast agents.

Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography

BACKGROUND

The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR).

METHODS

In this retrospective evaluation of 105 patients with stage II-III breast cancer, oxy-hemoglobin (ctO₂Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2-3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO₂Hb changes across chemotherapy when corrected for pCR status, age, and BMI.

RESULTS

Patients who achieved pCR to NAC had an overall decrease of 3.88 μM for ctO₂Hb (95% CI, 1.39 to 6.37 μM), p = .004, after 2-3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 μM (95% CI, - 1.30 to 1.58 μM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO₂Hb levels with BMI and age.

CONCLUSIONS

This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2-3 weeks of chemotherapy.

Shortwave-infrared meso-patterned imaging enables label-free mapping of tissue water and lipid content

Water and lipids are key participants in many biological processes, but there are few non-invasive methods that provide quantification of these components in vivo, and none that can isolate and quantify lipids in the blood. Here we develop a new imaging modality termed shortwave infrared meso-patterned imaging (SWIR-MPI) to provide label-free, non-contact, spatial mapping of water and lipid concentrations in tissue. The method utilizes patterned hyperspectral illumination to target chromophore absorption bands in the 900-1,300 nm wavelength range. We use SWIR-MPI to monitor clinically important physiological processes including edema, inflammation, and tumor lipid heterogeneity in preclinical models. We also show that SWIR-MPI can spatially map blood-lipids in humans, representing an example of non-invasive and contact-free measurements of in vivo blood lipids. Together, these results highlight the potential of SWIR-MPI to enable new capabilities in fundamental studies and clinical monitoring of major conditions including obesity, cancer, and cardiovascular disease.

Analysis of the serial circulating tumor cell count during neoadjuvant chemotherapy in breast cancer patients

We evaluated the prognostic implications of the circulating tumor cell (CTC) count in non-metastatic, HER2-negative breast cancer patients who failed to achieve pathologic complete response (pCR) after neoadjuvant chemotherapy (NCT). A total of 173, non-metastatic breast cancer patients treated with NCT were prospectively enrolled. CTCs were obtained from blood drawn pre-NCT and post-NCT using a SMART BIOPSY SYSTEM isolation kit (Cytogen Inc., Seoul, Korea) with immunofluorescence staining. Excluding 26 HER2-positive patients, Relapse-free survival (RFS) and overall survival (OS) related to the CTC count and the association of the CTC count with the treatment response to given therapy were analyzed in 147 HER2-negative patients. Among 147 HER2-negative patients, 28 relapses (19.0%) and 13 deaths (8.8%, all breast cancer-specific) were observed during a median follow-up of 37.3 months. One hundred and seven patients (72.8%) were hormone receptor-positive, and 40 patients (27.2%) had triple-negative breast cancer (TNBC). One or more CTCs were identified in 88 of the 147 patients (59.9%) before NCT and 77 of the 134 patients (52.4%) after NCT. In the entire HER2-negative patient cohort, the initial nodal status was the most significant factor influencing RFS and OS. In TNBC, 11 patients (27.5%) achieved pCR and patients that failed to achieve pCR with ≥ 5 CTCs after NCT, showed worse RFS (HR, 10.66; 95% CI, 1.80–63.07; p = 0.009) and OS (HR, 14.00; 95% CI, 1.26–155.53; p = 0.032). The patients with residual tumor and a high number of the CTCs after NCT displayed the worse outcome. These findings could provide justification to launch a future, well designed trial with longer follow-up data to obtain regulatory approval for clinical use of the assay, especially for the ER-positive, HER2-negative breast cancer subset.

Noninvasive Detection of Differential Water Content Inside Biological Samples Using Deep Raman Spectroscopy

Here we conceptually demonstrate the capability of deep Raman spectroscopy to noninvasively monitor changes in the water content within biological tissues. Water was added by injection into an isolated tissue volume (a 20 mm diameter disk of 5 mm thickness) representing a 20% increase in the overall mass, which was equivalent to a 5% increase in the water/tissue content. The elevated water content was detected through a larger volume of tissue with a total thickness of approximately 12 mm and a spiked tissue segment located in its center using transmission Raman spectroscopy (TRS) by monitoring the change of the OH (∼3390 cm^-1) Raman band area (3350-3550 cm^-1 spectral region) after being normalized to the neighboring CH stretching band. The tissue sample was raster scanned with TRS to yield a spatial map of the water concentration within the sample encompassing the spiked tissue zone. The mapping revealed the presence and location of the spiked region. The results provide the first conceptual demonstration using a deep Raman-based architecture, which can be used noninvasively for the detection of an elevated water content deep within biological tissues. It is envisaged that this concept could play a role in rapid in vivo detection and localization of cancerous lesions (generally exhibiting a higher water content) beneath the tissue surface.

A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning

Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locally advanced breast cancer (LABC) patients. An early prediction of responsiveness to NAC could facilitate treatment adjustments on an individual patient basis that would be expected to improve treatment outcomes and patient survival. This study investigated, for the first time, the efficacy of quantitative computed tomography (qCT) parametric imaging to characterize intra-tumour heterogeneity and its application in predicting tumour response to NAC in LABC patients. Textural analyses were performed on CT images acquired from 72 patients before the start of chemotherapy to determine quantitative features of intra-tumour heterogeneity. The best feature subset for response prediction was selected through a sequential feature selection with bootstrap 0.632 + area under the receiver operating characteristic (ROC) curve (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+) as a performance criterion. Several classifiers were evaluated for response prediction using the selected feature subset. Amongst the applied classifiers an Adaboost decision tree provided the best results with cross-validated \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{A}\mathrm{U}\mathrm{C}}_{0.632+}$$\end{document}AUC0.632+, accuracy, sensitivity and specificity of 0.89, 84%, 80% and 88%, respectively. The promising results obtained in this study demonstrate the potential of the proposed biomarkers to be used as predictors of LABC tumour response to NAC prior to the start of treatment.

Machine Learning-Based A Priori Chemotherapy Response Prediction in Breast Cancer Patients using Textural CT Biomarkers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020;2020:1250-1253. [PMID: 33018214 DOI: 10.1109/embc44109.2020.9176099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Early prediction of cancer response to neoadjuvant chemotherapy (NAC) could permit personalized treatment adjustments for patients, which would improve treatment outcomes and patient survival. For the first time, the efficiency of quantitative computed tomography (qCT) textural and second derivative of textural (SDT) features were investigated and compared in this study. It was demonstrated that intra-tumour heterogeneity can be probed through these biomarkers and used as chemotherapy tumour response predictors in breast cancer patients prior to the start of treatment. These features were used to develop a machine learning approach which provided promising results with cross-validated AUC0.632+, accuracy, sensitivity and specificity of 0.86, 81%, 74% and 88%, respectively.Clinical Relevance- The results obtained in this study demonstrate the potential of textural CT biomarkers as response predictors of standard NAC before treatment initiation.

Method for Quantitative Broadband Diffuse Optical Spectroscopy of Tumor-Like Inclusions

A hybrid reflectance-based diffuse optical imaging (DOI) technique combining discrete wavelength frequency-domain (FD) near-infrared spectroscopy (NIRS) with broadband continuous wave NIRS measurements was developed to quantify the broadband optical properties of deep tumor-like inclusions. This method was developed to more accurately measure the broadband optical properties of human tumors using a compact handheld imaging probe and without requiring a priori spectral constraints. We simulated the reconstruction of absorption and scattering spectra (650–1000 nm) of human breast tumors in a homogeneous background at depths of 0 to 10 mm. The hybrid DOI technique demonstrated enhanced performance in reconstruction of optical absorption with a mean accuracy over all 71 wavelengths of 8.39% versus 32.26% for a 10 mm deep tumor with the topographic DOI method. The new hybrid technique was also tested and validated on two heterogeneous tissue-simulating phantoms with inclusion depths of 2, 7, and 9 mm. The mean optical absorption accuracy over all wavelengths was similarly improved up to 5x for the hybrid DOI method versus topographic DOI for the deepest inclusions.

In vivo and in vitro application of near-infrared fiber optic probe for Ehrlich carcinoma distinction: Towards the development of real-time tumor margins assessment tool

This report describes a full-scale experiment on intradermal Ehrlich carcinoma (EC) differentiation in mouse model using NIR spectroscopy in diffuse reflectance mode and chemometric data processing. EC is widely used as an experimental tumor model due to its resemblance with human undifferentiated epithelial tumors and can be applied as a preclinical testing in order to verify the capability of NIR spectroscopy to distinguish cancer from healthy tissues before a clinical research with an aim of creating a new analytical tool for on-line intraoperative tumor margins assessment. The study consists of five steps of NIR spectra measurements: in vivo on the early stage of carcinoma growth; in vivo on the advanced stage of carcinoma growth; in vivo during the surgery; in vitro study of the post-operative materials stored in formalin; in vitro study of the post-operative materials stored in paraffin. It was shown that reliable tumor differentiation with a compact optic fiber probe was possible in all these cases. The classification models were built on two data sets, obtained during in vivo and in vitro measurements; both of them demonstrated 100% specificity and sensitivity.

Diffuse optical spectroscopy assessment of rodent tumor model oxygen state after single-dose irradiation

Modern radiation therapy of malignant tumors requires careful selection of conditions that can improve the effectiveness of the treatment. The study of the dynamics and mechanisms of tumor reoxygenation after radiation therapy makes it possible to select the regimens for optimizing the ongoing treatment. Diffuse optical spectroscopy (DOS) is among the methods used for non-invasive assessment of tissue oxygenation. In this work DOS was used forin vivoregistration of changes in oxygenation level of an experimental rat tumor after single-dose irradiation at a dose of 10 Gy and investigation of their possible mechanisms. It was demonstrated that in 24 h after treatment, tumor oxygenation increases, which is mainly due to an increase in the oxygen supply to the tissues. DOS is demonstrated to be efficient for study of changes in blood flow parameters when monitoring tumor response to therapy.

Monitoring of tumor burden in vivo by optical imaging in a xenograft SCID mouse model: evaluation of two fluorescent proteins of the GFP-superfamily

BACKGROUND

Mouse models of human-malignant-melanoma (MM) are important tools to study tumor dynamics. The enhanced green fluorescent protein (EGFP) is widely used in molecular imaging approaches, together with optical scanners, and fluorescence imaging.

PURPOSE

Currently, there are no data available as to whether other fluorescent proteins are more suitable. The goal of this preclinical study was to analyze two fluorescent proteins of the GFP superfamily under real-time in vivo conditions using fluorescence reflectance imaging (FRI).

MATERIAL AND METHODS

The human melanoma cell line MeWo was stable transfected with one plasmid: pEGFP-C1 or pDsRed1-N1. We investigated two severe combined immunodeficiency (SCID)-mice groups: A (solid xenografts) and B (xenografts as metastases). After three weeks, the animals were weekly imaged by FRI. Afterwards the mice were euthanized and metastases were imaged in situ: to quantify the cutis-dependent reduction of emitted light, we compared signal intensities obtained by metastases in vivo with signal intensities obtained by in situ liver parenchyma preparations.

RESULTS

More than 90% of cells were stable transfected. EGFP-/DsRed-xenograft tumors had identical growth kinetics. In vivo the emitted light by DsRed tumors/metastases was much brighter than by EGFP. DsRed metastases were earlier (3 vs. 5 weeks) and much more sensitive detectable than EGFP metastases. Cutis-dependent reduction of emitted light was greater in EGFP than in DsRed mice (tenfold). Autofluorescence of DsRed was lower than of EGFP.

CONCLUSION

We established an in vivo xenograft mouse model (DsRed-MeWo) that is reliable, reproducible, and superior to the EGFP model as a preclinical tool to study innovative therapies by FRI under real-time in vivo conditions.

Tissue oxygen saturation predicts response to breast cancer neoadjuvant chemotherapy within 10 days of treatment

Ideally, neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3- to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (StO2) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC  =  0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue StO2 to surrounding tissue StO2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer.

Diffuse optical spectroscopy for monitoring the responses of patients with breast cancer to neoadjuvant chemotherapy: A meta-analysis

BACKGROUND

This study aimed to investigate the potential of diffuse optical spectroscopy (DOT) for monitoring the responses of patients with breast cancer to neoadjuvant chemotherapy (NAC).

METHODS

We searched PubMed, EMBASE, Cochrane Database of Systematic Reviews, and Web of Science for relevant studies. Data were extracted for pooled analysis, heterogeneity testing, threshold effect testing, sensitivity analysis, publication bias analysis, and subgroup analysis.

RESULTS

The pooled meta-analysis of the 10 eligible studies that included 422 patients indicated the high performance of DOT for monitoring total patient responses to NAC (OR = 14.78, 95% CI: 8.23-26.54, P < .001), with low significant heterogeneity (I = 7.2%, P = .375). DOT possessed an area under the curve of 0.84 (95% CI: 0.81-0.87) to distinguish total patient responses to NAC. Subgroup analysis showed that the pooled sensitivity of DOT for monitoring pathologic complete response to NAC was 87%, and the pooled specificity was 70%. Meanwhile, the pooled sensitivity of DOT for monitoring pathologic complete and partial responses to NAC was 82%, and the pooled specificity was 82%. Although Begg's funnel plot (P = .049) indicated the presence of publication bias among the included studies, trim-and-fill method verified the stability of the pooled outcomes.

CONCLUSION

Our meta-analysis of available published data indicated that DOT can be potentially used to predict and monitor patient responses to NAC. A larger study population is needed to fully assess the use of DOT for guiding therapies and predicting responses of individual subjects to NAC.

Recent methodology advances in fluorescence molecular tomography

Molecular imaging (MI) is a novel imaging discipline that has been continuously developed in recent years. It combines biochemistry, multimodal imaging, biomathematics, bioinformatics, cell & molecular physiology, biophysics, and pharmacology, and it provides a new technology platform for the early diagnosis and quantitative analysis of diseases, treatment monitoring and evaluation, and the development of comprehensive physiology. Fluorescence Molecular Tomography (FMT) is a type of optical imaging modality in MI that captures the three-dimensional distribution of fluorescence within a biological tissue generated by a specific molecule of fluorescent material within a biological tissue. Compared with other optical molecular imaging methods, FMT has the characteristics of high sensitivity, low cost, and safety and reliability. It has become the research frontier and research hotspot of optical molecular imaging technology. This paper took an overview of the recent methodology advances in FMT, mainly focused on the photon propagation model of FMT based on the radiative transfer equation (RTE), and the reconstruction problem solution consist of forward problem and inverse problem. We introduce the detailed technologies utilized in reconstruction of FMT. Finally, the challenges in FMT were discussed. This survey aims at summarizing current research hotspots in methodology of FMT, from which future research may benefit.

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.

Breast tumor hemodynamic response during a breath-hold as a biomarker to predict chemotherapeutic efficacy: preclinical study

Continuous wave diffuse optical tomographic/spectroscopic system does not provide absolute concentrations of chromophores in tissue and monitor only the changes of chromophore concentration. Therefore, it requires a perturbation of physiological signals, such as blood flow and oxygenation. In that sense, a few groups reported that monitoring a relative hemodynamic change during a breast tissue compression or a breath-hold to a patient can provide good contrast between tumor and nontumor. However, no longitudinal study reports the utilization of a breath-hold to predict tumor response during chemotherapy. A continuous wave near-infrared spectroscopy was employed to monitor hemodynamics in rat breast tumor during a hyperoxic to normoxic inhalational gas intervention to mimic a breath-hold during tumor growth and chemotherapy. The reduced oxyhemoglobin concentration during inhalational gas intervention correlated well with tumor growth, and it responded one day earlier than the change of tumor volume after chemotherapy. In conclusion, monitoring tumor hemodynamics during a breath-hold may serve as a biomarker to predict chemotherapeutic efficacy of tumor.

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.

Quantitative real-time optical imaging of the tissue metabolic rate of oxygen consumption

The tissue metabolic rate of oxygen consumption (tMRO2) is a clinically relevant marker for a number of pathologies including cancer and arterial occlusive disease. We present and validate a noncontact method for quantitatively mapping tMRO2 over a wide, scalable field of view at 16  frames  /  s. We achieve this by developing a dual-wavelength, near-infrared coherent spatial frequency-domain imaging (cSFDI) system to calculate tissue optical properties (i.e., absorption, μa, and reduced scattering, μs', parameters) as well as the speckle flow index (SFI) at every pixel. Images of tissue oxy- and deoxyhemoglobin concentration (  [  HbO2  ]   and [HHb]) are calculated from optical properties and combined with SFI to calculate tMRO2. We validate the system using a series of yeast-hemoglobin tissue-simulating phantoms and conduct in vivo tests in humans using arterial occlusions that demonstrate sensitivity to tissue metabolic oxygen debt and its repayment. Finally, we image the impact of cyanide exposure and toxicity reversal in an in vivo rabbit model showing clear instances of mitochondrial uncoupling and significantly diminished tMRO2. We conclude that dual-wavelength cSFDI provides rapid, quantitative, wide-field mapping of tMRO2 that can reveal unique spatial and temporal dynamics relevant to tissue pathology and viability.

Noninvasive optical spectroscopy for identification of non-melanoma skin cancer: Pilot study

OBJECTIVE

Optical spectroscopy offers a noninvasive alternative to biopsy as a first-line screening tool for suspicious skin lesions. This study sought to define several optical parameters across malignant and benign tissue types.

STUDY DESIGN

Prospective pilot trial utilizing the Zenalux IM1 optical spectroscopy device from April 2016 to February 2017. For each skin lesion, provider pre-biopsy probability of malignancy was compared to histolopathologic diagnosis. Optical data were characterized across basal cell carcinoma (BCC; n = 9), squamous cell carcinoma (SCC; n = 5), actinic keratosis (AK; n = 4), scar tissue (n = 6), nevus (n = 2), and neurofibroma (NF; n = 1). Across all patients, agreement was determined between control measurements collected adjacent to the lesion and from the upper extremity.

METHODS

Prospective single center pilot study. The optical properties of 27 cutaneous lesions were collected from 18 adult patients presenting to Otolaryngology and Dermatology clinics with suspicious skin lesions warranting biopsy. Spectroscopy measurements were recorded for each lesion: two at the lesion site, two at an adjacent site (internal control), and one at the central medial upper extremity (arm control). Variables of interest included absolute oxygenated hemoglobin (Hb), Hb saturation, total Hb concentration, and Eumelanin concentration. For each lesion, internal control averages were subtracted from lesion averages to provide delta parameter values, and lesion averages were divided by internal control averages to provide ratio parameter values.

RESULTS

Mean percent difference between pre-biopsy probability of malignancy and histology was 29%, with a difference of 75% or greater seen in 5 of 25 lesions. Mean values for BCC, SCC, AK, and scar tissue varied most between extracted mean reduced scatter estimate (μa'; cm- ) delta values (BCC: -2.2 ± 3.8; SCC: -3.9 ± 2.0; AK: -3.3 ± 4.2, Scar: -1.7 ± 1.2) and total Hb (µM) ratio (BCC: 2.0 ± 3.3; SCC: 3.0 ± 1.3; AK: 1.1 ± 0.6; Scar: 1.4 ± 1.1). Agreement between local and arm controls was poor.

CONCLUSION

This pilot trial utilizes optical spectroscopy as a noninvasive method for determining cutaneous lesion histology. Effect sizes observed across optical parameters for benign and malignant tissue types will guide larger prospective studies that may ultimately lead to prediction of lesional histology without need for invasive biopsy. Lasers Surg. Med. 50:246-252, 2018. © 2018 Wiley Periodicals, Inc.

Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer

Purpose To identify dynamic optical imaging features that associate with the degree of pathologic response in patients with breast cancer during neoadjuvant chemotherapy (NAC). Materials and Methods Of 40 patients with breast cancer who participated in a longitudinal study between June 2011 and March 2016, 34 completed the study. There were 13 patients who obtained a pathologic complete response (pCR) and 21 patients who did not obtain a pCR. Imaging data from six subjects were excluded from the study because either the patients dropped out of the study before it was finished or there was an instrumentation malfunction. Two weeks into the treatment regimen, three-dimensional images of both breasts during a breath hold were acquired by using dynamic diffuse optical tomography. Features from the breath-hold traces were used to distinguish between response groups. Receiver operating characteristic (ROC) curves and sensitivity analysis were used to determine the degree of association with 5-month treatment outcome. Results An ROC curve analysis showed that this method could identify patients with a pCR with a positive predictive value of 70.6% (12 of 17), a negative predictive value of 94.1% (16 of 17), a sensitivity of 92.3% (12 of 13), a specificity of 76.2% (16 of 21), and an area under the ROC curve of 0.85. Conclusion Several dynamic optical imaging features obtained within 2 weeks of NAC initiation were identified that showed statistically significant differences between patients with pCR and patients without pCR as determined 5 months after treatment initiation. If confirmed in a larger cohort prospective study, these dynamic imaging features may be used to predict treatment outcome as early as 2 weeks after treatment initiation. ^© RSNA, 2018 Online supplemental material is available for this article.

Emerging Breast Imaging Technologies on the Horizon

Early detection of breast cancers by mammography in conjunction with adjuvant therapy has contributed to reduction in breast cancer mortality. Mammography remains the "gold-standard" for breast cancer screening but is limited by tissue superposition. Digital breast tomosynthesis and more recently, dedicated breast computed tomography have been developed to alleviate the tissue superposition problem. However, all of these modalities rely upon x-ray attenuation contrast to provide anatomical images, and there are ongoing efforts to develop and clinically translate alternative modalities. These emerging modalities could provide for new contrast mechanisms and may potentially improve lesion detection and diagnosis. In this article, several of these emerging modalities are discussed with a focus on technologies that have advanced to the stage of in vivo clinical evaluation.

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features

Background

Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer.

Methods

The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times.

Results

Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the three response groups with accuracies less than 60% at all scan time points. Recurrence free survival (RFS) of response groups determined based on combined features followed similar trend as determined based on clinical and pathology.

Conclusions

This work demonstrates the potential of using QUS, texture and molecular features for predicting the response of primary breast tumors to chemotherapy early, and guiding the treatment planning of refractory patients.

Change of tumor vascular reactivity during tumor growth and postchemotherapy observed by near-infrared spectroscopy

Breast cancer is one of the most common cancers in females. To monitor chemotherapeutic efficacy for breast cancer, medical imaging systems such as x-ray mammography, computed tomography, magnetic resonance imaging, and ultrasound imaging have been used. Currently, it can take up to 3 to 6 weeks to see the tumor response from chemotherapy by monitoring tumor volume changes. We used near-infrared spectroscopy (NIRS) to predict breast cancer treatment efficacy earlier than tumor volume changes by monitoring tumor vascular reactivity during inhalational gas interventions. The results show that the amplitude of oxy-hemoglobin changes (vascular reactivity) during hyperoxic gas inhalation is well correlated with tumor growth and responded one day earlier than tumor volume changes after chemotherapy. These results may imply that NIRS with respiratory challenges can be useful in early detection of tumor and in the prediction of tumor response to chemotherapy.

Noninvasive optical imaging of resistance training adaptations in human muscle

A quantitative and dynamic analysis of skeletal muscle structure and function can guide training protocols and optimize interventions for rehabilitation and disease. While technologies exist to measure body composition, techniques are still needed for quantitative, long-term functional imaging of muscle at the bedside. We evaluate whether diffuse optical spectroscopic imaging (DOSI) can be used for long-term assessment of resistance training (RT). DOSI measures of tissue composition were obtained from 12 adults before and after 5 weeks of training and compared to lean mass fraction (LMF) from dual-energy X-ray absorptiometry (DXA). Significant correlations were detected between DXA LMF and DOSI-measured oxy-hemo/myoglobin, deoxy-hemo/myoglobin, total-hemo/myoglobin, water, and lipid. RT-induced increases of ∼6% in oxy-hemo/myoglobin (3.4±1.0  μM, p=0.00314) and total-hemo/myoglobin (4.9±1.1  μM, p=0.00024) from the medial gastrocnemius were detected with DOSI and accompanied by ∼2% increases in lean soft tissue mass (36.4±12.4  g, p=0.01641) and ∼60% increases in 1 rep-max strength (41.5±6.2  kg, p=1.9E-05). DOSI measures of vascular and/or muscle changes combined with correlations between DOSI and DXA suggest that quantitative diffuse optical methods can be used to evaluate body composition, provide feedback on long-term interventions, and generate new insight into training-induced muscle adaptations.

Predicting Treatment Response of Breast Cancer to Neoadjuvant Chemotherapy Using Ultrasound-Guided Diffuse Optical Tomography

PURPOSE

To prospectively investigate ultrasound-guided diffuse optical tomography (US-guided DOT) in predicting breast cancer response to neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

Eighty-eight breast cancer patients, with a total of 93 lesions, were included in our study. Pre- and post-last chemotherapy, size and total hemoglobin concentration (THC) of each lesion were measured by conventional US and US-guided DOT 1 day before biopsy (time point t0, THC THC0, SIZE S0) and 1 to 2 days before surgery (time point tL, THCL, SL). The relative changes in THC and SIZE of lesions after the first and last NAC cycles were considered as the variables ΔTHC and ΔSIZE. Receiver operating characteristic curve was performed to calculate ΔTHC and ΔSIZE cutoff values to evaluate pathologic response of 93 breast cancers to NAC, which were then prospectively used to predicate response of 61 breast cancers to NAC.

RESULTS

The cutoff values of ΔTHC and ΔSIZE for evaluation of breast cancers NAC treatment response were 23.9% and 42.6%. At ΔTHC 23.9%, the predicted treatment response in 61 breast lesions for the time points t1 to t3 was calculated by area under the curve (AUC), which were AUC₁ 0.534 (P=.6668), AUC₂ 0.604 (P=.1893), and AUC₃ 0.674(P =. 0.027), respectively; for ΔSIZE 42.6%, at time points t1 to t3, AUC₁ 0.505 (P=.9121), AUC₂ 0.645 (P=.0115), and AUC₃ 0.719 (P=.0018).

CONCLUSION

US-guided DOT ΔTHC 23.9% and US ΔSIZE 42.6% can be used for the response evaluation and earlier prediction of the pathological response after three rounds of chemotherapy.

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.

Imaging Considerations and Interprofessional Opportunities in the Care of Breast Cancer Patients in the Neoadjuvant Setting

OBJECTIVE

To discuss standard-of-care and emerging imaging techniques employed for screening and detection, diagnosis and staging, monitoring response to therapy, and guiding cancer treatments.

DATA SOURCES

Published journal articles indexed in the National Library of Medicine database and relevant websites.

CONCLUSION

Imaging plays a fundamental role in the care of cancer patients and specifically, breast cancer patients in the neoadjuvant setting, providing an excellent opportunity for interprofessional collaboration between oncologists, researchers, radiologists, and oncology nurses. Quantitative imaging strategies to assess cellular, molecular, and vascular characteristics within the tumor is needed to better evaluate initial diagnosis and treatment response.

IMPLICATIONS FOR NURSING PRACTICE

Nurses caring for patients in all settings must continue to seek education on emerging imaging techniques. Oncology nurses provide education about the test, ensure the patient has appropriate pre-testing instructions, and manage patient expectations about timing of results availability.

Prediction of neoadjuvant chemotherapy response using diffuse optical spectroscopy in breast cancer

PURPOSE

Near-infrared diffuse optical spectroscopy (DOS) has been recently used to predict neoadjuvant chemotherapy response (NAC). In the present study, we explore the change in blood-oxygen content using DOS to predict NAC response against breast cancer.

MATERIALS AND METHODS

A total of 20 patients were enrolled and underwent DOS scan with blood-oxygen detection before each treatment cycle. The first DOS scan was performed before NAC treatment (pretreatment), and subsequent scans were performed after each NAC treatment circle. Changes in blood content and oxygen content by DOS were evaluated and compared with tumor size, and their changes were analyzed in response versus nonresponse group.

RESULTS

Thirteen patients were classified into response and seven patients into nonresponse group. The tumor blood content value (-1.06 ± 0.43) and oxygen content value (0.48 ± 0.17) of DOS at pretreatment was significantly different from presurgery in response group (P < 0.05), but not in nonresponse group. In response group, the percentage change in blood content (median 91.19%) was significantly larger than tumor size (median 48.89%) (P = 0.0035), while in oxygen content (median 47.11%) is not (P = 0.2815). Comparing each cycle, the percentage change in blood content could distinguish responder from non-responder as early as after the first treatment cycle (19.1 versus 6.6%, P = 0.0265). Blood content percentage sensitivity was 76.9% and specificity was 85.7% (AUC 0.912), while oxygen content percentage sensitivity was 76.9% and specificity was 71.4% (AUC 0.797).

CONCLUSION

Both blood and oxygen content measured by DOS could be used to discriminate responder to the treatment versus non-responder. Among the two, percentage change of blood content was more precise and earlier than that of oxygen content to predicted breast tumor response. The percentage change in blood content could distinguish responder from non-responder after the first treatment cycle.

Multispectral Optoacoustic Tomography (MSOT) of Human Breast Cancer

Purpose: In a pilot study, we introduce fast handheld multispectral optoacoustic tomography (MSOT) of the breast at 28 wavelengths, aiming to identify high-resolution optoacoustic (photoacoustic) patterns of breast cancer and noncancerous breast tissue.Experimental Design: We imaged 10 female patients ages 48-81 years with malignant nonspecific breast cancer or invasive lobular carcinoma. Three healthy volunteers ages 31-36 years were also imaged. Fast-MSOT was based on unique single-frame-per-pulse (SFPP) image acquisition employed to improve the accuracy of spectral differentiation over using a small number of wavelengths. Breast tissue was illuminated at the 700-970 nm spectral range over 0.56 seconds total scan time. MSOT data were guided by ultrasonography and X-ray mammography or MRI.Results: The extended spectral range allowed the computation of oxygenated hemoglobin (HBO₂), deoxygenated hemoglobin (HB), total blood volume (TBV), lipid, and water contributions, allowing first insights into in vivo high-resolution breast tissue MSOT cancer patterns. TBV and Hb/HBO₂ images resolved marked differences between cancer and control tissue, manifested as a vessel-rich tumor periphery with highly heterogeneous spatial appearance compared with healthy tissue. We observe significant TBV variations between different tumors and between tumors over healthy tissues. Water and fat lipid layers appear disrupted in cancer versus healthy tissue; however, offer weaker contrast compared with TBV images.Conclusions: In contrast to optical methods, MSOT resolves physiologic cancer features with high resolution and revealed patterns not offered by other radiologic modalities. The new features relate to personalized and precision medicine potential. Clin Cancer Res; 23(22); 6912-22. ©2017 AACR.

Collagen quantification in breast tissue using a 12-wavelength near infrared spectral tomography (NIRST) system

A portable near infrared spectral tomography (NIRST) system was adapted for breast cancer detection and treatment monitoring with improved speed of acquisition for parallel 12 wavelengths of parallel frequency-domain (FD) and continuous-wavelength (CW) measurement. Using a novel gain adjustment scheme in the Photomultiplier Tube detectors (PMTs), the data acquisition time for simultaneous acquisition involving three FD and three CW wavelengths, has been reduced from 90 to 55 seconds, while signal variation was also reduced from 2.1% to 1.1%. Tomographic images of breast collagen content have been recovered for the first time, and image reconstruction approaches with and without collagen content included have been validated in simulation studies and normal subject exams. Simulations indicate that including collagen content into the reconstruction procedure can significantly reduce the overestimation in total hemoglobin, water and lipid by 8.9μM, 1.8% and 15.8%, respectively, and underestimates in oxygen saturation by 9.5%, given an average 10% background collagen content. A breast cancer patient with invasive ductal carcinoma was imaged and the reconstructed images show that the recovered tumor/background contrast in total hemoglobin increased from 1.5 to 1.7 when collagen was included in reconstruction.

Feasibility of spatial frequency-domain imaging for monitoring palpable breast lesions

In breast cancer diagnosis and therapy monitoring, there is a need for frequent, noninvasive disease progression evaluation. Breast tumors differ from healthy tissue in mechanical stiffness as well as optical properties, which allows optical methods to detect and monitor breast lesions noninvasively. Spatial frequency-domain imaging (SFDI) is a reflectance-based diffuse optical method that can yield two-dimensional images of absolute optical properties of tissue with an inexpensive and portable system, although depth penetration is limited. Since the absorption coefficient of breast tissue is relatively low and the tissue is quite flexible, there is an opportunity for compression of tissue to bring stiff, palpable breast lesions within the detection range of SFDI. Sixteen breast tissue-mimicking phantoms were fabricated containing stiffer, more highly absorbing tumor-mimicking inclusions of varying absorption contrast and depth. These phantoms were imaged with an SFDI system at five levels of compression. An increase in absorption contrast was observed with compression, and reliable detection of each inclusion was achieved when compression was sufficient to bring the inclusion center within ∼12  mm of the phantom surface. At highest compression level, contrasts achieved with this system were comparable to those measured with single source-detector near-infrared spectroscopy.