Geometric distortions in clinical MRI sequences for radiotherapy: insights gained from a multicenter investigation.

BACKGROUND: As magnetic resonance imaging (MRI) becomes increasingly integrated into radiotherapy (RT) for enhanced treatment planning and adaptation, the inherent geometric distortion in acquired MR images pose a potential challenge to treatment accuracy. This study aimed to evaluate the geometric distortion levels in the clinical MRI protocols used across Danish RT centers and discuss influence of specific sequence parameters. Based on the variety in geometric performance across centers, we assess if harmonization of MRI sequences is a relevant measure. MATERIALS AND METHODS: Nine centers participated with 12 MRI scanners and MRI-Linacs (MRL). Using a travelling phantom approach, a reference MRI sequence was used to assess variation in baseline distortion level between scanners. The phantom was also scanned with local clinical MRI sequences for brain, head/neck (H/N), abdomen, and pelvis. The influence of echo time, receiver bandwidth, image weighting, and 2D/3D acquisition was investigated. RESULTS: We found a large variation in geometric accuracy across 93 clinical sequences examined, exceeding the baseline variation found between MRI scanners (σ = 0.22 mm), except for abdominal sequences where the variation was lower. Brain and abdominal sequences showed lowest distortion levels ([0.22, 2.26] mm), and a large variation in performance was found for H/N and pelvic sequences ([0.19, 4.07] mm). Post hoc analyses revealed that distortion levels decreased with increasing bandwidth and a less clear increase in distortion levels with increasing echo time. 3D MRI sequences had lower distortion levels than 2D (median of 1.10 and 2.10 mm, respectively), and in DWI sequences, the echo-planar imaging read-out resulted in highest distortion levels. CONCLUSION: There is a large variation in the geometric distortion levels of clinical MRI sequences across Danish RT centers, and between anatomical sites. The large variation observed makes harmonization of MRI sequences across institutions and adoption of practices from well-performing anatomical sites, a relevant measure within RT.

Dose comparison of robustly optimized intensity modulated proton therapy (IMPT) vs IMRT and VMAT photon plans for testicular seminoma.

BACKGROUND: Patients with stage II seminoma have traditionally been treated with photons to the retroperitoneal and iliac space, which leads to a substantial dose bath to abdominal and pelvic organs at risk (OAR). As these patients are young and with excellent prognosis, reducing dose to OAR and thereby the risk of secondary cancer is of utmost importance. We compared IMPT to opposing IMRT fields and VMAT, assessing dose to OAR and both overall and organ-specific secondary cancer risk. MATERIAL AND METHODS: A comparative treatment planning study was conducted on planning CT-scans from ten patients with stage II seminoma, treated with photons to a 'dog-leg' field with doses ranging from 20 to 25 Gy and a 10 Gy sequential boost to the metastatic lymph node(s). Photon plans were either 3-4 field IMRT (Eclipse) or 1-2 arc VMAT (Pinnacle). Proton plans used robust (5 mm; 3.5%) IMPT (Eclipse), multi field optimization with 3 posterior fields supplemented by 2 anterior fields at the level of the iliac vessels. Thirty plans were generated. Mean doses to OARs were compared for IMRT vs IMPT and VMAT vs IMPT. The risk of secondary cancer was calculated according to the model described by Schneider, using excess absolute risk (EAR, per 10,000 persons per year) for body outline, stomach, duodenum, pancreas, bowel, bladder and spinal cord. RESULTS: Mean doses to all OARs were significantly lower with IMPT except similar kidney (IMRT) and spinal cord (VMAT) doses. The relative EAR for body outline was 0.59 for IMPT/IMRT (p < .05) and 0.33 for IMPT/VMAT (p < .05). Organ specific secondary cancer risk was also lower for IMPT except for pancreas and duodenum. CONCLUSION: Proton therapy reduced radiation dose to OAR compared to both IMRT and VMAT plans, and potentially reduce the risk of secondary cancer both overall and for most OAR.

Coverage probability planning for simultaneously integrated boosts of inguinal lymph nodes in vulvar cancer.

BACKGROUND AND PURPOSE: Strategies for minimizing irradiation of organs at risk (OARs) from pathological inguinal lymph node (PILN) boosting are needed to minimize the risk of morbidity. Coverage probability (CovP) is a conformal planning strategy for simultaneously integrated boost (SIB). Our aim was to investigate if SIB of PILN using CovP can be delivered safely in vulvar cancer. MATERIALS AND METHODS: Ten consecutive patients treated with definitive radiotherapy (RT) including SIB of PILN and with daily cone beam CT (CBCT) were included. Dose prescription was 51.2/32 fx to the elective target and 64 Gy/32 fx to the gross disease at the vulva and to positive lymph nodes (LN). PILN were contoured on both planning CT and MRI (GTV-N) and combined to form ITV-N. Each PILN GTV-N was contoured on every third CBCT, in total 11 CBCT for each patient. OARs were subcutaneous tissue (SC), inguinal vessels, skin rim, bowel, and body contour. Three plans were created for every patient: A) Standard CT-based planning; PTV-N based on GTV-NCT with a 10 mm isotropic margin. B) CT and MRI-based planning with smaller margins: PTV-N based on ITV-N with a 5 mm isotropic margin. C) CovP. The total delivered dose to GTV-Ns was estimated by accumulating dose across all fractions based on GTV-Ns contoured on CBCT. RESULTS: Thirty-five PILNs were boosted. There was no significant difference in accumulated GTV-N D98% between the three plans. CovP delivered a higher mean dose to the GTV-N D50% and D2% (p < 0.001). The planned mean doses to the OARs were reduced when applying CovP. CONCLUSIONS: SIB of PILN in vulvar cancer based on CovP and a 5 mm PTV margin does not compromise target coverage during RT and reduces the dose to normal tissues in the groin.

Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer.

AIM: The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity. METHODS: Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis. RESULTS: Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r = - 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes. CONCLUSION: A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue.

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as 'chemo fog'. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

Treatment plan comparison of proton vs photon radiotherapy for lower-grade gliomas.

BACKGROUND AND PURPOSE: Patients with lower-grade gliomas are long-term survivors after radiotherapy and may benefit from the reduced dose to normal tissue achievable with proton therapy. Here, we aimed to quantify differences in dose to the uninvolved brain and contralateral hippocampus and compare the risk of radiation-induced secondary cancer for photon and proton plans for lower-grade glioma patients. MATERIALS AND METHODS: Twenty-three patients were included in this in-silico planning comparative study and had photon and proton plans calculated (50.4 Gy(RBE = 1.1), 28 Fx) applying similar dose constraints to the target and organs at risk. Automatically calculated photon plans were generated with a 3 mm margin from clinical target volume (CTV) to planning target volume. Manual proton plans were generated using robust optimisation on the CTV. Dose metrics of organs at risk were compared using population mean dose-volume histograms and Wilcoxon signed-rank test. Secondary cancer risk per 10,000 persons per year (PPY) was estimated using dose-volume data and a risk model for secondary cancer induction. RESULTS: CTV coverage (V95%>98%) was similar for the two treatment modalities. Mean dose (Dmean) to the uninvolved brain was significantly reduced from 21.5 Gy (median, IQR 17.1-24.4 Gy) with photons compared to 10.3 Gy(RBE) (8.1-13.9 Gy(RBE)) with protons. Dmean to the contralateral hippocampus was significantly reduced from 6.5 Gy (5.4-11.7 Gy) with photons to 1.5 Gy(RBE) (0.4-6.8 Gy(RBE)) with protons. The estimated secondary cancer risk was reduced from 6.7 PPY (median, range 3.3-10.4 PPY) with photons to 3.0 PPY (1.3-7.5 PPY) with protons. CONCLUSION: A significant reduction in mean dose to uninvolved brain and contralateral hippocampus was found with proton planning. The estimated secondary cancer risk was reduced with proton therapy.

A national study on the inter-observer variability in the delineation of organs at risk in the brain.

BACKGROUND: The Danish Neuro Oncology Group (DNOG) has established national consensus guidelines for the delineation of organs at risk (OAR) structures based on published literature. This study was conducted to finalise these guidelines and evaluate the inter-observer variability of the delineated OAR structures by expert observers. MATERIAL AND METHODS: The DNOG delineation guidelines were formed by participants from all Danish centres that treat brain tumours with radiotherapy. In a two-day workshop, guidelines were discussed and finalised based on a pilot study. Following this, the ten participants contoured the following OARs on T1-weighted gadolinium enhanced MRI from 13 patients with brain tumours: optic tracts, optic nerves, chiasm, spinal cord, brainstem, pituitary gland and hippocampus. The metrics used for comparison were the Dice similarity coefficient (Dice), mean surface distance (MSD) and others. RESULTS: A total of 968 contours were delineated across the 13 patients. On average eight (range six to nine) individual contour sets were made per patient. Good agreement was found across all structures with a median MSD below 1 mm for most structures, with the chiasm performing the best with a median MSD of 0.45 mm. The Dice was as expected highly volume dependent, the brainstem (the largest structure) had the highest Dice value with a median of 0.89 whereas smaller volumes such as the chiasm had a Dice of 0.71. CONCLUSION: Except for the caudal definition of the spinal cord, the variances observed in the contours of OARs in the brain were generally low and consistent. Surface mapping revealed sub-regions of higher variance for some organs. The data set is being prepared as a validation data set for auto-segmentation algorithms for use within the Danish Comprehensive Cancer Centre - Radiotherapy and potential collaborators.

Dosimetric impact of edema on inguinal lymph node boost in locally advanced vulvar cancer.

We aimed to evaluate the extent of groin edema and its dosimetric effect in boosted inguinal lymph nodes (LN) for vulvar cancer patients. The level of edema was determined in 10 patients treated with radical radiotherapy. A dosimetric evaluation of six LNs in the patient with the maximum level of edema was performed. The accumulated dose across CBCT fractions was acceptable for all six LNs (>94% of prescribed dose) even with the development of up to 13 mm of edema. The major contributor to fractional dose degradation was geographical displacement of the nodes. We suggest evaluation of edema on daily CBCT.

Phantom-based quality assurance for multicenter quantitative MRI in locally advanced cervical cancer.

BACKGROUND AND PURPOSE: A wide variation of MRI systems is a challenge in multicenter imaging biomarker studies as it adds variation in quantitative MRI values. The aim of this study was to design and test a quality assurance (QA) framework based on phantom measurements, for the quantitative MRI protocols of a multicenter imaging biomarker trial of locally advanced cervical cancer. MATERIALS AND METHODS: Fifteen institutes participated (five 1.5 T and ten 3 T scanners). Each institute optimized protocols for T2, diffusion-weighted imaging, T1, and dynamic contrast-enhanced (DCE-)MRI according to system possibilities, institutional preferences and study-specific constraints. Calibration phantoms with known values were used for validation. Benchmark protocols, similar on all systems, were used to investigate whether differences resulted from variations in institutional protocols or from system variations. Bias, repeatability (%RC), and reproducibility (%RDC) were determined. Ratios were used for T2 and T1 values. RESULTS: The institutional protocols showed a range in bias of 0.88-0.98 for T2 (median %RC = 1%; %RDC = 12%), -0.007 to 0.029 × 10-3 mm2/s for the apparent diffusion coefficient (median %RC = 3%; %RDC = 18%), and 0.39-1.29 for T1 (median %RC = 1%; %RDC = 33%). For DCE a nonlinear vendor-specific relation was observed between measured and true concentrations with magnitude data, whereas the relation was linear when phase data was used. CONCLUSION: We designed a QA framework for quantitative MRI protocols and demonstrated for a multicenter trial for cervical cancer that measurement of consistent T2 and apparent diffusion coefficient values is feasible despite protocol differences. For DCE-MRI and T1 mapping with the variable flip angle method, this was more challenging.

Influence of FAZA PET hypoxia and HPV-status for the outcome of head and neck squamous cell carcinoma (HNSCC) treated with radiotherapy: Long-term results from the DAHANCA 24 trial (NCT01017224).

PURPOSE: Hypoxic tumor volumes can be visualized with 18F-FAZA PET/CT. In head and neck squamous cell carcinoma (HNSCC), hypoxia is important for the clinical outcome after primary radiotherapy (RT). The outcome is furthermore heavily influenced by the HPV/p16-positivity of oropharyngeal tumors (OPCp16+ tumors). The study purposes were (1) to report on locoregional failures within five years after primary RT in a prospective cohort stratified by both HPV/p16-status and PET hypoxia and (2) to characterize the failure site and the spatial association to PET hypoxia. MATERIAL AND METHODS: From 2009 to 2011, 38 patients with non-metastatic SCC of the larynx, oro-, hypo- and nasopharynx completing primary RT were included in the prospective DAHANCA 24 trial (NCT01017224). Fifteen patients had OPCp16+ tumors. All were imaged with a static FAZA PET/CT prior to treatment. The hypoxia threshold was determined by a tumor-to-muscle ratio (TMR) of 1.6. Recurrences were documented histologically. Imaging of the recurrence was deformable fused with the pre-treatment FAZA PET/CT. The spatial information of recurrence- and hypoxic volumes were compared visually. RESULTS: Sixteen patients had more hypoxic tumors (high tracer uptake, TMR ≥1.6) before treatment (42%). With a median follow-up of 7.8 years, nine locoregional recurrences were observed, of which seven were in patients with high-uptake tumors (44% and 9%, respectively, HR 5.8 [1.2-28.2]). The risk of locoregional recurrence was highest among patients with more hypoxic, non-OPCp16+ tumors (57% [21-94%]), with a risk difference of 45% [4-86%], when comparing to less hypoxic, non-OPCp16+ tumors. Eight patients had sufficient imaging of the recurrence for co-registration with the FAZA PET/CT. Six had hypoxic primary tumors, and in two, the recurrence was overlapping the baseline hypoxic subvolume. CONCLUSION: HNSCC demonstrating a TMR ≥1.6 at baseline is significantly associated with treatment failure after primary RT. In addition to HPV/p16-status, FAZA PET/CT has potential for the selection of tumors requiring treatment intensification.

Cognitive impairment following radiation to hippocampus and other brain structures in adults with primary brain tumours.

BACKGROUND: Radiation therapy (RT) to the brain may result in cognitive impairment. The primary objective of the present study was to examine the relationship between RT dose to the hippocampus and learning and memory functions. Secondary objective was to examine relationships between doses to other brain structures and specific cognitive functions. METHODS: A cross-sectional analysis was undertaken in 78 primary brain tumour patients after RT. Cognitive function was assessed by neuropsychological tests. Test scores were standardized using normative data adjusted for age and level of education. Test-specific cognitive impairment was determined as a z-score ≤-1.5. Radiation dose to brain structures and test-specific cognitive impairment outcomes were fitted to a logistic regression model. RESULTS: High RT dose to the left hippocampus was associated with impaired verbal learning and memory (p = 0.04). RT dose to the left hippocampus, left temporal lobe, left frontal lobe and total frontal lobe were associated with verbal fluency impairment (p < 0.05) and doses to the thalamus and the left frontal lobe with impaired executive functioning (p ≤ 0.03). Finally, RT dose to the brain and thalamus were associated with impaired processing speed (p ≤ 0.05). CONCLUSION: The present study indicates that the hippocampus may be vulnerable to radiation and that high radiation doses to the left hippocampus may lead to significant verbal learning and memory impairment. High RT doses to the left hippocampus and other left side structures may result in impairments in verbal fluency, executive function, and processing speed. Validation of these findings are being undertaken in a prospective study.

Tumour subregion analysis of colorectal liver metastases using semi-automated clustering based on DCE-MRI: Comparison with histological subregions and impact on pharmacokinetic parameter analysis.

PURPOSE: To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted pharmacokinetic (PK) parameters between tumour subregions. MATERIALS AND METHODS: This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. RESULTS: Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between Ktrans and kep for viable and non-viable subregions (p < 0.001) and between whole lesions and viable subregions (p < 0.001). CONCLUSION: We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice.

Robust estimation of hemo-dynamic parameters in traditional DCE-MRI models.

PURPOSE: In dynamic contrast enhanced (DCE) MRI, separation of signal contributions from perfusion and leakage requires robust estimation of parameters in a pharmacokinetic model. We present and quantify the performance of a method to compute tissue hemodynamic parameters from DCE data using established pharmacokinetic models. METHODS: We propose a Bayesian scheme to obtain perfusion metrics from DCE MRI data. Initial performance is assessed through digital phantoms of the extended Tofts model (ETM) and the two-compartment exchange model (2CXM), comparing the Bayesian scheme to the standard Levenberg-Marquardt (LM) algorithm. Digital phantoms are also invoked to identify limitations in the pharmacokinetic models related to measurement conditions. Using computed maps of the extra vascular volume (ve) from 19 glioma patients, we analyze differences in the number of un-physiological high-intensity ve values for both ETM and 2CXM, using a one-tailed paired t-test assuming un-equal variance. RESULTS: The Bayesian parameter estimation scheme demonstrated superior performance over the LM technique in the digital phantom simulations. In addition, we identified limitations in parameter reliability in relation to scan duration for the 2CXM. DCE data for glioma and cervical cancer patients was analyzed with both algorithms and demonstrated improvement in image readability for the Bayesian method. The Bayesian method demonstrated significantly fewer non-physiological high-intensity ve values for the ETM (p<0.0001) and the 2CXM (p<0.0001). CONCLUSION: We have demonstrated substantial improvement of the perceptive quality of pharmacokinetic parameters from advanced compartment models using the Bayesian parameter estimation scheme as compared to the LM technique.

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF.

PURPOSE: This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. PROCEDURES: Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. RESULTS: When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. CONCLUSIONS: The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma.

BACKGROUND: The clinical target volume (CTV) in radiotherapy is routinely based on gadolinium contrast enhanced T1 weighted (T1w + Gd) and T2 weighted fluid attenuated inversion recovery (T2w FLAIR) magnetic resonance imaging (MRI) sequences which have been shown to over- or underestimate the microscopic tumor cell spread. Gliomas favor spread along the white matter fiber tracts. Tumor growth models incorporating the MRI diffusion tensors (DTI) allow to account more consistently for the glioma growth. The aim of the study was to investigate the potential of a DTI driven growth model to improve target definition in glioblastoma (GBM). MATERIAL AND METHODS: Eleven GBM patients were scanned using T1w, T2w FLAIR, T1w + Gd and DTI. The brain was segmented into white matter, gray matter and cerebrospinal fluid. The Fisher-Kolmogorov growth model was used assuming uniform proliferation and a difference in white and gray matter diffusion of a ratio of 10. The tensor directionality was tested using an anisotropy weighting parameter set to zero (γ0) and twenty (γ20). The volumetric comparison was performed using Hausdorff distance, Dice similarity coefficient (DSC) and surface area. RESULTS: The median of the standard CTV (CTVstandard) was 180 cm3. The median surface area of CTVstandard was 211 cm2. The median surface area of respective CTVγ0 and CTVγ20 significantly increased to 338 and 376 cm2, respectively. The Hausdorff distance was greater than zero and significantly increased for both CTVγ0 and CTVγ20 with respective median of 18.7 and 25.2 mm. The DSC for both CTVγ0 and CTVγ20 were significantly below one with respective median of 0.74 and 0.72, which means that 74 and 72% of CTVstandard were included in CTVγ0 and CTVγ20, respectively. CONCLUSIONS: DTI driven growth models result in CTVs with a significantly increased surface area, a significantly increased Hausdorff distance and decreased overlap between the standard and model derived volume.

Are complex DCE-MRI models supported by clinical data?

PURPOSE: To ascertain whether complex dynamic contrast enhanced (DCE) MRI tracer kinetic models are supported by data acquired in the clinic and to determine the consequences of limited contrast-to-noise. METHODS: Generically representative in silico and clinical (cervical cancer) DCE-MRI data were examined. Bayesian model selection evaluated support for four compartmental DCE-MRI models: the Tofts model (TM), Extended Tofts model, Compartmental Tissue Uptake model (CTUM), and Two-Compartment Exchange model. RESULTS: Complex DCE-MRI models were more sensitive to noise than simpler models with respect to both model selection and parameter estimation. Indeed, as contrast-to-noise decreased, complex DCE models became less probable and simpler models more probable. The less complex TM and CTUM were the optimal models for the DCE-MRI data acquired in the clinic. [In cervical tumors, Ktrans, Fp, and PS increased after radiotherapy (P = 0.004, 0.002, and 0.014, respectively)]. CONCLUSION: Caution is advised when considering application of complex DCE-MRI kinetic models to data acquired in the clinic. It follows that data-driven model selection is an important prerequisite to DCE-MRI analysis. Model selection is particularly important when high-order, multiparametric models are under consideration. (Parameters obtained from kinetic modeling of cervical cancer clinical DCE-MRI data showed significant changes at an early stage of radiotherapy.) Magn Reson Med 77:1329-1339, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Comparison of linear and nonlinear implementation of the compartmental tissue uptake model for dynamic contrast-enhanced MRI.

PURPOSE: Fitting tracer kinetic models using linear methods is much faster than using their nonlinear counterparts, although this comes often at the expense of reduced accuracy and precision. The aim of this study was to derive and compare the performance of the linear compartmental tissue uptake (CTU) model with its nonlinear version with respect to their percentage error and precision. THEORY AND METHODS: The linear and nonlinear CTU models were initially compared using simulations with varying noise and temporal sampling. Subsequently, the clinical applicability of the linear model was demonstrated on 14 patients with locally advanced cervical cancer examined with dynamic contrast-enhanced magnetic resonance imaging. RESULTS: Simulations revealed equal percentage error and precision when noise was within clinical achievable ranges (contrast-to-noise ratio >10). The linear method was significantly faster than the nonlinear method, with a minimum speedup of around 230 across all tested sampling rates. Clinical analysis revealed that parameters estimated using the linear and nonlinear CTU model were highly correlated (ρ ≥ 0.95). CONCLUSION: The linear CTU model is computationally more efficient and more stable against temporal downsampling, whereas the nonlinear method is more robust to variations in noise. The two methods may be used interchangeably within clinical achievable ranges of temporal sampling and noise. Magn Reson Med 77:2414-2423, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.