Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method.

ABSTRACT: Renal echo planar diffusion tensor imaging (DTI) has clinical potential but suffers from geometric distortion. We evaluated feasibility of reversed gradient distortion correction in 10 diabetic patients and 6 volunteers. Renal area, apparent diffusion coefficient, fractional anisotropy, and tensor eigenvalues were measured on uncorrected and distortion-corrected DTI. Corrected DTI correlated better than uncorrected DTI (r = 0.904 vs 0.840, P = 0.002) with reference anatomic T2-weighted imaging, with no significant difference in DTI metrics.

Automatic treatment planning for VMAT-based total body irradiation using Eclipse scripting.

The purpose of this work is to establish an automated approach for a multiple isocenter volumetric arc therapy (VMAT)-based TBI treatment planning approach. Five anonymized full-body CT imaging sets were used. A script was developed to automate and standardize the treatment planning process using the Varian Eclipse v15.6 Scripting API. The script generates two treatment plans: a head-first VMAT-based plan for upper body coverage using four isocenters and a total of eight full arcs; and a feet-first AP/PA plan with three isocenters that covers the lower extremities of the patient. PTV was the entire body cropped 5 mm from the patient surface and extended 3 mm into the lungs and kidneys. Two plans were generated for each case: one to a total dose of 1200 cGy in 8 fractions and a second one to a total dose of 1320 cGy in 8 fractions. Plans were calculated using the AAA algorithm and 6 MV photon energy. One plan was created and delivered to an anthropomorphic phantom containing 12 OSLDs for in-vivo dose verification. For the plans prescribed to 1200 cGy total dose the following dosimetric results were achieved: median PTV V100% = 94.5%; median PTV D98% = 89.9%; median lungs Dmean = 763 cGy; median left kidney Dmean = 1058 cGy; and median right kidney Dmean = 1051 cGy. For the plans prescribed to 1320 cGy total dose the following dosimetric results were achieved: median PTV V100% = 95.0%; median PTV D98% = 88.7%; median lungs Dmean = 798 cGy; median left kidney Dmean = 1059 cGy; and median right kidney Dmean = 1064 cGy. Maximum dose objective was met for all cases. The dose deviation between the treatment planning dose and the dose measured by the OSLDs was within ±4%. In summary, we have demonstrated that scripting can produce high-quality plans based on predefined dose objectives and can decrease planning time by automatic target and optimization contours generation, plan creation, field and isocenter placement, and optimization objectives setup.

Full automation of spinal stereotactic radiosurgery and stereotactic body radiation therapy treatment planning using Varian Eclipse scripting.

The purpose of this feasibility study is to develop a fully automated procedure capable of generating treatment plans with multiple fractionation schemes to improve speed, robustness, and standardization of plan quality. A fully automated script was implemented for spinal stereotactic radiosurgery/stereotactic body radiation therapy (SRS/SBRT) plan generation using Eclipse v15.6 API. The script interface allows multiple dose/fractionation plan requests, planning target volume (PTV) expansions, as well as information regarding distance/overlap between spinal cord and targets to drive decision-making. For each requested plan, the script creates the course, plans, field arrangements, and automatically optimizes and calculates dose. The script was retrospectively applied to ten computed tomography (CT) scans of previous cervical, thoracic, and lumbar spine SBRT patients. Three plans were generated for each patient - simultaneous integrated boost (SIB) 1800/1600 cGy to gross tumor volume (GTV)/PTV in one fraction; SIB 2700/2100 cGy to GTV/PTV in three fractions; and 3000 cGy to PTV in five fractions. Plan complexity and deliverability patient-specific quality assurance (QA) was performed using ArcCHECK with an Exradin A16 chamber inserted. Dose objectives were met for all organs at risk (OARs) for each treatment plan. Median target coverage was GTV V100% = 87.3%, clinical target volume (CTV) V100% = 95.7% and PTV V100% = 88.0% for single fraction plans; GTV V100% = 95.6, CTV V100% = 99.6% and PTV V100% = 97.2% for three fraction plans; and GTV V100% = 99.6%, CTV V100% = 99.1% and PTV V100% = 97.2% for five fraction plans. All plans (n = 30) passed patient-specific QA (>90%) at 2%/2 mm global gamma. A16 chamber dose measured at isocenter agreed with planned dose within 3% for all cases. Automatic planning for spine SRS/SBRT through scripting increases efficiency, standardizes plan quality and approach, and provides a tool for target coverage comparison of different fractionation schemes without the need for additional resources.

Geometric distortion correction in prostate diffusion-weighted MRI and its effect on quantitative apparent diffusion coefficient analysis.

PURPOSE: To evaluate the effect of correction for B0 inhomogeneity-induced geometric distortion in echo-planar diffusion-weighted imaging on quantitative apparent diffusion coefficient (ADC) analysis in multiparametric prostate MRI. METHODS: Geometric distortion correction was performed in echo-planar diffusion-weighted images (b = 0, 50, 400, 800 s/mm2 ) of 28 patients, using two b0 scans with opposing phase-encoding polarities. Histology-matched tumor and healthy tissue volumes of interest delineated on T2 -weighted images were mapped to the nondistortion-corrected and distortion-corrected data sets by resampling with and without spatial coregistration. The ADC values were calculated on the volume and voxel level. The effect of distortion correction on ADC quantification and tissue classification was evaluated using linear-mixed models and logistic regression, respectively. RESULTS: Without coregistration, the absolute differences in tumor ADC (range: 0.0002-0.189 mm2 /s×10-3 (volume level); 0.014-0.493 mm2 /s×10-3 (voxel level)) between the nondistortion-corrected and distortion-corrected were significantly associated (P < 0.05) with distortion distance (mean: 1.4 ± 1.3 mm; range: 0.3-5.3 mm). No significant associations were found upon coregistration; however, in patients with high rectal gas residue, distortion correction resulted in improved spatial representation and significantly better classification of healthy versus tumor voxels (P < 0.05). CONCLUSIONS: Geometric distortion correction in DWI could improve quantitative ADC analysis in multiparametric prostate MRI. Magn Reson Med 79:2524-2532, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

High temporal resolution motion estimation using a self-navigated simultaneous multi-slice echo planar imaging acquisition.

BACKGROUND: Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations. PURPOSE: To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator. STUDY TYPE: Prospective feasibility study. POPULATION/SUBJECTS: Three human volunteers. FIELD STRENGTH/SEQUENCE: 3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6. ASSESSMENT: Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE). STATISTICAL TESTS: Direct comparison of NMSE values. RESULTS: High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates. DATA CONCLUSION: Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

BACKGROUND: Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. PURPOSE: To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). STUDY TYPE: Prospective. SUBJECTS: Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). FIELD STRENGTH/SEQUENCE: Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. ASSESSMENT: Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. STATISTICAL TESTS: Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. RESULTS: For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. DATA CONCLUSION: Our findings suggest that SVM, using features from a combination of diffusion models, improves prediction accuracy for differentiation of benign versus malignant breast tumors, and may further assist in subtyping of breast cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1205-1216.

Relative enhanced diffusivity: noise sensitivity, protocol optimization, and the relation to intravoxel incoherent motion.

OBJECTIVE: To explore the relationship between relative enhanced diffusivity (RED) and intravoxel incoherent motion (IVIM), as well as the impact of noise and the choice of intermediate diffusion weighting (b value) on the RED parameter. MATERIALS AND METHODS: A mathematical derivation was performed to cast RED in terms of the IVIM parameters. Noise analysis and b value optimization was conducted by using Monte Carlo calculations to generate diffusion-weighted imaging data appropriate to breast and liver tissue at three different signal-to-noise ratios. RESULTS: RED was shown to be approximately linearly proportional to the IVIM parameter f, inversely proportional to D and to follow an inverse exponential decay with respect to D*. The choice of intermediate b value was shown to be important in minimizing the impact of noise on RED and in maximizing its discriminatory power. RED was shown to be essentially a reparameterization of the IVIM estimates for f and D obtained with three b values. CONCLUSION: RED imaging in the breast and liver should be performed with intermediate b values of 100 and 50 s/mm2, respectively. Future clinical studies involving RED should also estimate the IVIM parameters f and D using three b values for comparison.

Relationship between kurtosis and bi-exponential characterization of high b-value diffusion-weighted imaging: application to prostate cancer.

BACKGROUND: High b-value diffusion-weighted imaging has application in the detection of cancerous tissue across multiple body sites. Diffusional kurtosis and bi-exponential modeling are two popular model-based techniques, whose performance in relation to each other has yet to be fully explored. PURPOSE: To determine the relationship between excess kurtosis and signal fractions derived from bi-exponential modeling in the detection of suspicious prostate lesions. MATERIAL AND METHODS: This retrospective study analyzed patients with normal prostate tissue (n = 12) or suspicious lesions (n = 13, one lesion per patient), as determined by a radiologist whose clinical care included a high b-value diffusion series. The observed signal intensity was modeled using a bi-exponential decay, from which the signal fraction of the slow-moving component was derived ( SFs). In addition, the excess kurtosis was calculated using the signal fractions and ADCs of the two exponentials ( KCOMP). As a comparison, the kurtosis was also calculated using the cumulant expansion for the diffusion signal ( KCE). RESULTS: Both K and KCE were found to increase with SFs within the range of SFs commonly found within the prostate. Voxel-wise receiver operating characteristic performance of SFs, KCE, and KCOMP in discriminating between suspicious lesions and normal prostate tissue was 0.86 (95% confidence interval [CI] = 0.85 - 0.87), 0.69 (95% CI = 0.68-0.70), and 0.86 (95% CI = 0.86-0.87), respectively. CONCLUSION: In a two-component diffusion environment, KCOMP is a scaled value of SFs and is thus able to discriminate suspicious lesions with equal precision . KCE provides a computationally inexpensive approximation of kurtosis but does not provide the same discriminatory abilities as SFs and KCOMP.

Stimulated echo diffusion tensor imaging (STEAM-DTI) with varying diffusion times as a probe of breast tissue.

PURPOSE: To explore the application of diffusion tensor imaging (DTI) for breast tissue and breast pathologies using a stimulated-echo acquisition mode (STEAM) with variable diffusion times. MATERIALS AND METHODS: In this Health Insurance Portability and Accountability Act-compliant study, approved by the local institutional review board, eight patients and six healthy volunteers underwent an MRI examination at 3 Tesla including STEAM-DTI with several diffusion times ranging from 68.5 to 902.5 ms. A DTI model was fitted to the data for each diffusion time, and parametric maps of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for healthy fibroglandular tissue (FGT) and lesions. The median value of radial diffusivity for FGT was fitted to a linear decay to obtain an estimation of the surface-to-volume ratio, from which the radial diameter was calculated. RESULTS: For healthy FGT, radial diffusivity presented a linear decay with the square root of the diffusion time resulting in a range of estimated radial diameters from 202 to 496 µm, while axial diffusivity presented a nearly time-independent diffusion. Residual fat signal was reduced at longer diffusion times due to the shorter T1 of fat. Residual fat signal to the overall signal in the healthy volunteers' FGT was found to range from 2.39% to 2.55% (shortest mixing time), and from 0.40% to 0.51% (longest mixing time) for the b500 images. CONCLUSION: The use of variable diffusion times may provide an in vivo noninvasive tool to probe diffusion lengths in breast tissue and breast pathology, and might aid by improving fat suppression at longer diffusion times. LEVEL OF EVIDENCE: 2 J. Magn. Reson. Imaging 2017;45:84-93.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.

PURPOSE: To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. MATERIALS AND METHODS: 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (Ktrans and Ve) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. RESULTS: ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with Ktrans and Ve. GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, Ktrans, and Ve. The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. CONCLUSION: T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. KEY POINTS: • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

A Simplified Approach to Measure the Effect of the Microvasculature in Diffusion-weighted MR Imaging Applied to Breast Tumors: Preliminary Results.

Purpose To evaluate the relative change of the apparent diffusion coefficient (ADC) at low- and medium-b-value regimens as a surrogate marker of microcirculation, to study its correlation with dynamic contrast agent-enhanced (DCE) magnetic resonance (MR) imaging-derived parameters, and to assess its potential for differentiation between malignant and benign breast tumors. Materials and Methods Ethics approval and informed consent were obtained. From May 2013 to June 2015, 61 patients diagnosed with either malignant or benign breast tumors were prospectively recruited. All patients were scanned with a 3-T MR imager, including diffusion-weighted imaging (DWI) and DCE MR imaging. Parametric analysis of DWI and DCE MR imaging was performed, including a proposed marker, relative enhanced diffusivity (RED). Spearman correlation was calculated between DCE MR imaging and DWI parameters, and the potential of the different DWI-derived parameters for differentiation between malignant and benign breast tumors was analyzed by dividing the sample into equally sized training and test sets. Optimal cut-off values were determined with receiver operating characteristic curve analysis in the training set, which were then used to evaluate the independent test set. Results RED had a Spearman rank correlation of 0.61 with the initial area under the curve calculated from DCE MR imaging. Furthermore, RED differentiated cancers from benign tumors with an overall accuracy of 90% (27 of 30) on the test set with 88.2% (15 of 17) sensitivity and 92.3% (12 of 13) specificity. Conclusion This study presents promising results introducing a simplified approach to assess results from a DWI protocol sensitive to the intravoxel incoherent motion effect by using only three b values. This approach could potentially aid in the differentiation, characterization, and monitoring of breast pathologies. © RSNA, 2016 Online supplemental material is available for this article.

Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging.

BACKGROUND: To compare "standard" diffusion weighted imaging, and diffusion tensor imaging (DTI) of 2(nd) and 4(th) -order for the differentiation of malignant and benign breast lesions. METHODS: Seventy-one patients were imaged at 3 Tesla with a 16-channel breast coil. A diffusion weighted MRI sequence including b = 0 and b = 700 in 30 directions was obtained for all patients. The image data were fitted to three different diffusion models: isotropic model - apparent diffusion coefficient (ADC), 2(nd) -order tensor model (the standard model used for DTI) and a 4(th) -order tensor model, with increased degrees of freedom to describe anisotropy. The ability of the fitted parameters in the different models to differentiate between malignant and benign tumors was analyzed. RESULTS: Seventy-two breast lesions were analyzed, out of which 38 corresponded to malignant and 34 to benign tumors. ADC (using any model) presented the highest discriminative ability of malignant from benign tumors with a receiver operating characteristic area under the curve (AUC) of 0.968, and sensitivity and specificity of 94.1% and 94.7% respectively for a 1.33 × 10(-3) mm(2) /s cutoff. Anisotropy measurements presented high statistical significance between malignant and benign tumors (P < 0.001), but with lower discriminative ability of malignant from benign tumors than ADC (AUC of 0.896 and 0.897 for fractional anisotropy and generalized anisotropy respectively). Statistical significant difference was found between generalized anisotropy and fractional anisotropy for cancers (P < 0.001) but not for benign lesions (P = 0.87). CONCLUSION: While anisotropy parameters have the potential to provide additional value for breast applications as demonstrated in this study, ADC exhibited the highest differentiation power between malignant and benign breast tumors.

Diffusion-weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model.

PURPOSE: To improve early diagnosis of prostate cancer to aid clinical decision-making. Diffusion-weighted magnetic resonance imaging (DW-MRI) is sensitive to water diffusion throughout tissues, which correlates with Gleason score, a histological measure of prostate cancer aggressiveness. In this study the ability of DW-MRI to detect prostate cancer onset and development was evaluated in transgenic adenocarcinoma of the mouse prostate (TRAMP) mice. MATERIALS AND METHODS: T2 -weighted and DW-MRI were acquired using a 7T MR scanner, 200 mm bore diameter; 10 TRAMP and 6 C57BL/6 control mice were scanned every 4 weeks from 8 weeks of age until sacrifice at 28-30 weeks. After sacrifice, the genitourinary tract was excised and sectioned for histological analysis. Histology slides registered with DW-MR images allowed for validation of DW-MR images and the apparent diffusion coefficient (ADC) as tools for cancer detection and disease stratification. An automated early assessment tool based on ADC threshold values was developed to aid cancer detection and progression monitoring. RESULTS: The ADC differentiated between control prostate ((1.86 ± 0.20) × 10(-3) mm(2) /s) and normal TRAMP prostate ((1.38 ± 0.10) × 10(-3) mm(2) /s) (P = 0.0001), between TRAMP prostate and well-differentiated cancer ((0.93 ± 0.18) × 10(-3) mm(2) /s) (P = 0.0006), and between well-differentiated cancer and poorly differentiated cancer ((0.63 ± 0.06) × 10(-3) mm(2) /s) (P = 0.02). CONCLUSION: DW-MRI is a tool for early detection of cancer, and discrimination between cancer stages in the TRAMP model. The incorporation of DW-MRI-based prostate cancer stratification and monitoring could increase the accuracy of preclinical trials using TRAMP mice.

Inhomogeneous static magnetic field-induced distortion correction applied to diffusion weighted MRI of the breast at 3T.

PURPOSE: To evaluate the performance of an advanced method for correction of inhomogeneous static magnetic field induced distortion in echo-planar imaging (EPI), applied to diffusion-weighted MRI (DWI) of the breast. METHODS: An algorithm for distortion correction based on the symmetry of the distortion induced by static field inhomogeneity when the phase encoding polarity is reversed was evaluated in 36 data sets of patients who received an MRI examination that included DWI (b = 0 and 700 s/mm(2) ) and an extra b = 0 s/mm(2) sequence with opposite phase encoding polarity. The decrease of the L2 -square norm after correction between opposed phase encoding b = 0 images was calculated. Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images was calculated before and after correction. RESULTS: The L2 -square norm between different phase encoding polarities for b = 0 images was reduced 94.3% on average after distortion correction. Furthermore, Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images increased significantly after correction for all cases (P < 0.001). CONCLUSION: Geometric distortion correction in DWI of the breast results in higher similarity of DWI to anatomical non-EPI T2 -weighted images and would potentially allow for a more reliable lesion segmentation mapping among different MRI modalities.

Dynamic contrast-enhanced MRI texture analysis for pretreatment prediction of clinical and pathological response to neoadjuvant chemotherapy in patients with locally advanced breast cancer.

The aim of this study was to investigate the potential of texture analysis, applied to dynamic contrast-enhanced MRI (DCE-MRI), to predict the clinical and pathological response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) before NAC is started. Fifty-eight patients with LABC were classified on the basis of their clinical response according to the Response Evaluation Criteria in Solid Tumors (RECIST) guidelines after four cycles of NAC, and according to their pathological response after surgery. T1 -weighted DCE-MRI with a temporal resolution of 1 min was acquired on a 3-T Siemens Trio scanner using a dedicated four-channel breast coil before the onset of treatment. Each lesion was segmented semi-automatically using the 2-min post-contrast subtracted image. Sixteen texture features were obtained at each non-subtracted post-contrast time point using a gray level co-occurrence matrix. Appropriate statistical analyses were performed and false discovery rate-based q values were reported to correct for multiple comparisons. Statistically significant results were found at 1-3 min post-contrast for various texture features for the prediction of both the clinical and pathological response. In particular, eight texture features were found to be statistically significant at 2 min post-contrast, the most significant feature yielding an area under the curve (AUC) of 0.77 for response prediction for stable disease versus complete responders after four cycles of NAC. In addition, four texture features were found to be significant at the same time point, with an AUC of 0.69 for response prediction using the most significant feature for classification based on the pathological response. Our results suggest that texture analysis could provide clinicians with additional information to increase the accuracy of prediction of an individual response before NAC is started.

Definitive Radiation With Nodal Boost for Patients With Locally Advanced Breast Cancer.

PURPOSE: The optimal local therapy of patients with nodal disease in supraclavicular (SCV), internal mammary nodes (IMN) and level III axilla is not well studied. We aimed to evaluate the outcomes of patients with breast cancer and advanced nodal disease that received a nodal boost. METHODS AND MATERIALS: This retrospective study included 79 patients with advanced nodal disease who underwent adjuvant radiation with a nodal boost to the SCV, IMNs, and/or axilla. All patients had radiographic changes after systemic therapy concerning for gross nodal disease. Overall survival, disease-free survival (DFS), and local recurrence-free survival were estimated using the Kaplan-Meier method. RESULTS: All patients received an initial 50 Gy to the breast/chest wall and regional nodes, of whom 46.8% received an IMN boost, 38.0% axillary (ax)/SCV boost, and 15.2% both IMN and ax/SCV boost (IMN + ax/SCV). Most patients had hormone receptor positive (74.7%) and human epidermal growth factor receptor 2 negative disease (83.5%). In addition, 12.7% of patients had clinical (c) N2 disease, 21.5% cN3A disease, 51.9% cN3B disease, and 5.1% cN3C disease. Most patients received chemotherapy (97.5%). The median nodal boost dose was 10 Gy (range, 10-20 Gy), with 21.6% of IMN, 16.7% of ax/SCV, and 16.7% of IMN + ax/SCV receiving 14 to 20 Gy. With a median follow up of 30 months, the 3-year local recurrence-free survival, DFS, and overall survival rates were 94.5%, 86.3%, and 93.8%, respectively. Crude rates of failure were 13.9% (10.1% distant failure [DF] alone; 3.8% DF + locoregional failure [LRF]). Rates of failure by boost group were 13.3% for ax/SCV (10.0% DF alone; 3.3% DF + LRF), 5.4% for IMN (2.7% DF alone, 2.7% DF + LRF), and 41.7% for IMN + ax/SCV (33.3% DF, 8.3% DF + LRF). There were no LRFs without DFs. The median time to failure was 22.8 months (interquartile range, 18-34 months). Clinical tumor size and IMN + ax/SCV versus IMN or ax/SCV alone was associated with worse DFS (hazard ratio [HR]: 9.78; 95% confidence interval [CI], 2.07-46.2; P = .004 and HR: 9.49; 95% CI, 2.67-33.7; P = .001, respectively). On multivariate analysis, IMN + ax/SCV versus IMN or ax/SCV alone retained significance (HR: 4.80; 95% CI, 1.27-18.13; P = .02). CONCLUSIONS: In this population of patients with locally advanced breast cancer, the majority of failures were distant with no isolated LRFs. Failures were the highest in the IMN + ax/SCV group (∼40%). Further treatment escalation is necessary for these patients.

Risk of Radiation Dermatitis in Patients With Skin of Color Who Undergo Radiation to the Breast or Chest Wall With and Without Regional Nodal Irradiation.

PURPOSE: Acute radiation dermatitis (ARD) is common after radiation therapy for breast cancer, with data indicating that ARD may disproportionately affect Black or African American (AA) patients. We evaluated the effect of skin of color (SOC) on physician-reported ARD in patients treated with radiation therapy. METHODS AND MATERIALS: We identified patients treated with whole breast or chest wall ± regional nodal irradiation or high tangents using 50 Gy in 25 fractions from 2015 to 2018. Baseline skin pigmentation was assessed using the Fitzpatrick scale (I = light/pale white to VI = black/very dark brown) with SOC defined as Fitzpatrick scale IV to VI. We evaluated associations among SOC, physician-reported ARD, late hyperpigmentation, and use of oral and topical treatments for RD using multivariable models. RESULTS: A total of 325 patients met eligibility, of which 40% had SOC (n = 129). On multivariable analysis, Black/AA race and chest wall irradiation had a lower odds of physician-reported grade 2 or 3 ARD (odds ratio [OR], 0.110; 95% confidence interval [CI], 0.030-0.397; P = .001; OR, 0.377; 95% CI, 0.161-0.883; P = .025), whereas skin bolus (OR, 8.029; 95% CI, 3.655-17.635; P = 0) and planning target volume D0.03cc (OR, 1.001; 95% CI, 1.000-1.001; P = .028) were associated with increased odds. On multivariable analysis, SOC (OR, 3.658; 95% CI, 1.236-10.830; P = .019) and skin bolus (OR, 26.786; 95% CI, 4.235-169.432; P = 0) were associated with increased odds of physician-reported late grade 2 or 3 hyperpigmentation. There was less frequent use of topical steroids to treat ARD and more frequent use of oral analgesics in SOC versus non-SOC patients (43% vs 63%, P < .001; 50% vs 38%, P = .05, respectively). CONCLUSIONS: Black/AA patients exhibited lower odds of physician-reported ARD. However, we found higher odds of late hyperpigmentation in SOC patients, independent of self-reported race. These findings suggest that ARD may be underdiagnosed in SOC when using the physician-rated scale despite this late evidence of radiation-induced skin toxicity.

Considerations for intensity modulated total body or total marrow and lymphoid irradiation.

We compiled a sampling of the treatment techniques of intensity-modulated total body irradiation, total marrow irradiation and total marrow and lymphoid irradiation utilized by several centers across North America and Europe. This manuscript does not serve as a consensus guideline, but rather is meant to serve as a convenient reference for centers that are considering starting an intensity-modulated program.

Assessing the reproducibility of CBCT-derived radiomics features using a novel three-dimensional printed phantom.

PURPOSE: Radiomics modeling is an exciting avenue for enhancing clinical decision making and personalized treatment. Radiation oncology patients often undergo routine imaging for position verification, particularly using LINAC-mounted cone beam computed tomography (CBCT). The wealth of imaging data collected in modern radiation therapy presents an ideal use case for radiomics modeling. Despite this, texture feature (TF) calculation can be limited by concerns over feature stability and reproducibility; in theory, this issue is compounded by the relatively poor image quality of CBCT, as well as variation of acquisition and reconstruction parameters. METHODS: In this study, we developed and validated a novel three-dimensional (3D) printed phantom for evaluating CBCT-based TF reliability. The phantom has a cylindrical shape (22 cm diameter and 25.5 cm height) with five inner inserts designed to hold custom-printed rods (1 cm diameter and 10-20 cm height) of various materials, infill shapes, and densities. TF reproducibility was evaluated across and within three LINACs from a single vendor using sets of three consecutive CBCT taken with the head, thorax, and pelvis clinical imaging protocols. PyRadiomics was used to extract a standard set of TFs from regions of interest centered on each rod. Two-way mixed effects absolute agreement intra-class correlation coefficient (ICC) was used to evaluate TF reproducibility, with features showing ICC values above 0.9 considered robust if their Bonferroni-corrected p-value was below 0.05. RESULTS: A total of 63, 87, and 83 features exhibited test-retest reliability for the head, thorax, and pelvis imaging protocols respectively. When assessing stability between discreet imaging sessions on the same LINAC, these numbers were reduced to 5, 63, and 70 features, respectively. The thorax and pelvis protocols maintained a rich candidate feature space in inter-LINAC analysis with 61 and 65 features, respectively, exceeding the ICC criteria. Crucially, no features were deemed reproducible when compared between protocols. CONCLUSIONS: We have developed a 3D phantom for consistent evaluation of TF stability and reproducibility. For LINACs from a single vendor, our study found a substantial number of features available for robust radiomics modeling from CBCT imaging. However, some features showed variations across LINACs. Studies involving CBCT-based radiomics must preselect features prior to their use in clinical-based models.

Bone structure and perfusion quantification of bone marrow edema pattern in the wrist of patients with rheumatoid arthritis: a multimodality study.

OBJECTIVE: To quantify bone structure and perfusion parameters in regions of bone marrow edema pattern (BMEP), non-edematous bone marrow (NBM), and pannus tissue areas in the wrists of patients with rheumatoid arthritis (RA) using 3-Tesla (3T) magnetic resonance imaging (MRI), and high resolution peripheral quantitative computed tomography (HR-pQCT). METHODS: Sixteen subjects fulfilling American College of Rheumatology classification were imaged using a HR-pQCT system and a 3T MRI scanner with an 8-channel wrist coil. Coronal T2-weighted and dynamic contrast-enhanced (DCE-MRI) images were acquired. BMEP and pannus tissue areas were segmented semiautomatically in T2-weighted images. NBM areas were placed at a similar distance from the joint space as BMEP regions. MR and HR-pQCT images were registered, and bone variables were calculated within the BMEP and NBM regions. Perfusion parameters in BMEP, pannus tissue, and NBM regions were calculated based on the signal-time curve obtained from DCE-MRI. RESULTS: Eighteen BMEP areas were segmented, 15 of them presented proximal to pannus-filled erosions. Significant increases in bone density and trabecular thickness and number were observed in all BMEP regions compared to NMB (p < 0.05). Significantly elevated perfusion measures were observed in both BMEP and pannus tissue regions compared to NBM (p < 0.05). CONCLUSION: BMEP regions showed significantly increased bone density and structures as well as perfusion measures, suggesting bone remodeling and active inflammation. Combining MRI and HR-pQCT provides a powerful multimodality approach for understanding BMEP and erosions, and for potentially identifying novel imaging markers for disease progression in RA.