Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study.

Background: In patients with locally advanced breast cancer (LABC) receiving neoadjuvant chemotherapy (NAC), quantitative ultrasound (QUS) radiomics can predict final responses early within 4 of 16-18 weeks of treatment. The current study was planned to study the feasibility of a QUS-radiomics model-guided adaptive chemotherapy. Methods: The phase 2 open-label randomized controlled trial included patients with LABC planned for NAC. Patients were randomly allocated in 1:1 ratio to a standard arm or experimental arm stratified by hormonal receptor status. All patients were planned for standard anthracycline and taxane-based NAC as decided by their medical oncologist. Patients underwent QUS imaging using a clinical ultrasound device before the initiation of NAC and after the 1st and 4th weeks of treatment. A support vector machine-based radiomics model developed from an earlier cohort of patients was used to predict treatment response at the 4th week of NAC. In the standard arm, patients continued to receive planned chemotherapy with the treating oncologists blinded to results. In the experimental arm, the QUS-based prediction was conveyed to the responsible oncologist, and any changes to the planned chemotherapy for predicted non-responders were made by the responsible oncologist. All patients underwent surgery following NAC, and the final response was evaluated based on histopathological examination. Results: Between June 2018 and July 2021, 60 patients were accrued in the study arm, with 28 patients in each arm available for final analysis. In patients without a change in chemotherapy regimen (53 of 56 patients total), the QUS-radiomics model at week 4 of NAC that was used demonstrated an accuracy of 97%, respectively, in predicting the final treatment response. Seven patients were predicted to be non-responders (observational arm (n=2), experimental arm (n=5)). Three of 5 non-responders in the experimental arm had chemotherapy regimens adapted with an early initiation of taxane therapy or chemotherapy intensification, or early surgery and ended up as responders on final evaluation. Conclusion: The study demonstrates the feasibility of QUS-radiomics adapted guided NAC for patients with breast cancer. The ability of a QUS-based model in the early prediction of treatment response was prospectively validated in the current study. Clinical trial registration: clinicaltrials.gov, ID NCT04050228.

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.

Radiation enhancement using focussed ultrasound-stimulated microbubbles for breast cancer: A Phase 1 clinical trial.

BACKGROUND: Preclinical studies have demonstrated that tumour cell death can be enhanced 10- to 40-fold when radiotherapy is combined with focussed ultrasound-stimulated microbubble (FUS-MB) treatment. The acoustic exposure of microbubbles (intravascular gas microspheres) within the target volume causes bubble cavitation, which induces perturbation of tumour vasculature and activates endothelial cell apoptotic pathways responsible for the ablative effect of stereotactic body radiotherapy. Subsequent irradiation of a microbubble-sensitised tumour causes rapid increased tumour death. The study here presents the mature safety and efficacy outcomes of magnetic resonance (MR)-guided FUS-MB (MRgFUS-MB) treatment, a radioenhancement therapy for breast cancer. METHODS AND FINDINGS: This prospective, single-center, single-arm Phase 1 clinical trial included patients with stages I-IV breast cancer with in situ tumours for whom breast or chest wall radiotherapy was deemed adequate by a multidisciplinary team (clinicaltrials.gov identifier: NCT04431674). Patients were excluded if they had contraindications for contrast-enhanced MR or microbubble administration. Patients underwent 2 to 3 MRgFUS-MB treatments throughout radiotherapy. An MR-coupled focussed ultrasound device operating at 800 kHz and 570 kPa peak negative pressure was used to sonicate intravenously administrated microbubbles within the MR-guided target volume. The primary outcome was acute toxicity per Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Secondary outcomes were tumour response at 3 months and local control (LC). A total of 21 female patients presenting with 23 primary breast tumours were enrolled and allocated to intervention between August/2020 and November/2022. Three patients subsequently withdrew consent and, therefore, 18 patients with 20 tumours were included in the safety and LC analyses. Two patients died due to progressive metastatic disease before 3 months following treatment completion and were excluded from the tumour response analysis. The prescribed radiation doses were 20 Gy/5 fractions (40%, n = 8/20), 30 to 35 Gy/5 fractions (35%, n = 7/20), 30 to 40 Gy/10 fractions (15%, n = 3/20), and 66 Gy/33 fractions (10%, n = 2/20). The median follow-up was 9 months (range, 0.3 to 29). Radiation dermatitis was the most common acute toxicity (Grade 1 in 16/20, Grade 2 in 1/20, and Grade 3 in 2/20). One patient developed grade 1 allergic reaction possibly related to microbubbles administration. At 3 months, 18 tumours were evaluated for response: 9 exhibited complete response (50%, n = 9/18), 6 partial response (33%, n = 6/18), 2 stable disease (11%, n = 2/18), and 1 progressive disease (6%, n = 1/18). Further follow-up of responses indicated that the 6-, 12-, and 24-month LC rates were 94% (95% confidence interval [CI] [84%, 100%]), 88% (95% CI [75%, 100%]), and 76% (95% CI [54%, 100%]), respectively. The study's limitations include variable tumour sizes and dose fractionation regimens and the anticipated small sample size typical for a Phase 1 clinical trial. CONCLUSIONS: MRgFUS-MB is an innovative radioenhancement therapy associated with a safe profile, potentially promising responses, and durable LC. These results warrant validation in Phase 2 clinical trials. TRIAL REGISTRATION: clinicaltrials.gov, identifier NCT04431674.

In Vivo Validation of an In Situ Calibration Bead as a Reference for Backscatter Coefficient Calculation.

OBJECTIVE: The study described here was aimed at assessing the capability of quantitative ultrasound (QUS) based on the backscatter coefficient (BSC) for classifying disease states, such as breast cancer response to neoadjuvant chemotherapy and quantification of fatty liver disease. We evaluated the effectiveness of an in situ titanium (Ti) bead as a reference target in calibrating the system and mitigating attenuation and transmission loss effects on BSC estimation. METHODS: Traditional BSC estimation methods require external references for calibration, which do not account for ultrasound attenuation or transmission losses through tissues. To address this issue, we used an in situ Ti bead as a reference target, because it can be used to calibrate the system and mitigate the attenuation and transmission loss effects on estimation of the BSC. The capabilities of the in situ calibration approach were assessed by quantifying consistency of BSC estimates from rabbit mammary tumors (N = 21). Specifically, mammary tumors were grown in rabbits and when a tumor reached ≥1 cm in size, a 2 mm Ti bead was implanted in the tumor as a radiological marker and a calibration source for ultrasound. Three days later, the tumors were scanned with an L-14/5 38 array transducer connected to a SonixOne scanner with and without a slab of pork belly placed on top of the tumors. The pork belly acted as an additional source of attenuation and transmission loss. QUS parameters, specifically effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were calculated using calibration spectra from both an external reference phantom and the Ti bead. RESULTS: For ESD estimation, the 95% confidence interval between measurements with and without the pork belly layer was 6.0, 27.4 using the in situ bead and 114, 135.1 with the external reference phantom. For EAC estimation, the 95% confidence intervals were -8.1, 0.5 for the bead and -41.5, -32.2 for the phantom. These results indicate that the in situ bead method has reduced bias in QUS estimates because of intervening tissue losses. CONCLUSION: The use of an in situ Ti bead as a radiological marker not only serves its traditional role but also effectively acts as a calibration target for QUS methods. This approach accounts for attenuation and transmission losses in tissue, resulting in more accurate QUS estimates and offering a promising method for enhanced disease state classification in clinical settings.

Quantitative US Delta Radiomics to Predict Radiation Response in Individuals with Head and Neck Squamous Cell Carcinoma.

Purpose To investigate the role of quantitative US (QUS) radiomics data obtained after the 1st week of radiation therapy (RT) in predicting treatment response in individuals with head and neck squamous cell carcinoma (HNSCC). Materials and Methods This prospective study included 55 participants (21 with complete response [median age, 65 years {IQR: 47-80 years}, 20 male, one female; and 34 with incomplete response [median age, 59 years {IQR: 39-79 years}, 33 male, one female) with bulky node-positive HNSCC treated with curative-intent RT from January 2015 to October 2019. All participants received 70 Gy of radiation in 33-35 fractions over 6-7 weeks. US radiofrequency data from metastatic lymph nodes were acquired prior to and after 1 week of RT. QUS analysis resulted in five spectral maps from which mean values were extracted. We applied a gray-level co-occurrence matrix technique for textural analysis, leading to 20 QUS texture and 80 texture-derivative parameters. The response 3 months after RT was used as the end point. Model building and evaluation utilized nested leave-one-out cross-validation. Results Five delta (Δ) parameters had statistically significant differences (P < .05). The support vector machines classifier achieved a sensitivity of 71% (15 of 21), a specificity of 76% (26 of 34), a balanced accuracy of 74%, and an area under the receiver operating characteristic curve of 0.77 on the test set. For all the classifiers, the performance improved after the 1st week of treatment. Conclusion A QUS Δ-radiomics model using data obtained after the 1st week of RT from individuals with HNSCC predicted response 3 months after treatment completion with reasonable accuracy. Keywords: Computer-Aided Diagnosis (CAD), Ultrasound, Radiation Therapy/Oncology, Head/Neck, Radiomics, Quantitative US, Radiotherapy, Head and Neck Squamous Cell Carcinoma, Machine Learning Clinicaltrials.gov registration no. NCT03908684 Supplemental material is available for this article. © RSNA, 2024.

Spectral-based Quantitative Ultrasound Imaging Processing Techniques: Comparisons of RF Versus IQ Approaches.

Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization. Typical spectral-based parameters include the backscatter coefficient (BSC) and attenuation coefficient slope (ACS). Traditionally, spectral-based QUS relies on the radio frequency (RF) signal to calculate the spectral-based parameters. Many clinical and research scanners only provide the in-phase and quadrature (IQ) signal. To acquire the RF data, the common approach is to convert IQ signal back into RF signal via mixing with a carrier frequency. In this study, we hypothesize that the performance, that is, accuracy and precision, of spectral-based parameters calculated directly from IQ data is as good as or better than using converted RF data. To test this hypothesis, estimation of the BSC and ACS using RF and IQ data from software, physical phantoms and in vivo rabbit data were analyzed and compared. The results indicated that there were only small differences in estimates of the BSC between when using the original RF, the IQ derived from the original RF and the RF reconverted from the IQ, that is, root mean square errors (RMSEs) were less than 0.04. Furthermore, the structural similarity index measure (SSIM) was calculated for ACS maps with a value greater than 0.96 for maps created using the original RF, IQ data and reconverted RF. On the other hand, the processing time using the IQ data compared to RF data were substantially less, that is, reduced by more than a factor of two. Therefore, this study confirms two things: (1) there is no need to convert IQ data back to RF data for conducting spectral-based QUS analysis, because the conversion from IQ back into RF data can introduce artifacts. (2) For the implementation of real-time QUS, there is an advantage to convert the original RF data into IQ data to conduct spectral-based QUS analysis because IQ data-based QUS can improve processing speed.

In vivo validation of an in situ calibration bead as a reference for backscatter coefficient calculation.

Objectives: The study aims to assess the capability of Quantitative Ultrasound (QUS) based on the backscatter coefficient (BSC) for classifying disease states, such as breast cancer response to neoadjuvant chemotherapy and quantifying fatty liver disease. We evaluate the effectiveness of an in situ titanium (Ti) bead as a reference target in calibrating the system and mitigating attenuation and transmission loss effects on BSC estimation. Methods: Traditional BSC estimation methods require external references for calibration, which do not account for ultrasound attenuation or transmission losses through tissues. To address this issue, we use an in situ titanium (Ti) bead as a reference target, because it can be used to calibrate the system and mitigate the attenuation and transmission loss effects on estimation of the BSC. The capabilities of the in situ calibration approach were assessed by quantifying consistency of BSC estimates from rabbit mammary tumors (N=21). Specifically, mammary tumors were grown in rabbits and when a tumor reached 1 cm or greater in size, a 2-mm Ti bead was implanted into the tumor as a radiological marker and a calibration source for ultrasound. Three days later, the tumors were scanned with a L-14/5 38 array transducer connected to a SonixOne scanner with and without a slab of pork belly placed on top of the tumors. The pork belly acted as an additional source of attenuation and transmission loss. QUS parameters, specifically effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were calculated using calibration spectra from both an external reference phantom and the Ti bead. Results: For ESD estimation, the 95% confidence interval between measurements with and without the pork belly layer was (6.0,27.4) using the in situ bead and (114, 135.1) with the external reference phantom. For EAC estimation, the 95% confidence interval were (-8.1, 0.5) for the bead and (-41.5, -32.2) for the phantom. These results indicate that the in situ bead method shows reduced bias in QUS estimates due to intervening tissue losses. Conclusions: The use of an in situ Ti bead as a radiological marker not only serves its traditional role but also effectively acts as a calibration target for QUS methods. This approach accounts for attenuation and transmission losses in tissue, resulting in more accurate QUS estimates and offering a promising method for enhanced disease state classification in clinical settings.

Transfer learning of pre-treatment quantitative ultrasound multi-parametric images for the prediction of breast cancer response to neoadjuvant chemotherapy.

Locally advanced breast cancer (LABC) is a severe type of cancer with a poor prognosis, despite advancements in therapy. As the disease is often inoperable, current guidelines suggest upfront aggressive neoadjuvant chemotherapy (NAC). Complete pathological response to chemotherapy is linked to improved survival, but conventional clinical assessments like physical exams, mammography, and imaging are limited in detecting early response. Early detection of tissue response can improve complete pathological response and patient survival while reducing exposure to ineffective and potentially harmful treatments. A rapid, cost-effective modality without the need for exogenous contrast agents would be valuable for evaluating neoadjuvant therapy response. Conventional ultrasound provides information about tissue echogenicity, but image comparisons are difficult due to instrument-dependent settings and imaging parameters. Quantitative ultrasound (QUS) overcomes this by using normalized power spectra to calculate quantitative metrics. This study used a novel transfer learning-based approach to predict LABC response to neoadjuvant chemotherapy using QUS imaging at pre-treatment. Using data from 174 patients, QUS parametric images of breast tumors with margins were generated. The ground truth response to therapy for each patient was based on standard clinical and pathological criteria. The Residual Network (ResNet) deep learning architecture was used to extract features from the parametric QUS maps. This was followed by SelectKBest and Synthetic Minority Oversampling (SMOTE) techniques for feature selection and data balancing, respectively. The Support Vector Machine (SVM) algorithm was employed to classify patients into two distinct categories: nonresponders (NR) and responders (RR). Evaluation results on an unseen test set demonstrate that the transfer learning-based approach using spectral slope parametric maps had the best performance in the identification of nonresponders with precision, recall, F1-score, and balanced accuracy of 100, 71, 83, and 86%, respectively. The transfer learning-based approach has many advantages over conventional deep learning methods since it reduces the need for large image datasets for training and shortens the training time. The results of this study demonstrate the potential of transfer learning in predicting LABC response to neoadjuvant chemotherapy before the start of treatment using quantitative ultrasound imaging. Prediction of NAC response before treatment can aid clinicians in customizing ineffectual treatment regimens for individual patients.

Noninvasive Evaluation of Breast Tumor Response to Combined Ultrasound-Stimulated Microbubbles and Hyperthermia Therapy Using Quantitative Ultrasound-Based Texture Analysis Method.

OBJECTIVES: Quantitative ultrasound (QUS) is a noninvasive imaging technique that can be used for assessing response to anticancer treatment. In the present study, tumor cell death response to the ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) treatment was monitored in vivo using QUS. METHODS: Human breast cancer cell lines (MDA-MB-231) were grown in mice and were treated with HT (10, 30, 50, and 60 minutes) alone, or in combination with USMB. Treatment effects were examined using QUS with a center frequency of 25 MHz (bandwidth range: 16 to 32 MHz). Backscattered radiofrequency (RF) data were acquired from tumors subjected to treatment. Ultrasound parameters such as average acoustic concentration (AAC) and average scatterer diameter (ASD), were estimated 24 hours prior and posttreatment. Additionally, texture features: contrast (CON), correlation (COR), energy (ENE), and homogeneity (HOM) were extracted from QUS parametric maps. All estimated parameters were compared with histopathological findings. RESULTS: The findings of our study demonstrated a significant increase in QUS parameters in both treatment conditions: HT alone (starting from 30 minutes of heat exposure) and combined treatment of HT plus USMB finally reaching a maximum at 50 minutes of heat exposure. Increase in AAC for 50 minutes HT alone and USMB +50 minutes was found to be 5.19 ± 0.417% and 5.91 ± 1.11%, respectively, compared to the control group with AAC value of 1.00 ± 0.44%. Furthermore, between the treatment groups, ΔASD-ENE values for USMB +30 minutes HT significantly reduced, depicting 0.00062 ± 0.00096% compared to 30 minutes HT only group, showing 0.0058 ± 0.0013%. Further, results obtained from the histological analysis indicated greater cell death and reduced nucleus size in both HT alone and HT combined with USMB. CONCLUSION: The texture-based QUS parameters indicated a correlation with microstructural changes obtained from histological data. This work demonstrated the use of QUS to detect HT treatment effects in breast cancer tumors in vivo.

A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype.

The purpose of this study was to investigate the performances of the tumor response prediction prior to neoadjuvant chemotherapy based on quantitative ultrasound, tumour core-margin, texture derivative analyses, and molecular parameters in a large cohort of patients (n = 208) with locally advanced and earlier-stage breast cancer and combined them to best determine tumour responses with machine learning approach. Two multi-features response prediction algorithms using a k-nearest neighbour and support vector machine were developed with leave-one-out and hold-out cross-validation methods to evaluate the performance of the response prediction models. In a leave-one-out approach, the quantitative ultrasound-texture analysis based model attained good classification performance with 80% of accuracy and AUC of 0.83. Including molecular subtype in the model improved the performance to 83% of accuracy and 0.87 of AUC. Due to limited number of samples in the training process, a model developed with a hold-out approach exhibited a slightly higher bias error in classification performance. The most relevant features selected in predicting the response groups are core-to-margin, texture-derivative, and molecular subtype. These results imply that that baseline tumour-margin, texture derivative analysis methods combined with molecular subtype can potentially be used for the prediction of ultimate treatment response in patients prior to neoadjuvant chemotherapy.

Locoregional Ablative Radiation Therapy for Patients With Breast Cancer Unsuitable for Surgical Resection.

PURPOSE: Patients with breast cancer who are unsuitable for surgical resection are typically managed with palliative systemic therapy alone. We report outcomes of 5-fraction ablative radiation therapy for nonresected breast cancers. METHODS AND MATERIALS: This is a retrospective analysis of an institutional registry of patients with breast cancer who were unsuitable for resection and underwent 35 to 40 Gy/5 fractions to the primary breast tumor or regional lymph nodes from 2014 to 2021. Primary outcomes were cumulative incidence of local failure and grade ≥3 toxicity (Common Terminology Criteria for Adverse Events, version 5.0). RESULTS: We reviewed 57 patients who received 61 treatment courses (median age of 81 years; range, 38-99). Unresectable tumor (10%), patient refusal (18%), medical inoperability (35%), and metastatic disease (37%) were the causes of not having surgery. Five patients (8%) had previously undergone adjuvant locoregional radiation therapy. Fifty-four percent (n = 33/61) of treatment courses targeted the breast only, 31% (n = 19/61) both the breast and lymph nodes, and 15% (n = 9/61) the lymph nodes only. Sixty-seven percent (n = 35/52) of the courses that targeted the breast were delivered with partial breast irradiation and 33% (n = 17/52) with whole breast radiation therapy (median dose of 25 Gy in 5 fractions) ± simultaneous integrated boost to the primary tumor. Most primary tumors (65%, n = 34/52) and target lymph nodes (61%, n = 17/28) were treated with a dose of 35 Gy in 5 fractions. Most treatments (52%) were delivered with intensity modulated radiation therapy (IMRT). Radiation therapy was delivered daily (20%), every other day (18%), twice weekly (36%), or weekly (26%). The 2-year cumulative incidence of local failure was 11.4% and grade≥3 toxicity was 15.1%. The grade ≥3 toxicity was 6.5% for IMRT treatments, versus 7.7% for non-IMRT treatments targeting partial breast or lymph nodes (hazard ratio, 1.13, P = .92), versus 38.9% for non-IMRT treatments targeting the entire breast (hazard ratio, 6.91, P = .023). All grade ≥3 toxicity cases were radiation dermatitis. No cases of brachial plexopathy were observed. CONCLUSIONS: Thirty-five to 40 Gy in 5 fractions is a safe and effective breast stereotactic body radiation therapy (SBRT) regimen and may be an attractive option for patients who are not surgical candidates. Highly conformal techniques (ie, IMRT or partial breast irradiation) were associated with a reduced risk of toxicity and should be the preferred treatment approaches.

Predicting head and neck cancer treatment outcomes with pre-treatment quantitative ultrasound texture features and optimising machine learning classifiers with texture-of-texture features.

Aim: Cancer treatments with radiation present a challenging physical toll for patients, which can be justified by the potential reduction in cancerous tissue with treatment. However, there remain patients for whom treatments do not yield desired outcomes. Radiomics involves using biomedical images to determine imaging features which, when used in tandem with retrospective treatment outcomes, can train machine learning (ML) classifiers to create predictive models. In this study we investigated whether pre-treatment imaging features from index lymph node (LN) quantitative ultrasound (QUS) scans parametric maps of head & neck (H&N) cancer patients can provide predictive information about treatment outcomes. Methods: 72 H&N cancer patients with bulky metastatic LN involvement were recruited for study. Involved bulky neck nodes were scanned with ultrasound prior to the start of treatment for each patient. QUS parametric maps and related radiomics texture-based features were determined and used to train two ML classifiers (support vector machines (SVM) and k-nearest neighbour (k-NN)) for predictive modeling using retrospectively labelled binary treatment outcomes, as determined clinically 3-months after completion of treatment. Additionally, novel higher-order texture-of-texture (TOT) features were incorporated and evaluated in regards to improved predictive model performance. Results: It was found that a 7-feature multivariable model of QUS texture features using a support vector machine (SVM) classifier demonstrated 81% sensitivity, 76% specificity, 79% accuracy, 86% precision and an area under the curve (AUC) of 0.82 in separating responding from non-responding patients. All performance metrics improved after implementation of TOT features to 85% sensitivity, 80% specificity, 83% accuracy, 89% precision and AUC of 0.85. Similar trends were found with k-NN classifier. Conclusion: Binary H&N cancer treatment outcomes can be predicted with QUS texture features acquired from index LNs. Prediction efficacy improved by implementing TOT features following methodology outlined in this work.

Quantitative Ultrasound for Evaluation of Tumour Response to Ultrasound-Microbubbles and Hyperthermia.

Objectives: Prior study has demonstrated the implementation of quantitative ultrasound (QUS) for determining the therapy response in breast tumour patients. Several QUS parameters quantified from the tumour region showed a significant correlation with the patient's clinical and pathological response. In this study, we aim to identify if there exists such a link between QUS parameters and changes in tumour morphology due to combined ultrasound-stimulated microbubbles (USMB) and hyperthermia (HT) using the breast xenograft model (MDA-MB-231). Method: Tumours grown in the hind leg of severe combined immuno-deficient mice were treated with permutations of USMB and HT. Ultrasound radiofrequency data were collected using a 25 MHz array transducer, from breast tumour-bearing mice prior and post-24-hour treatment. Result: Our result demonstrated an increase in the QUS parameters the mid-band fit and spectral 0-MHz intercept with an increase in HT duration combined with USMB which was found to be reflective of tissue structural changes and cell death detected using haematoxylin and eosin and terminal deoxynucleotidyl transferase dUTP nick end labelling stain. A significant decrease in QUS spectral parameters was observed at an HT duration of 60 minutes, which is possibly due to loss of nuclei by the majority of cells as confirmed using histology analysis. Morphological alterations within the tumour might have contributed to the decrease in backscatter parameters. Conclusion: The work here uses the QUS technique to assess the efficacy of cancer therapy and demonstrates that the changes in ultrasound backscatters mirrored changes in tissue morphology.

Radiation combined with ultrasound and microbubbles: A potential novel strategy for cancer treatment.

Cancer is one of the leading causes of death worldwide. Several emerging technologies are helping to battle cancer. Cancer therapies have been effective at killing cancer cells, but a large portion of patients still die to this disease every year. As such, more aggressive treatments of primary cancers are employed and have been shown to be capable of saving a greater number of lives. Recent research advances the field of cancer therapy by employing the use of physical methods to alter tumor biology. It uses microbubbles to enhance radiation effect by damaging tumor vasculature followed by tumor cell death. The technique can specifically target tumor volumes by conforming ultrasound fields capable of microbubbles stimulation and localizing it to avoid vascular damage in surrounding tissues. Thus, this new application of ultrasound-stimulated microbubbles (USMB) can be utilized as a novel approach to cancer therapy by inducing vascular disruption resulting in tumor cell death. Using USMB alongside radiation has showed to augment the anti-vascular effect of radiation, resulting in enhanced tumor response. Recent work with nanobubbles has shown vascular permeation into intracellular space, extending the use of this new treatment method to potentially further improve the therapeutic effect of the ultrasound-based therapy. The significant enhancement of localized tumor cell kill means that radiation-based treatments can be made more potent with lower doses of radiation. This technique can manifest a greater impact on radiation oncology practice by increasing treatment effectiveness significantly while reducing normal tissue toxicity. This review article summarizes the past and recent advances in USMB enhancement of radiation treatments. The review mainly focuses on preclinical findings but also highlights some clinical findings that use USMB as a therapeutic modality in cancer therapy.

Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancer.

Preclinical studies have demonstrated focused ultrasound (FUS) stimulated microbubble (MB) rupture leads to the activation of acid sphingomyelinase-ceramide pathway in the endothelial cells. When radiotherapy (RT) is delivered concurrently with FUS-MB, apoptotic pathway leads to increased cell death resulting in potent radiosensitization. Here we report the first human trial of using magnetic resonance imaging (MRI) guided FUS-MB treatment in the treatment of breast malignancies. In the phase 1 prospective interventional study, patients with breast cancer were treated with fractionated RT (5 or 10 fractions) to the disease involving breast or chest wall. FUS-MB treatment was delivered before 1st and 5th fractions of RT (within 1 h). Eight patients with 9 tumours were treated. All 7 evaluable patients with at least 3 months follow-up treated for 8 tumours had a complete response in the treated site. The maximum acute toxicity observed was grade 2 dermatitis in 1 site, and grade 1 in 8 treated sites, at one month post RT, which recovered at 3 months. No RT-related late effect or FUS-MB related toxicity was noted. This study demonstrated safety of combined FUS-MB and RT treatment. Promising response rates suggest potential strong radiosensitization effects of the investigational modality.Trial registration: clinicaltrials.gov, identifier NCT04431674.

Ultrasound-stimulated microbubbles enhancement of fractionated radiation for tumor treatment.

BACKGROUND: Radiation therapy (XRT) causes numerous biological changes in tumor microenvironment. Radiation vascular response, due to endothelial disruption, can influence treatment outcomes in a dose-dependent manner. Ultrasound-stimulated microbubbles (USMB) have also been demonstrated to create a vascular response in the tumor microenvironment and enhance tumor response when used in combination with XRT. Single doses of 8-10 Gy are known to induce activation of acid sphingomyelinase (ASMase)-induced ceramide production, causing vascular damage. Destruction of vasculature results in endothelial apoptosis followed by tumor cell death. The effect of tumor response is known to be synergistic by 10-fold higher cell kill observed when USMB is combined with radiation. METHODS: In this study, we used an USMB approach in combination with conventional low dose fractionated radiation to enhance endothelial cell responses to XRT in human PC3 prostate cancer xenograft model. Mice were divided into untreated, USMB therapy, fractionated XRT, and combined USMB therapy followed by XRT (USMB + XRT) groups. USMB therapy was delivered twice per week in the USMB-alone and combined USMB + XRT treatment groups over four weeks. Radiation treatments were delivered in fractions of 2 Gy/day (total 40 Gy in 20 fractions, BED10 = 48 Gy) in the XRT-alone and combined USMB + XRT groups. The treatment outcome was evaluated using histopathology, power Doppler, and immunohistochemistry assays. RESULTS: Tumor growth assessment showed that sizes of tumors increased in the control and the single treatment groups over a treatment period of four weeks, but significantly decreased with the combined treatments of USMB + XRT. Immunohistochemical analysis indicated a statistically significant vascular disruption in mice that received treatment involving a full 4-week schedule of combined (USMB + XRT) treatments. A statistically significant increase in vascular disruption was demonstrated through CD68 and trichrome fibrosis staining. Changes in local perfusion assessed using high-frequency power Doppler imaging demonstrated attenuated blood flow in the combined group. DISCUSSION AND CONCLUSIONS: This work demonstrates the efficacy of using USMB as a radiation sensitizer in a mouse model of human PC3 tumor xenograft. This radiation treatment enhancement modality has the advantage of targeting tumor vasculature with ultrasound stimulation that can be implemented prior to radiation treatment.

Ultrasound-stimulated microbubbles enhanced vascular disruption in fractionated radiotherapy-treated tumours via ASMase activation.

Recent studies have indicated that radiotherapy affects tumour vasculature as well as tumour cells. The use of ultrasound-stimulated microbubbles (USMB) can potentially enhance the effects of radiotherapy through the activation of the acid sphingomyelinase [ASMase or sphingomyelin phosphodiesterase 1 (SMPD1)]-ceramide pathway. ASMase knockout (ASMase-/-) and wild-type (WT) mice bearing fibrosarcoma (MCA/129 tumour line) were treated with 10 Gy or 20 Gy in five fractions alongside or independently of USMB treatments. The results indicated that tumour responses to fractionated radiotherapy (fXRT) were enhanced when fXRT was coupled with USMB as part of the treatment regimen. Sphingosine-1-phosphate (S1P)-treated mice and ASMase-/- mice demonstrated radioresistance against fXRT alone, whereas only ASMase-/- mice showed radioresistance against fXRT treatment alone and when combined with USMB. Results indicated that in WT and S1P-treated cohorts, the use of USMB with fXRT enhanced the tumour response compared to use of USMB or fXRT alone. Although in WT and S1P-treated cohorts, there was enhanced vascular disruption, ASMase-/- cohorts demonstrated no significant vascular disruption, indicating the importance of ASMase in facilitating vascular changes in response to fXRT and USMB treatment.

Enhanced full-inversion-based ultrasound elastography for evaluating tumor response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

PURPOSE: An enhanced ultrasound elastography technique is proposed for early assessment of locally advanced breast cancer (LABC) response to neoadjuvant chemotherapy (NAC). METHODS: The proposed elastography technique inputs ultrasound radiofrequency data obtained through tissue quasi-static stimulation and adapts a strain refinement algorithm formulated based on fundamental principles of continuum mechanics, coupled with an iterative inverse finite element method to reconstruct the breast Young's modulus (E) images. The technique was explored for therapy response assessment using data acquired from 25 LABC patients before and at weeks 1, 2, and 4 after the NAC initiation (100 scans). The E ratio of tumor to the surrounding tissue was calculated at different scans and compared to the baseline for each patient. Patients' response to NAC was determined many months later using standard clinical and histopathological criteria. RESULTS: Reconstructed E ratio changes obtained as early as one week after the NAC onset demonstrate very good separation between the two cohorts of responders and non-responders to NAC. Statistically significant differences were observed in the E ratio changes between the two patient cohorts at weeks 1 to 4 after treatment (p-value < 0.001; statistical power greater than 97%). A significant difference in axial strain ratio changes was observed only at week 4 (p-value = 0.01; statistical power = 76%). No significant difference was observed in tumor size changes at weeks 1, 2 or 4. CONCLUSION: The proposed elastography technique demonstrates a high potential for chemotherapy response monitoring in LABC patients and superior performance compared to strain imaging.

Focused Ultrasound and Ultrasound Stimulated Microbubbles in Radiotherapy Enhancement for Cancer Treatment.

Radiation therapy (RT) has been the standard of care for treating a multitude of cancer types. However, ionizing radiation has adverse short and long-term side effects which have resulted in treatment complications for decades. Thus, advances in enhancing the effects of RT have been the primary focus of research in radiation oncology. To avoid the usage of high radiation doses, treatment modalities such as high-intensity focused ultrasound can be implemented to reduce the radiation doses required to destroy cancer cells. In the past few years, the use of focused ultrasound (FUS) has demonstrated immense success in a number of applications as it capitalizes on spatial specificity. It allows ultrasound energy to be delivered to a targeted focal area without harming the surrounding tissue. FUS combined with RT has specifically demonstrated experimental evidence in its application resulting in enhanced cell death and tumor cure. Ultrasound-stimulated microbubbles have recently proved to be a novel way of enhancing RT as a radioenhancing agent on its own, or as a delivery vector for radiosensitizing agents such as oxygen. In this mini-review article, we discuss the bio-effects of FUS and RT in various preclinical models and highlight the applicability of this combined therapy in clinical settings.