Diffusion-weighted imaging reflects pathological therapeutic response and relapse in breast cancer

Update on DWI for Breast Cancer Diagnosis and Treatment Monitoring

DWI is a noncontrast MRI technique that measures the diffusion of water molecules within biologic tissue. DWI is increasingly incorporated into routine breast MRI examinations. Currently, the main applications of DWI are breast cancer detection and characterization, prognostication, and prediction of treatment response to neoadjuvant chemotherapy. In addition, DWI is promising as a noncontrast MRI alternative for breast cancer screening. Problems with suboptimal resolution and image quality have restricted the mainstream use of DWI for breast imaging, but these shortcomings are being addressed through several technologic advancements. In this review, we present an up-to-date assessment of the use of DWI for breast cancer imaging, including a summary of the clinical literature and recommendations for future use.

Design of Dual-Targeted pH-Sensitive Hybrid Polymer Micelles for Breast Cancer Treatment: Three Birds with One Stone

Breast cancer has a high prevalence in the world and creates a substantial socio-economic impact. Polymer micelles used as nano-sized polymer therapeutics have shown great advantages in treating breast cancer. Here, we aim to develop a dual-targeted pH-sensitive hybrid polymer (HPPF) micelles for improving the stability, controlled-release ability and targeting ability of the breast cancer treatment options. The HPPF micelles were constructed using the hyaluronic acid modified polyhistidine (HA-PHis) and folic acid modified Plannick (PF127-FA), which were characterized via ¹H NMR. The optimized mixing ratio (HA-PHis:PF127-FA) was 8:2 according to the change of particle size and zeta potential. The stability of HPPF micelles were enhanced with the higher zeta potential and lower critical micelle concentration compared with HA-PHis and PF127-FA. The drug release percents significantly increased from 45% to 90% with the decrease in pH, which illustrated that HPPF micelles were pH-sensitive owing to the protonation of PHis. The cytotoxicity, in vitro cellular uptake and in vivo fluorescence imaging experiments showed that HPPF micelles had the highest targeting ability utilizing FA and HA, compared with HA-PHis and PF127-FA. Thus, this study constructs an innovative nano-scaled drug delivery system, which provides a new strategy for the treatment of breast cancer.

Assessment of intravoxel incoherent motion MR imaging for differential diagnosis of breast lesions and evaluation of response: a systematic review

Background

The current study aimed to assess the performance for quantitative differentiation and evaluation of response in categorized observations from intravoxel incoherent motion analyses of patients based on breast tumors. To assess the presence of heterogeneity, the Cochran's Q tests for heterogeneity with a significance level of P < 0.1 and I2 statistic with values > 75% were used. A random-effects meta-analysis model was used to estimate pooled sensitivity and specificity. The standardized mean difference (SMD) and 95% confidence intervals of the true diffusivity (D), pseudo-diffusivity (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) were calculated, and publication bias was evaluated using the Begg's and Egger's tests and also funnel plot. Data were analyzed by STATA v 16 (StataCorp, College Station).

Results

The pooled D value demonstrated good measurement performance showed a sensitivity 86%, specificity 86%, and AUC 0.91 (SMD − 1.50, P < 0.001) in the differential diagnosis of breast lesions, which was comparable to that of the ADC that showed a sensitivity of 76%, specificity 79%, and AUC 0.85 (SMD 1.34, P = 0.01), then by the f it showed a sensitivity 80%, specificity 76%, and AUC 0.85 (SMD 0.89, P = 0.001), and D* showed a sensitivity 84%, specificity 59%, and AUC 0.71 (SMD − 0.30, P = 0.20).

Conclusion

The estimated sensitivity and specificity in the current meta-analysis were acceptable. So, this approach can be used as a suitable method in the differentiation and evaluation response of breast tumors.

Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods

Background

The apparent diffusion coefficient (ADC) value using histogram analysis is helpful to predict responses to neoadjuvant chemotherapy (NAC) in breast cancer. However, the measurement method has not reached a consensus. This study was to assess the diagnostic performance of the ADC histogram analysis at predicting patient response prior to NAC in breast cancer patients using different region of interest (ROI) selection methods.

Methods

A total of 75 patients who underwent diffusion weighted imaging (DWI) prior to NAC were retrospectively enrolled from February 2017 to December 2019. Images were measured using small 2-dimensional (2D) ROI, large 2D ROI, and volume ROI methods. The measurement time and ROI size were recorded. Histopathologic responses were acquired using the Miller-Payne grading system after surgery. The inter- and intra-observer repeatability was analyzed and the ADC histogram values from the three ROI methods were compared. The efficacy of each method at predicting patient response prior to NAC was assessed using the area under the receiver operating characteristic curve (AUC) for the whole study population and subgroups according to molecular subtype.

Results

Among the 75 enrolled patients, 26 (34.67%) were responsive to NAC therapy. The ADC histogram values were significantly different among the three ROI methods (P≤0.038). Inter- and intra-observer repeatability of the large 2D ROI method and the volume ROI method was generally greater than that observed with the 2D ROI method. The 10% ADC value of the large 2D ROI method showed the greatest AUC (0.701) in the whole study population and in the luminal subgroup (AUC 0.804). The volume ROI method required significantly more time than the other two ROI methods (P<0.001).

Conclusions

The small 2D ROI method is not appropriate for predicting response prior to NAC in breast cancer patients due to the poor repeatability. When choosing the ROI method and the histogram parameters for predicting response prior to NAC in breast cancer patients using ADC-derived histogram analysis, 10% of the large 2D ROI method is recommended, especially in luminal A subtype patients.

Factors affecting the value of diffusion-weighted imaging for identifying breast cancer patients with pathological complete response on neoadjuvant systemic therapy: a systematic review

This review aims to identify factors causing heterogeneity in breast DWI-MRI and their impact on its value for identifying breast cancer patients with pathological complete response (pCR) on neoadjuvant systemic therapy (NST). A search was performed on PubMed until April 2020 for studies analyzing DWI for identifying breast cancer patients with pCR on NST. Technical and clinical study aspects were extracted and assessed for variability. Twenty studies representing 1455 patients/lesions were included. The studies differed with respect to study population, treatment type, DWI acquisition technique, post-processing (e.g., mono-exponential/intravoxel incoherent motion/stretched exponential modeling), and timing of follow-up studies. For the acquisition and generation of ADC-maps, various b-value combinations were used. Approaches for drawing regions of interest on longitudinal MRIs were highly variable. Biological variability due to various molecular subtypes was usually not taken into account. Moreover, definitions of pCR varied. The individual areas under the curve for the studies range from 0.50 to 0.92. However, overlapping ranges of mean/median ADC-values at pre- and/or during and/or post-NST were found for the pCR and non-pCR groups between studies. The technical, clinical, and epidemiological heterogeneity may be causal for the observed variability in the ability of DWI to predict pCR accurately. This makes implementation of DWI for pCR prediction and evaluation based on one absolute ADC threshold for all breast cancer types undesirable. Multidisciplinary consensus and appropriate clinical study design, taking biological and therapeutic variation into account, is required for obtaining standardized, reliable, and reproducible DWI measurements for pCR/non-pCR identification.

Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning

This study aimed to investigate the predictive efficacy of positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) for the pathological response of advanced breast cancer to neoadjuvant chemotherapy (NAC). The breast PET/MRI image deep learning model was introduced and compared with the conventional methods. PET/CT and MRI parameters were evaluated before and after the first NAC cycle in patients with advanced breast cancer [n = 56; all women; median age, 49 (range 26–66) years]. The maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained with the corresponding baseline values (SUV0, MTV0, and TLG0, respectively) and interim PET images (SUV1, MTV1, and TLG1, respectively). Mean apparent diffusion coefficients were obtained from baseline and interim diffusion MR images (ADC0 and ADC1, respectively). The differences between the baseline and interim parameters were measured (ΔSUV, ΔMTV, ΔTLG, and ΔADC). Subgroup analysis was performed for the HER2-negative and triple-negative groups. Datasets for convolutional neural network (CNN), assigned as training (80%) and test datasets (20%), were cropped from the baseline (PET0, MRI0) and interim (PET1, MRI1) images. Histopathologic responses were assessed using the Miller and Payne system, after three cycles of chemotherapy. Receiver operating characteristic curve analysis was used to assess the performance of the differentiating responders and non-responders. There were six responders (11%) and 50 non-responders (89%). The area under the curve (AUC) was the highest for ΔSUV at 0.805 (95% CI 0.677–0.899). The AUC was the highest for ΔSUV at 0.879 (95% CI 0.722–0.965) for the HER2-negative subtype. AUC improved following CNN application (SUV0:PET0 = 0.652:0.886, SUV1:PET1 = 0.687:0.980, and ADC1:MRI1 = 0.537:0.701), except for ADC0 (ADC0:MRI0 = 0.703:0.602). PET/MRI image deep learning model can predict pathological responses to NAC in patients with advanced breast cancer.

Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI

BACKGROUND

The clinicopathological classification of breast cancer is proposed according to therapeutic purposes. It is simplified and can be conducted easily in clinical practice, and this subtyping undoubtedly contributes to the treatment selection of breast cancer. This study aims to investigate the feasibility of using a Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI for predicting the clinicopathological subtypes of breast cancer.

METHODS

Patients who underwent breast magnetic resonance imaging were confirmed by retrieving data from our institutional picture archiving and communication system (PACS) between March 2013 and September 2017. Five clinicopathological subtypes were determined based on the status of ER, PR, HER2 and Ki-67 from the immunohistochemical test. The radiomic features of diffusion-weighted imaging were derived from the volume of interest (VOI) of each tumour. Fisher discriminant analysis was performed for clinicopathological subtyping by using a backward selection method. To evaluate the diagnostic performance of the radiomic features, ROC analyses were performed to differentiate between immunohistochemical biomarker-positive and -negative groups.

RESULTS

A total of 84 radiomic features of four statistical methods were included after preprocessing. The overall accuracy for predicting the clinicopathological subtypes was 96.4% by Fisher discriminant analysis, and the weighted accuracy was 96.6%. For predicting diverse clinicopathological subtypes, the prediction accuracies ranged from 92 to 100%. According to the cross-validation, the overall accuracy of the model was 82.1%, and the accuracies of the model for predicting the luminal A, luminal B_HER2-, luminal B_HER2+, HER2 positive and triple negative subtypes were 79, 77, 88, 92 and 73%, respectively. According to the ROC analysis, the radiomic features had excellent performance in differentiating between different statuses of ER, PR, HER2 and Ki-67.

CONCLUSIONS

The Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI is a reliable method for the prediction of clinicopathological breast cancer subtypes.

Diffusion MRI of the breast: Current status and future directions

Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.

Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy

In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR), some achieve a partial response, and some do not respond at all or even progress. Accurate prediction of treatment response has the potential to improve patient care by improving prognostication, enabling de-escalation of toxic treatment that has little benefit, facilitating upfront use of novel targeted therapies, and avoiding delays to surgery. Visual inspection of a patient's tumor on multiparametric MRI is insufficient to predict that patient's response to NAC. However, machine learning and deep learning approaches using a mix of qualitative and quantitative MRI features have recently been applied to predict treatment response early in the course of or even before the start of NAC. This is a novel field but the data published so far has shown promising results. We provide an overview of the machine learning and deep learning models developed to date, as well as discuss some of the challenges to clinical implementation.

Diffusion-Weighted Magnetic Resonance Imaging of Patients with Breast Cancer Following Neoadjuvant Chemotherapy Provides Early Prediction of Pathological Response - A Prospective Study

The purpose of this study was to evaluate the capacity of diffusion-weighted magnetic resonance imaging (DW-MRI) for early prediction of pathological response in breast cancer patients undergoing neoadjuvant chemotherapy (NCT). This prospective unicentric study evaluated 62 patients who underwent NCT. MRI was performed prior to the start of treatment (MR1), after the first NCT cycle (MR2), and upon completion of NCT (MR3). Pathological response was used as the gold-standard. Patients’ median age was 45.5 years and the median tumor size was 40 mm. Twenty-four (38.7%) tumors presented complete pathological response (pCR). The percent increase in apparent diffusion coefficient (ADC) value between MR1 and MR2 was higher in the pCR group (p < 0.001). When the minimum increase in ADC between MR1 and MR2 was set at 25%, sensitivity was 83%, specificity was 84%, positive predictive value was 77%, negative predictive value was 89%, and accuracy was 84% for an early prediction of pCR to NCT. Meanwhile, there were no significant changes in major tumor dimensions between MR1 and MR2. In conclusion, an increase in ADC after the first cycle of NCT correlates well with pCR after the chemotherapy in our cohort, precedes reduction in tumor size on conventional MRI, and may therefore be used as an early predictor of treatment response.

Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role

Diffusion-weighted imaging (DWI) of the breast is a MRI sequence that shows several advantages when compared to the dynamic contrast-enhanced sequence: it does not need intravenous contrast, it is relatively quick and easy to implement (artifacts notwithstanding). In this review, the current applications of DWI for lesion characterization and prognosis as well as for response evaluation are analyzed from the point of view of the necessary steps to become a useful surrogate of underlying biological processes (tissue architecture and cellularity): from the proof of concept, to the proof of mechanism, the proof of principle and finally the proof of effectiveness. Future applications of DWI in screening, DWI modeling and radiomics are also discussed.

Can Multi-Parametric MR Based Approach Improve the Predictive Value of Pathological and Clinical Therapeutic Response in Breast Cancer Patients?

The potential of total choline (tCho), apparent diffusion coefficient (ADC) and tumor volume, both individually and in combination of all these three parameters (multi-parametric approach), was evaluated in predicting both pathological and clinical responses in 42 patients with locally advanced breast cancer (LABC) enrolled for neoadjuvant chemotherapy (NACT). Patients were sequentially examined by conventional MRI; diffusion weighted imaging and in vivo proton MR spectroscopy at 4 time points (pre-therapy, after I, II, and III NACT) at 1.5 T. Miller Payne grading system was used for pathological assessment of response. Of the 42 patients, 24 were pathological responders (pR) while 18 were pathological non-responders (pNR). Clinical response determination classified 26 patients as responders (cR) while 16 as non-responders (cNR). tCho and ADC showed significant changes after I NACT, however, MR measured tumor volume showed reduction only after II NACT both in pR and cR. After III NACT, the sensitivity to detect responders was highest for MR volume (83.3% for pR and 96.2% for cR) while the specificity was highest for ADC (76.5% for pR and 100% for cR). Combination of all three parameters exhibited lower sensitivity (66.7%) than MR volume for pR prediction, however, a moderate improvement was seen in specificity (58.8%). For the prediction of clinical response, multi-parametric approach showed 84.6% sensitivity with 100% specificity compared to MR volume (sensitivity 96.2%; specificity 80%). Kappa statistics demonstrated substantial agreement of clinical response with MR volume (k = 0.78) and with multi-parametric approach (k = 0.80) while moderate agreement was seen for tCho (k = 0.48) and ADC (k = 0.46). The values of k for tCho, MR volume and ADC were 0.31, 0.38, and 0.18 indicating fair, moderate, and slight agreement, respectively with pathological response. Moderate agreement (k = 0.44) was observed between clinical and pathological responses. Our study demonstrated that both tCho and ADC are strong predictors of assessment of early pathological and clinical responses. Multi-parametric approach yielded 100% specificity in predicting clinical response. Following III NACT, MR volume emerged as highly suitable predictor for both clinical and pathological assessments. PCA demonstrated separate clusters of pR vs. pNR and cR vs. cNR at post-therapy while with some overlap at pre-therapy.

Diffusion-weighted imaging in monitoring the pathological response to neoadjuvant chemotherapy in patients with breast cancer: a meta-analysis

Background

Diffusion-weighted imaging (DWI) is suggested as an non-invasive and non-radioactive imaging modality in the identification of pathological complete response (pCR) in breast cancer patients receiving neoadjuvant chemotherapy (NACT). A growing number of trials have been investigating in this aspect and some studies found a superior performance of DWI compared with conventional imaging techniques. However, the efficiency of DWI is still in dispute. This meta-analysis aims at evaluating the accuracy of DWI in the detection of pCR to NACT in patients with breast cancer.

Methods

Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were drawn to estimate the diagnostic effect of DWI to NACT. Summary receiver operating characteristic curve (SROC), the area under the SROC curve (AUC), and Youden index (*Q) were also calculated. The possible sources of heterogeneity among the included studies were explored using single-factor meta-regression analyses. Publication bias and quality assessment were assessed using Deek’s funnel plot and QUADAS-2 form respectively.

Results

Twenty studies incorporated 1490 participants were enrolled in our analysis. Pooled estimates revealed a sensitivity of 0.89 (95% CI, 0.86–0.91), a specificity of 0.72 (95% CI, 0.68–0.75), and a DOR of 27.00 (95% CI, 15.60–46.73). The AUC of SROC curve and *Q index were 0.9088 and 0.8408, respectively. The results of meta-regression analyses showed that pCR rate, time duration of study population, and study design were not the sources of heterogeneity.

Conclusion

A relatively high sensitivity and specificity of DWI in diagnosing pCP for patients with breast cancer underwent NACT treatment was found in our meta-analysis. This finding indicated that the use of DWI might provide an accurate and precise assessment of pCR to NACT.

Pre-operative assessment of residual disease in locally advanced breast cancer patients: A sequential study by quantitative diffusion weighted MRI as a function of therapy

PURPOSE

The potential of diffusion weighted imaging (DWI) in assessing pathologic response and surgical margins in locally advanced breast cancer patients (n=38) undergoing neoadjuvant chemotherapy was investigated.

METHODS

DWI was performed at pre-therapy (Tp0), after I (Tp1) and III (Tp3) NACT at 1.5T. Apparent diffusion coefficient (ADC) of whole tumor (ADC_WT), solid tumor (ADC_ST), intra-tumoral necrosis (ADC_Nec) was determined. Further, ADC of 6 consecutive shells (5mm thickness each) including tumor margin to outside tumor margins (OM1 to OM5) was calculated and the data analyzed to define surgical margins.

RESULTS

Of 38 patients, 6 were pathological complete responders (pCR), 19 partial responders (pPR) and 13 were non-responders (pNR). Significant increase was observed in ADC_ST and ADC_WT in pCR and pPR following therapy. Pre-therapy ADC was significantly lower in pCR compared to pPR and pNR indicating the heterogeneous nature of tumor which may affect drug perfusion and consequently the response. ADC of outside margins (OM1, OM2, and OM3) was significantly different among pCR, pPR and pNR at Tp3 which may serve as response predictive parameter. Further, at Tp3, ADC of outside margins (OM1, OM2, and OM3) was significantly lower compared to that seen at Tp0 in pCR, indicating the presence of residual disease in these shells.

CONCLUSION

Pre-surgery information may serve as a guide to define cancer free margins and the extent of residual disease which may be useful in planning breast conservation surgery.

Diffusion-Weighted Imaging for Predicting and Monitoring Primary Central Nervous System Lymphoma Treatment Response

BACKGROUND AND PURPOSE

Whether ADC value predicts the therapy response and outcomes of primary central system lymphoma remains controversial. This study assessed the minimum ADC correlated with treatment response in patients with primary central nervous system lymphoma undergoing methotrexate-based chemotherapy.

MATERIALS AND METHODS

Thirty-five patients with primary central nervous system lymphoma underwent conventional MR imaging and DWI before chemotherapy and after 1 and 5 cycles of chemotherapy. Treatment response was determined according to the International PCNSL Collaborative Group criteria and was classified as a complete response, partial response, or progressive disease. Pretreatment minimum ADC, minimum ADC after 1 cycle, minimum ADC after 5 cycles, and change in minimum ADC were compared among the different response groups. The Pearson correlation test was calculated between these ADC parameters and tumor response.

RESULTS

The pretreatment minimum ADC of the progressive disease group was lower than that of the complete response and partial response groups, but there was no significant difference among them. The minimum ADC after 1 cycle and minimum ADC after 5 cycles were statistically significantly higher than the pretreatment minimum ADC. A comparison among groups showed that minimum ADC after 1 cycle, minimum ADC after 5 cycles, minimum ADC change, and the percentage of minimum ADC change were all significantly different among the 3 groups. A significant positive correlation was observed between the percentage of minimum ADC after 1 cycle of chemotherapy and the size reduction percentage after 5 cycles of chemotherapy. The minimum ADC change and the percentage of minimum ADC change performed better in the differentiation of the final treatment response, specifically in complete response and partial response from progressive disease.

CONCLUSIONS

The minimum ADC after 1 cycle and minimum ADC changes were better correlated with the treatment response than the pretreatment minimum ADC. Minimum ADC after early therapy may potentially to be used to predict and monitor the response of primary central nervous system lymphoma to chemotherapy.

Role of the Intravoxel Incoherent Motion Diffusion Weighted Imaging in the Pre-treatment Prediction and Early Response Monitoring to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer

The aim of this study was to explore whether intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) can probe pre-treatment differences or monitor early response in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC). Thirty-six patients with locally advanced breast cancer were imaged using multiple-b DWI with 12 b values ranging from 0 to 1000  s/mm(2) at the baseline, and 28 patients were repeatedly scanned after the second cycle of NAC. Subjects were divided into pathologic complete response (pCR) and nonpathologic complete response (non-pCR) groups according to the surgical pathologic specimen. Parameters (D, D*, f, maximum diameter [MD] and volume [V]) before and after 2 cycles of NAC and their corresponding change (Δparameter) between pCR and non-pCR groups were compared using the Student t test or nonparametric test. The diagnostic performance of different parameters was judged by the receiver-operating characteristic curve analysis. Before NAC, the f value of pCR group was significantly higher than that of non-pCR (32.40% vs 24.40%, P = 0.048). At the end of the second cycle of NAC, the D value was significantly higher and the f value was significantly lower in pCR than that in non-pCR (P = 0.001; P = 0.015, respectively), whereas the D* value and V of the pCR group was slightly lower than that of the non-pCR group (P = 0.507; P = 0.676, respectively). ΔD was higher in pCR (-0.45 × 10(-3)  mm(2)/s) than that in non-pCR (-0.07 × 10(-3)  mm(2)/s) after 2 cycles of NAC (P < 0.001). Δf value in the pCR group was significantly higher than that in the non-pCR group (17.30% vs 5.30%, P = 0.001). There was no significant difference in ΔD* between the pCR and non-pCR group (P = 0.456). The prediction performance of ΔD value was the highest (AUC [area under the curve] = 0.924, 95% CI [95% confidence interval] = 0.759-0.990). When the optimal cut-off was set at -0.163 × 10(-3)  mm(2)/s, the values for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were up to 100% (95% CI = 66.4-100), 73.7% (95% CI = 48.8-90.9), 64.3% (95% CI = 35.6-86.0), and 100% (95% CI = 73.2-99.3), respectively. IVIM-derived parameters, especially the D and f value, showed potential value in the pre-treatment prediction and early response monitoring to NAC in locally advanced breast cancer. ΔD value had the best prediction performance for pathologic response after NAC.

Predicting the Response of Breast Cancer to Neoadjuvant Therapy Using a Mechanically Coupled Reaction-Diffusion Model

Although there are considerable data on the use of mathematical modeling to describe tumor growth and response to therapy, previous approaches are often not of the form that can be easily applied to clinical data to generate testable predictions in individual patients. Thus, there is a clear need to develop and apply clinically relevant oncologic models that are amenable to available patient data and yet retain the most salient features of response prediction. In this study we show how a biomechanical model of tumor growth can be initialized and constrained by serial patient-specific magnetic resonance imaging data, obtained at two time points early in the course of therapy (before initiation and following one cycle of therapy), to predict the response for individual patients with breast cancer undergoing neoadjuvant therapy. Using our mechanics coupled modeling approach, we are able to predict, after the first cycle of therapy, breast cancer patients that would eventually achieve a complete pathologic response and those who would not, with receiver operating characteristic area under the curve (AUC) of 0.87, sensitivity of 92%, and specificity of 84%. Our approach significantly outperformed the AUCs achieved by standard (i.e., not mechanically coupled) reaction-diffusion predictive modeling (0.75), simple analysis of the tumor cellularity estimated from imaging data (0.73), and the Response Evaluation Criteria in Solid Tumors (0.71). Thus, we show the potential for mathematical model prediction for use as a prognostic indicator of response to therapy. The work indicates the considerable promise of image-driven biophysical modeling for predictive frameworks within therapeutic applications.

Integrated PET/MRI for whole-body staging of patients with primary cervical cancer: preliminary results

PURPOSE

To assess the diagnostic value of integrated PET/MRI for whole-body staging of cervical cancer patients, as well as to investigate a potential association between PET/MRI derived functional parameters and prognostic factors of cervical cancer.

METHODS

The present study was approved by the local institutional review board. Twenty-seven patients with histopathologically confirmed cervical cancer were prospectively enrolled in our study. All patients underwent a whole-body PET/MRI examination after written informed consent was obtained. Two radiologists separately evaluated the PET/MRI data sets regarding the determination of local tumor extent of primary cervical cancer lesions, as well as detection of nodal and distant metastases. Furthermore, SUV and ADC values of primary tumor lesions were analyzed and correlated with dedicated prognostic factors of cervical cancer. Results based on histopathology and cross-sectional imaging follow-up served as the reference standard.

RESULTS

PET/MRI enabled the detection of all 27 primary tumor lesions of the uterine cervix and allowed for the correct determination of the T-stage in 23 (85 %) out of the 27 patients. Furthermore, the calculated sensitivity, specificity and diagnostic accuracy for the detection of nodal positive patients (n = 11) were 91 %, 94 % and 93 %, respectively. PET/MRI correctly identified regional metastatic disease (N1-stage) in 8/10 (80 %) patients and non-regional lymph node metastases in 5/5 (100 %) patients. In addition, quantitative analysis of PET and MRI derived functional parameters (SUV; ADC values) revealed a significant correlation with pathological grade and tumor size (p < 0.05).

CONCLUSIONS

The present study demonstrates the high potential of integrated PET/MRI for the assessment of primary tumor and the detection of lymph node metastases in patients with cervical cancer. Providing additional prognostic information, PET/MRI may serve as a valuable diagnostic tool for cervical cancer patients in a pretreatment setting.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Evaluation of Diffusion-Weighted Magnetic Resonance Imaging for Follow-up and Treatment Response Assessment of Lymphoma: Results of an 18F-FDG-PET/CT–Controlled Prospective Study in 64 Patients

Purpose: To determine the value of diffusion-weighted MRI (DWI-MRI) for treatment response assessment in 2-[18F]fluoro-2-deoxy-D-glucose (FDG)–avid lymphoma.

Experimental Design: Patients with FDG-avid Hodgkin (HL) or non-Hodgkin lymphoma (NHL) at pretherapeutic 18F-FDG-PET/CT, who had also undergone pretherapeutic whole-body DWI-MRI, were included in this prospective study. Depending on the histologic lymphoma subtype, patients received different systemic treatment regimens, and follow-up DWI-MRI and 18F-FDG-PET/CT were performed at one or more time points, depending on the clinical course. For each follow-up DWI-MRI, region-based rates of agreement, and rates of agreement in terms of treatment response (complete remission, partial remission, stable disease, or progressive disease), relative to the corresponding 18F-FDG-PET/CT, were calculated.

Results: Sixty-four patients were included: 10 with HL, 22 with aggressive NHL, and 32 with indolent NHL. The overall region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.4%. For the 51 interim examinations (performed after 1–3 therapy cycles), region-based agreement of DWI-MRI with 18F-FDG-PET/CT was 99.2%, and for the 48 end-of-treatment examinations, agreement was 99.8%. No significant differences, in terms of region-based agreement between DWI-MRI and 18F-FDG-PET/CT, were observed between the three lymphoma groups (HL, aggressive NHL, indolent NHL; P = 0.25), or between interim and end-of-treatment examinations (P = 0.21). With regard to treatment response assessment, DWI-MRI agreed with 18F-FDG-PET/CT in 99 of 102 follow-up examinations (97.1%), with a κ value of 0.94 (P &lt; 0.0001).

Conclusions: In patients with FDG-avid lymphoma, DWI-MRI may be a feasible alternative to 18F-FDG-PET/CT for follow-up and treatment response assessment. Clin Cancer Res; 21(11); 2506–13. ©2015 AACR.

Diffusion MRI and novel texture analysis in osteosarcoma xenotransplants predicts response to anti-checkpoint therapy

Combinations of targeted drugs have been employed to treat sarcomas, however, response rates have not improved notably, therefore emphasizing the need for novel treatments. In addition, imaging approaches to assess therapeutic response is lacking, as currently measurable indices, such as volume and/or diameter, do not accurately correlate with changes in tumor biology. In this study, quantitative and profound analyses of magnetic resonance imaging (MRI) were developed to evaluate these as imaging biomarkers for MK1775 and Gem in an osteosarcoma xenotransplant model at early time-points following treatment. Notably, we showed that Gem and Gem+MK1775 groups had significantly inhibited tumor growth by day 4, which was presaged by elevations in mean ADC by 24 hours post treatment. Significant differences were also observed at later time points for the Gem+MK1775 combination and MK1775 therapy. ADC distribution and entropy (randomness of ADC values) were also elevated by 24 hours following therapy. Immunohistochemistry demonstrated that these treatment-related increases in ADC correlated with apoptosis and observed cell condensations (dense- and exploded bodies). These findings underline the role of ADC as a quantitative imaging biomarker for therapy-induced response and show promising clinical relevance in the sarcoma patient population.