The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

Folate receptor α deficiency - Myelin-sensitive MRI as a reliable biomarker to monitor the efficacy and long-term outcome of a new therapeutic approach.

Cerebral folate transport deficiency, caused by a genetic defect in folate receptor α, is a devastating neurometabolic disorder that, if untreated, leads to epileptic encephalopathy, psychomotor decline and hypomyelination. Currently, there are limited data on effective dosage and duration of treatment, though early diagnosis and therapy with folinic acid appears critical. The aim of this long-term study was to identify new therapeutic approaches and novel biomarkers for assessing efficacy, focusing on myelin-sensitive MRI. Clinical, biochemical, structural and quantitative MRI parameters of seven patients with genetically confirmed folate receptor α deficiency were acquired over 13 years. Multimodal MRI approaches comprised MR-spectroscopy (MRS), magnetization transfer (MTI) and diffusion tensor imaging (DTI) sequences. Patients started oral treatment immediately following diagnosis or in an interval of up to 2.5 years. Escalation to intravenous and intrathecal administration was performed in the absence of effects. Five patients improved, one with a presymptomatic start of therapy remained symptom-free, and one with inconsistent treatment deteriorated. While CSF 5-methyltetrahydrofolate and MRS parameters normalized immediately after therapy initiation, myelin-sensitive MTI and DTI measures correlated with gradual clinical improvement and ongoing myelination under therapy. Early initiation of treatment at sufficient doses, considering early intrathecal applications, is critical for favorable outcome. The majority of patients showed clinical improvements that correlated best with MTI parameters, allowing individualized monitoring of myelination recovery. Presymptomatic therapy seems to ensure normal development and warrants newborn screening. Furthermore, the quantitative parameters of myelin-sensitive MRI for therapy assessments can now be used for hypomyelination disorders in general.

CSF and venous blood flow from childhood to adulthood studied by real-time phase-contrast MRI.

PURPOSE: In vivo measurements of CSF and venous flow using real-time phase-contrast (RT-PC) MRI facilitate new insights into the dynamics and physiology of both fluid systems. In clinical practice, however, use of RT-PC MRI is still limited. Because many forms of hydrocephalus manifest in infancy and childhood, it is a prerequisite to investigate normal flow parameters during this period to assess pathologies of CSF circulation. This study aims to establish reference values of CSF and venous flow in healthy subjects using RT-PC MRI and to determine their age dependency. METHODS: RT-PC MRI was performed in 44 healthy volunteers (20 females, age 5-40 years). CSF flow was quantified at the aqueduct (Aqd), cervical (C3) and lumbar (L3) spinal levels. Venous flow measurements comprised epidural veins, internal jugular veins and inferior vena cava. Parameters analyzed were peak velocity, net flow, pulsatility, and area of region of interest (ROI). STATISTICAL TESTS: linear regression, student's t-test and analysis of variance (ANOVA). RESULTS: In adults volunteers, no significant changes in flow parameters were observed. In contrast, pediatric subjects exhibited a significant age-dependent decrease of CSF net flow and pulsatility in Aqd, C3 and L3. Several venous flow parameters decreased significantly over age at C3 and changed more variably at L3. CONCLUSION: Flow parameters varies depending on anatomical location and age. We established changes of brain and spinal fluid dynamics over an age range from 5-40 years. The application of RT-PC MRI in clinical care may improve our understanding of CSF flow pathology in individual patients.

Advanced and amplified BOLD fluctuations in high-grade gliomas.

BACKGROUND: Glioma grade along with patient's age and general health are used for treatment planning and prognosis. PURPOSE: To characterize and quantify the spontaneous blood oxygen level-dependent (BOLD) fluctuations in gliomas using measures based on T2*-weighted signal time-series and to distinguish between high- and low-grade gliomas. STUDY TYPE: Retrospective. SUBJECTS: Twenty-one patients with high-grade and 13 patients with low-grade gliomas confirmed on histology were investigated. FIELD STRENGTH/SEQUENCE: Dynamic T2*-weighted (multislice single-shot echo-planar-imaging) magnetic resonance imaging (MRI) was performed on a 3T system with an 8-element receive-only head coil to measure the BOLD fluctuations. In addition, a dynamic T1 -weighted (3D fast field echo) dynamic contrast-enhanced (DCE) perfusion scan was performed. ASSESSMENT: Three BOLD measures were determined: the temporal shift (TS), amplitude of low frequency fluctuations (ALFF), and regional homogeneity (ReHo). DCE perfusion-based cerebral blood volume (CBV) and time-to-peak (TTP) maps were concurrently evaluated for comparison. STATISTICAL TESTS: An analysis-of-variance test was first used. When the test appeared significant, post-hoc analysis was performed using analysis-of-covariance with age as covariate. Logistic regression and receiver-operator characteristic curve analysis were also performed. RESULTS: TS was significantly advanced in high-grade gliomas compared to the contralateral cortex (P = 0.01) and low-grade gliomas (P = 0.009). In high-grade gliomas, ALFF and CBV were significantly higher than the contralateral cortex (P = 0.041 and P = 0.008, respectively) and low-grade gliomas (P = 0.036 and P = 0.01, respectively). ReHo and TTP did not show significant differences between high- and low-grade gliomas (P = 0.46 and P = 0.42, respectively). The area-under-curve was above 0.7 only for the TS, ALFF, and CBV measures. DATA CONCLUSION: Advanced and amplified hemodynamic fluctuations manifest in high-grade gliomas, but not in low-grade gliomas, and can be assessed using BOLD measures. Preliminary results showed that quantification of spontaneous fluctuations has potential for hemodynamic characterization of gliomas and distinguishing between high- and low-grade gliomas. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:1616-1625.

Differentiation of grade II/III and grade IV glioma by combining "T1 contrast-enhanced brain perfusion imaging" and susceptibility-weighted quantitative imaging.

PURPOSE: MRI is a useful method for discriminating low- and high-grade glioma using perfusion MRI and susceptibility-weighted imaging (SWI). The purpose of this study is to evaluate the usefulness of T1-perfusion MRI and SWI in discriminating among grade II, III, and IV gliomas. METHODS: T1-perfusion MRI was used to measure relative cerebral blood volume (rCBV) in 129 patients with glioma (70 grade IV, 33 grade III, and 26 grade II tumors). SWI was also used to measure the intratumoral susceptibility signal intensity (ITSS) scores for each tumor in these patients. rCBV and ITSS values were compared to seek differences between grade II vs. grade III, grade III vs. grade IV, and grade III+II vs. grade IV tumors. RESULTS: Significant differences in rCBV values of the three grades of the tumors were noted and pairwise comparisons showed significantly higher rCBV values in grade IV tumors as compared to grade III tumors, and similarly increased rCBV was seen in the grade III tumors as compared to grade II tumors (p < 0.001). Grade IV gliomas showed significantly higher ITSS scores on SWI as compared to grade III tumors (p < 0.001) whereas insignificant difference was seen on comparing ITSS scores of grade III with grade II tumors. Combining the rCBV and ITSS resulted in significant improvement in the discrimination of grade III from grade IV tumors. CONCLUSION: The combination of rCBV values derived from T1-perfusion MRI and SWI derived ITSS scores improves the diagnostic accuracy for discrimination of grade III from grade IV gliomas.

Susceptibility Weighted With Quantitative Phase Magnetic Resonance Imaging in Differentiation of Various Stages of Hemorrhage and Calcification in Female Pelvic Pathologies: A Preliminary Study.

BACKGROUND: The purposes of this study were to assess the value of phase for characterization of female pelvic lesions with hemorrhage in various stages and to differentiate them from calcified lesions at 3.0-T magnetic resonance imaging (MRI). METHODS: Forty-four female patients with hemorrhagic (n = 37) or calcified (n = 7) pelvic pathology underwent conventional MRI including susceptibility-weighted imaging with phase information. Hemorrhagic lesions were grouped into acute, subacute, and chronic, and calcified lesions were detected on the basis of conventional imaging findings. Phase quantification of these hemorrhagic and calcified lesions was performed. RESULTS: The phase values significantly differed (P < 0.001) among various stages of hemorrhage, as well as calcification (chronic hemorrhage, -65.09 ± 9.09 degrees; subacute hemorrhage, -11.41 ± 4.4 degrees; acute hemorrhage, -42.30 ± 5.20 degrees; and calcified lesions, 117.55 ± 12.93 degrees). CONCLUSIONS: Quantitative phase imaging has the potential to differentiate various stages of hemorrhagic and calcified pathologies. This may add value to the conventional MRI in improved characterization of these entities in female pelvic pathologies.

Role of Dynamic Contrast-Enhanced Perfusion Magnetic Resonance Imaging in Grading of Pediatric Brain Tumors on 3T.

BACKGROUND/AIMS: Perfusion magnetic resonance imaging (MRI) is useful for preoperative assessment of brain tumors. Dynamic susceptibility contrast perfusion MRI is commonly used for evaluation of brain tumors. Dynamic contrast-enhanced (DCE) MRI is an alternative method that has mainly been used in adult brain tumors. In this preliminary study, we report our initial experience with the DCE perfusion MRI in pediatric brain tumors. METHODS: Sixty-four newly diagnosed pediatric brain tumor patients underwent DCE perfusion MRI on a 3-T scanner. Hemodynamic and kinetic parametric maps were generated and the regions with the highest values were measured on each map. Statistical differences were sought to differentiate between low-grade tumors, high-grade tumors, and medulloblastomas. The perfusion metrics of common posterior fossa tumors were also compared. RESULTS: Relative corrected cerebral blood volume (rCBV) and fractional plasma volume measures differed significantly between high- and low-grade tumors (p < 0.05). High-grade tumors could be differentiated from low-grade tumors, with an rCBV cutoff value of 2.41 and 88.6% sensitivity and 65% specificity. There was no significant difference in Ktrans, Kep, Ve, or λtr between these 2 groups of tumors. rCBV, relative quantification of the cerebral blood flow, and permeability indices were found to be significantly different in various posterior fossa tumors, i.e., pilocytic astrocytoma, ependymoma, and medulloblastoma (p < 0.05). CONCLUSION: DCE-derived perfusion metrics are useful in differentiating high-grade tumors from low-grade ones and discriminating among various posterior fossa tumors in the pediatric age group.

Subcompartmentalization of extracellular extravascular space (EES) into permeability and leaky space with local arterial input function (AIF) results in improved discrimination between high- and low-grade glioma using dynamic contrast-enhanced (DCE) MRI.

PURPOSE: To modify the generalized tracer kinetic model (GTKM) by introducing an additional tissue uptake leakage compartment in extracellular extravascular space (LTKM). In addition, an implicit determination of voxel-wise local arterial input function (AIF) Cp (t) was performed to see whether these changes help in better discrimination between low- and high-grade glioma using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). MATERIALS AND METHODS: The modified model (LTKM) was explored and fitted to the concentration-time curve C(t) of each voxel, in which the local AIF Cp (t) could be estimated by a time invariant convolution approximation based on a separately measured global AIF Ca (t). A comparative study of tracer kinetic analysis was performed on 184 glioma patients using DCE-MRI data on 1.5T and 3T MRI systems. RESULTS: The LTKM analysis provided more accurate pharmacokinetic parameters as evidenced by their relative constancy with respect to the length of concentration-time curve used. In addition, LTKM with local AIF resulted in improved discrimination between low-grade and high-grade gliomas. CONCLUSION: LTKM with local AIF provides more accurate estimation of physiological parameters and improves discrimination between low-grade and high-grade gliomas as compared with GTKM.

Comparative evaluation of 3-dimensional pseudocontinuous arterial spin labeling with dynamic contrast-enhanced perfusion magnetic resonance imaging in grading of human glioma.

INTRODUCTION: The study was performed to compare dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) with 3-dimensional (3D) pseudocontinuous arterial spin labeling (PCASL) MRI in gliomas with an aim to see whether arterial spin labeling (ASL)-derived cerebral blood flow (CBF) values can be used as an alternative to DCE-MRI for its grading. MATERIALS AND METHODS: Sixty-four patients with glioma (37 male; mean age, 43 years; 38 high grade and 26 low grade) underwent 3D-PCASL and DCE-MRI. The DCE indices (relative cerebral blood volume, rCBV; relative CBF, rCBF; permeability, k and kep; and leakage, ve) and ASL (absolute and rCBF) values were quantified from the tumors. Student independent t test was used to compare ASL and DCE-MRI indices. Pearson correlation was used to see correlation between DCE- and ASL-derived CBF values in tumor and normal parenchyma. RESULTS: On Student t test, neither ASL-derived absolute CBF (P = 0.78) nor rCBF (P = 0.12) values were found to be significantly different in 2 groups, whereas DCE indices except ve were significantly higher in high-grade gliomas. Arterial spin labeling-derived rCBF values weakly correlated with DCE-derived rCBF values, whereas these did not show correlation in normal grey (P = 0.12, r = 0.2) and white (P = 0.26, r = 0.14) matter regions. CONCLUSIONS: Three-dimensional pseudocontinuous arterial spin labeling does not appear to be a reliable technique in the current form and may not be a suitable replacement for DCE in grading of glioma.

Modeling interaction of Glioma cells and CAR T-cells considering multiple CAR T-cells bindings.

Chimeric antigen receptor (CAR) T-cell based immunotherapy has shown its potential in treating blood cancers, and its application to solid tumors is currently being extensively investigated. For glioma brain tumors, various CAR T-cell targets include IL13Rα2, EGFRvIII, HER2, EphA2, GD2, B7-H3, and chlorotoxin. In this work, we are interested in developing a mathematical model of IL13Rα2 targeting CAR T-cells for treating glioma. We focus on extending the work of Kuznetsov et al. (1994) by considering binding of multiple CAR T-cells to a single glioma cell, and the dynamics of these multi-cellular conjugates. Our model more accurately describes experimentally observed CAR T-cell killing assay data than the models which do not consider multi-cellular conjugates. Moreover, we derive conditions in the CAR T-cell expansion rate that determines treatment success or failure. Finally, we show that our model captures distinct CAR T-cell killing dynamics from low to high antigen receptor densities in patient-derived brain tumor cells.

Discriminant analysis to classify glioma grading using dynamic contrast-enhanced MRI and immunohistochemical markers.

INTRODUCTION: The purpose of the present study was to look for the possible predictors which might discriminate between high- and low-grade gliomas by pooling dynamic contrast-enhanced (DCE)-perfusion derived indices and immunohistochemical markers. METHODS: DCE-MRI was performed in 76 patients with different grades of gliomas. Perfusion indices, i.e., relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), permeability (k (trans) and k (ep)), and leakage (v (e)) were quantified. MMP-9-, PRL-3-, HIF-1α-, and VEGF-expressing cells were quantified from the excised tumor tissues. Discriminant function analysis using these markers was used to identify discriminatory variables using a stepwise procedure. To look for correlations between immunohistochemical parameters and DCE metrics, Pearson's correlation coefficient was also used. RESULTS: A discriminant function for differentiating between high- and low-grade tumors was constructed using DCE-MRI-derived rCBV, k (ep), and v (e). The form of the functions estimated are "D (1) = 0.642 × rCBV + 0.591 × k (ep) - 1.501 × v (e) - 1.550" and "D (2) = 1.608 × rCBV + 3.033 × k (ep) + 5.508 × v (e) - 8.784" for low- and high-grade tumors, respectively. This function classified overall 92.1% of the cases correctly (89.1% high-grade tumors and 100% low-grade tumors). In addition, VEGF expression correlated with rCBV and rCBF, whereas MMP-9 expression correlated with k (ep). A significant positive correlation of HIF-1α with rCBV and VEGF expression was also found. CONCLUSION: DCE-MRI may be used to differentiate between high-grade and low-grade brain tumors non-invasively, which may be helpful in appropriate treatment planning and management of these patients. The correlation of its indices with immunohistochemical markers suggests that this imaging technique is useful in tissue characterization of gliomas.

Dynamic contrast-enhanced magnetic resonance imaging-derived kep as a potential biomarker of matrix metalloproteinase 9 expression in patients with glioblastoma multiforme: a pilot study.

OBJECTIVE: To look for the association of tissue matrix metalloproteinase 9 (MMP-9) expression with dynamic contrast-enhanced magnetic resonance imaging and to see whether these can prognosticate patients with glioblastoma multiforme (GBM). METHODS: Forty-seven patients with GBM underwent dynamic contrast-enhanced magnetic resonance imaging to look for association of its indices with tissue MMP-9 expression using Pearson correlation. Kaplan-Meier survival analysis was performed to study the survival pattern for low-, medium-, and high-tissue MMP-9 expression and kep values. RESULTS: Among perfusion indices, kep, k, and ve significantly correlated with MMP-9 expression. Matrix metalloproteinase 9 expression was found to be best estimated by kep using a quadratic model. The 1-year survival in low-, medium-, and high-tissue MMP-9 and kep groups were 59%, 45%, and 7%, and 59%, 33%, and 15%, respectively. CONCLUSION: The association of kep and MMP-9 expression with survival suggests that kep may be used as imaging biomarker of GBM progression and its prognostication.

Deep breathing couples CSF and venous flow dynamics.

Venous system pathologies have increasingly been linked to clinically relevant disorders of CSF circulation whereas the exact coupling mechanisms still remain unknown. In this work, flow dynamics of both systems were studied using real-time phase-contrast flow MRI in 16 healthy subjects during normal and forced breathing. Flow evaluations in the aqueduct, at cervical level C3 and lumbar level L3 for both the CSF and venous fluid systems reveal temporal modulations by forced respiration. During normal breathing cardiac-related flow modulations prevailed, while forced breathing shifted the dominant frequency of both CSF and venous flow spectra towards the respiratory component and prompted a correlation between CSF and venous flow in the large vessels. The average of flow magnitude of CSF was increased during forced breathing at all spinal and intracranial positions. Venous flow in the large vessels of the upper body decreased and in the lower body increased during forced breathing. Deep respiration couples interdependent venous and brain fluid flow-most likely mediated by intrathoracic and intraabdominal pressure changes. Further insights into the driving forces of CSF and venous circulation and their correlation will facilitate our understanding how the venous system links to intracranial pressure regulation and of related forms of hydrocephalus.

Utilizing Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Analyze Interstitial Fluid Flow and Transport in Glioblastoma and the Surrounding Parenchyma in Human Patients.

BACKGROUND: Glioblastoma (GBM) is the deadliest and most common brain tumor in adults, with poor survival and response to aggressive therapy. Limited access of drugs to tumor cells is one reason for such grim clinical outcomes. A driving force for therapeutic delivery is interstitial fluid flow (IFF), both within the tumor and in the surrounding brain parenchyma. However, convective and diffusive transport mechanisms are understudied. In this study, we examined the application of a novel image analysis method to measure fluid flow and diffusion in GBM patients. METHODS: Here, we applied an imaging methodology that had been previously tested and validated in vitro, in silico, and in preclinical models of disease to archival patient data from the Ivy Glioblastoma Atlas Project (GAP) dataset. The analysis required the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is readily available in the database. The analysis results, which consisted of IFF flow velocity and diffusion coefficients, were then compared to patient outcomes such as survival. RESULTS: We characterized IFF and diffusion patterns in patients. We found strong correlations between flow rates measured within tumors and in the surrounding parenchymal space, where we hypothesized that velocities would be higher. Analyzing overall magnitudes indicated a significant correlation with both age and survival in this patient cohort. Additionally, we found that neither tumor size nor resection significantly altered the velocity magnitude. Lastly, we mapped the flow pathways in patient tumors and found a variability in the degree of directionality that we hypothesize may lead to information concerning treatment, invasive spread, and progression in future studies. CONCLUSIONS: An analysis of standard DCE-MRI in patients with GBM offers more information regarding IFF and transport within and around the tumor, shows that IFF is still detected post-resection, and indicates that velocity magnitudes correlate with patient prognosis.

Repeatability of tumor perfusion kinetics from dynamic contrast-enhanced MRI in glioblastoma.

BACKGROUND: Dynamic contrast-enhanced MRI (DCE-MRI) parameters have been shown to be biomarkers for treatment response in glioblastoma (GBM). However, variations in analysis and measurement methodology complicate determination of biological changes measured via DCE. The aim of this study is to quantify DCE-MRI variations attributable to analysis methodology and image quality in GBM patients. METHODS: The Extended Tofts model (eTM) and Leaky Tracer Kinetic Model (LTKM), with manually and automatically segmented vascular input functions (VIFs), were used to calculate perfusion kinetic parameters from 29 GBM patients with double-baseline DCE-MRI data. DCE-MRI images were acquired 2-5 days apart with no change in treatment. Repeatability of kinetic parameters was quantified with Bland-Altman and percent repeatability coefficient (%RC) analysis. RESULTS: The perfusion parameter with the least RC was the plasma volume fraction (v p ), with a %RC of 53%. The extra-cellular extra-vascular volume fraction (v e ) %RC was 82% and 81%, for extended Tofts-Kety Model (eTM) and LTKM respectively. The %RC of the volume transfer rate constant (K trans ) was 72% for the eTM, and 82% for the LTKM, respectively. Using an automatic VIF resulted in smaller %RCs for all model parameters, as compared to manual VIF. CONCLUSIONS: As much as 72% change in K trans (eTM, autoVIF) can be attributable to non-biological changes in the 2-5 days between double-baseline imaging. Poor K trans repeatability may result from inferior temporal resolution and short image acquisition time. This variation suggests DCE-MRI repeatability studies should be performed institutionally, using an automatic VIF method and following quantitative imaging biomarkers alliance guidelines.

Synthetic Apparent Diffusion Coefficient for High b-Value Diffusion-Weighted MRI in Prostate.

PURPOSE: It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value increases the diagnostic power of prostate cancer. DWI with higher. RESULTS: No significant difference was observed between actual ADC and sADC for b-value increases the diagnostic power of prostate cancer. DWI with higher p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (Discussion/. CONCLUSION: Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher.

Towards integration of 64Cu-DOTA-trastuzumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2 + breast cancer.

While targeted therapies exist for human epidermal growth factor receptor 2 positive (HER2 +) breast cancer, HER2 + patients do not always respond to therapy. We present the results of utilizing a biophysical mathematical model to predict tumor response for two HER2 + breast cancer patients treated with the same therapeutic regimen but who achieved different treatment outcomes. Quantitative data from magnetic resonance imaging (MRI) and 64Cu-DOTA-trastuzumab positron emission tomography (PET) are used to estimate tumor density, perfusion, and distribution of HER2-targeted antibodies for each individual patient. MRI and PET data are collected prior to therapy, and follow-up MRI scans are acquired at a midpoint in therapy. Given these data types, we align the data sets to a common image space to enable model calibration. Once the model is parameterized with these data, we forecast treatment response with and without HER2-targeted therapy. By incorporating targeted therapy into the model, the resulting predictions are able to distinguish between the two different patient responses, increasing the difference in tumor volume change between the two patients by > 40%. This work provides a proof-of-concept strategy for processing and integrating PET and MRI modalities into a predictive, clinical-mathematical framework to provide patient-specific predictions of HER2 + treatment response.

Circulating tumor DNA as an early cancer detection tool.

Circulating tumor DNA holds substantial promise as an early detection biomarker, particularly for cancers that do not have currently accepted screening methodologies, such as ovarian, pancreatic, and gastric cancers. Many features intrinsic to ctDNA analysis may be leveraged to enhance its use as an early cancer detection biomarker: including ctDNA fragment lengths, DNA copy number variations, and associated patient phenotypic information. Furthermore, ctDNA testing may be synergistically used with other multi-omic biomarkers to enhance early detection. For instance, assays may incorporate early detection proteins (i.e., CA-125), epigenetic markers, circulating tumor RNA, nucleosomes, exosomes, and associated immune markers. Many companies are currently competing to develop a marketable early cancer detection test that leverages ctDNA. Although some hurdles (like early stage disease assay accuracy, high implementation costs, confounding from clonal hematopoiesis, and lack of clinical utility studies) need to be addressed before integration into healthcare, ctDNA assays hold substantial potential as an early cancer screening test.

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data.

Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of haematological cancers and is currently being investigated for solid tumours, including high-grade glioma brain tumours. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumours. In this work, we use a mathematical model of predator-prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor T-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, proliferation, exhaustion, and persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyser to parametrize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted when compared with higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumour growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumour characteristics including tumour growth rate and antigen level to maximize therapeutic benefit.

Change in Apparent Diffusion Coefficient Is Associated With Local Failure After Stereotactic Body Radiation Therapy for Non-Small Cell Lung Cancer: A Prospective Clinical Trial.

PURPOSE: Response assessment with computed tomography after stereotactic body radiation therapy (SBRT) for non-small cell lung cancer (NSCLC) is challenging because myriad anatomic changes can occur after treatment. Diffusion-weighted magnetic resonance imaging (MRI) may provide additional data to guide therapy response. The primary objective was to evaluate the effect of SBRT on the mean apparent diffusion coefficient (ADC). METHODS AND MATERIALS: This is a prospective clinical study of patients with NSCLC who received SBRT to the primary lung lesion. Patients underwent MRI scans before and at 1 month after completion of SBRT. MRI consisted of T1- and T2-weighted sequences, along with postcontrast, dynamic-contrast, and diffusion-weighted sequences with construction of ADC maps. Two blinded radiologists generated the ADC. SBRT was given over 5 fractions. RESULTS: A total of 13 patients were enrolled. Twelve patients were eligible for analysis. An average increase of 50% and 46% in mean single-plane ADC was observed after treatment by readers 1 and 2, respectively (P < .01, both reviewers). There was good interobserver agreement of single-plane ADC values between the 2 radiologists (Pearson correlation of 0.85 [baseline] and 0.89 [1-month post-SBRT], P < .001 for both). There was also a significant 18% increase in mean volumetric ADC on the 1-month scan (Wilcoxon P = .02). Two patients developed a local failure after SBRT, 1 at 6 months and the other at 34 months. Using a threshold of volumetric ADC increase of greater than 40%, 2 of 2 patients demonstrated local failure compared with 0 of 10 patients below this limit. CONCLUSIONS: A statistically significant increase in ADC was observed 1 month after treatment. An ADC increase of 40% at 1 month was associated with a higher rate of local failure. This pilot study provides impetus for studying ADC as a radiomic biomarker in patients receiving lung SBRT for NSCLC.