Clinical Experience With an Offline Adaptive Radiation Therapy Head and Neck Program: Dosimetric Benefits and Opportunities for Patient Selection.

PURPOSE: The objective of this study was to develop a linear accelerator (LINAC)-based adaptive radiation therapy (ART) workflow for the head and neck that is informed by automated image tracking to identify major anatomic changes warranting adaptation. In this study, we report our initial clinical experience with the program and an investigation into potential trigger signals for ART. METHODS AND MATERIALS: Offline ART was systematically performed on patients receiving radiation therapy for head and neck cancer on C-arm LINACs. Adaptations were performed at a single time point during treatment with resimulation approximately 3 weeks into treatment. Throughout treatment, all patients were tracked using an automated image tracking system called the Automated Watchdog for Adaptive Radiotherapy Environment (AWARE). AWARE measures volumetric changes in gross tumor volumes (GTVs) and selected normal tissues via cone beam computed tomography scans and deformable registration. The benefit of ART was determined by comparing adaptive plan dosimetry and normal tissue complication probabilities against the initial plans recalculated on resimulation computed tomography scans. Dosimetric differences were then correlated with AWARE-measured volume changes to identify patient-specific triggers for ART. Candidate trigger variables were evaluated using receiver operator characteristic analysis. RESULTS: In total, 46 patients received ART in this study. Among these patients, we observed a significant decrease in dose to the submandibular glands (mean ± standard deviation: -219.2 ± 291.2 cGy, P < 10-5), parotids (-68.2 ± 197.7 cGy, P = .001), and oral cavity (-238.7 ± 206.7 cGy, P < 10-5) with the adaptive plan. Normal tissue complication probabilities for xerostomia computed from mean parotid doses also decreased significantly with the adaptive plans (P = .008). We also observed systematic intratreatment volume reductions (ΔV) for GTVs and normal tissues. Candidate triggers were identified that predicted significant improvement with ART, including parotid ΔV = 7%, neck ΔV = 2%, and nodal GTV ΔV = 29%. CONCLUSIONS: Systematic offline head and neck ART was successfully deployed on conventional LINACs and reduced doses to critical salivary structures and the oral cavity. Automated cone beam computed tomography tracking provided information regarding anatomic changes that may aid patient-specific triggering for ART.

Automated tracking of morphologic changes in weekly magnetic resonance imaging during head and neck radiotherapy.

BACKGROUND AND PURPOSE: Anatomic changes during head and neck radiotherapy can impact dose delivery, necessitate adaptive replanning, and indicate patient-specific response to treatment. We have developed an automated system to track these changes through longitudinal MRI scans to aid identification and clinical intervention. The purpose of this article is to describe this tracking system and present results from an initial cohort of patients. MATERIALS AND METHODS: The Automated Watchdog in Adaptive Radiotherapy Environment (AWARE) was developed to process longitudinal MRI data for radiotherapy patients. AWARE automatically identifies and collects weekly scans, propagates radiotherapy planning structures, computes structure changes over time, and reports important trends to the clinical team. AWARE also incorporates manual structure review and revision from clinical experts and dynamically updates tracking statistics when necessary. AWARE was applied to patients receiving weekly T2-weighted MRI scans during head and neck radiotherapy. Changes in nodal gross tumor volume (GTV) and parotid gland delineations were tracked over time to assess changes during treatment and identify early indicators of treatment response. RESULTS: N = 91 patients were tracked and analyzed in this study. Nodal GTVs and parotids both shrunk considerably throughout treatment (-9.7 ± 7.7% and -3.7 ± 3.3% per week, respectively). Ipsilateral parotids shrunk significantly faster than contralateral (-4.3 ± 3.1% vs. -2.9 ± 3.3% per week, p = 0.005) and increased in distance from GTVs over time (+2.7 ± 7.2% per week, p < 1 × 10-5 ). Automatic structure propagations agreed well with manual revisions (Dice = 0.88 ± 0.09 for parotids and 0.80 ± 0.15 for GTVs), but for GTVs the agreement degraded 4-5 weeks after the start of treatment. Changes in GTV volume observed by AWARE as early as one week into treatment were predictive of large changes later in the course (AUC = 0.79). CONCLUSION: AWARE automatically identified longitudinal changes in GTV and parotid volumes during radiotherapy. Results suggest that this system may be useful for identifying rapidly responding patients as early as one week into treatment.

Dose differentiated high-dose-rate prostate brachytherapy: a feasibility assessment of MRI-guided dose escalation to dominant intra-prostatic lesions.

Purpose: Prostate brachytherapy is routinely performed with trans-rectal ultrasound (TRUS)- or computed tomography (CT)-based planning that cannot delineate dominant intra-prostatic lesions (DILs). In contrast, magnetic resonance imaging (MRI)-based planning allows for more accurate DIL delineation and dose escalation. This study assessed the maximum achievable dose escalation to DILs. Material and methods: We retrospectively identified 24 patients treated with high-dose-rate (HDR) prostate brachytherapy boost (15 Gy in 1 fraction). All patients had a pre-treatment prostate MRI with 1-3 DILs. MRIs were used to delineate DILs and were co-registered to TRUS intra-procedure. Treatment plans were experimentally re-optimized to escalate DIL dose. Dosimetric indices from the original and re-optimized plans were compared using two-tailed paired t-test. Re-optimized plans were deemed acceptable if they achieved all of the following criteria: prostate D90 > 100%, prostate V100 > 90%, urethra D10 < 118%, rectum V80 < 0.5 cc, bladder D1cc < 75%, or if they did not exceed organs at risk (OARs) doses of the original plan. Results: The mean DIL D90 was significantly increased from 134% of the prescription dose on the original plans to 154% on the re-optimized plans. The mean urethra D10 and mean bladder D1cc were significantly reduced from 123% to 117% and from 72% to 65%, respectively. Prostate D90 was reduced from 106% to 102%, and prostate V100 was reduced from 93% to 91%. Conclusions: We re-optimized HDR brachytherapy plans to escalate DILs dose to a mean D90 of > 150% while maintaining favorable prostate coverage and OARs doses. We propose DIL D90 dose of > 150% (22.5 Gy) as an achievable goal.

The future of MRI in radiation therapy: Challenges and opportunities for the MR community.

Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.

Clinical Outcomes and Predictors of Lung Toxicity After Multiple Courses of Lung Stereotactic Body Radiotherapy for Early-Stage Non-Small Cell Lung Cancer.

BACKGROUND: The clinical outcomes of multicourse lung stereotactic body radiotherapy (SBRT) have yet to be validated in a prospective study, and there are a lack of data on allowable composite dosimetry. PATIENTS AND METHODS: Forty-four patients underwent multicourse lung SBRT for recurrent or metachronous NSCLC. The median biologically effective dose (BED10) for the first course and subsequent courses were 132 and 100 Gy, respectively. Patient and treatment characteristics were evaluated to determine the correlation with the development of radiation pneumonitis (RP). RESULTS: The local control rate was 91%. A total of 13.6% developed a grade 2+ RP, and 4.5% developed a grade 3+ RP, including one grade 5. On univariable analysis, multiple composite dosimetric factors (V5 [proportion of lung structure receiving at least 5 Gy], V10, V20, V40, and mean lung dose) were correlated with the development of RP. When comprised of the first and second course of SBRT, a composite lung V5 of < 30% and > 50% was associated with a 0 and 75% incidence of grade 2+ RP, respectively. We identified no significant correlation on multivariable analysis but observed a strong trend between composite lung V5 and the development of grade 2+ RP (hazard ratio, 1.157; P = .058). Evaluation of multiple clinical factors also identified a significant correlation between the timing of repeat lung SBRT and the development of grade 2+ RP after the second course (P = .0028). CONCLUSION: Subsequent courses of lung SBRT, prescribed to a median BED10 of 100 Gy, can provide a high rate of local control with a 4.5% incidence of grade 3+ toxicity. Composite lung V5 and the timing of the second course of lung SBRT may be correlated to the development of RP.

Extracting diffusion tensor fractional anisotropy and mean diffusivity from 3-direction DWI scans using deep learning.

PURPOSE: To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions. METHODS: Two machine-learning models were implemented to map undersampled dMRI signals with high-quality FA and MD maps that were reconstructed from fully sampled DTI scans. The first model was a previously described multilayer perceptron (MLP), which maps signals and FA/MD values from a single voxel. The second was a convolutional neural network U-Net model, which maps dMRI slices to full FA/MD maps. Each method was trained on dMRI brain scans (N = 46), and reconstruction accuracies were compared with conventional linear-least-squares (LLS) reconstructions. RESULTS: In an independent testing cohort (N = 20), 3-direction U-Net reconstructions had significantly lower absolute FA error than both 3-direction MLP (U-Net3-dir : 0.06 ± 0.01 vs. MLP3-dir : 0.08 ± 0.01, P < 1 × 10-5 ) and 6-direction LLS (LLS6-dir : 0.09 ± 0.03, P = 1 × 10-5 ). The MD errors were not significantly different among 3-direction MLP (0.06 ± 0.01 × 10-3 mm2 /s), 3-direction U-Net (0.06 ± 0.01 × 10-3 mm2 /s), and 6-direction LLS (0.07 ± 0.02 × 10-3 mm2 /s, P > .1). CONCLUSION: The proposed U-Net model reconstructed FA from 3-direction dMRI scans with improved accuracy compared with both a previously described MLP approach and LLS fitting from 6-direction scans. The MD reconstruction accuracies did not differ significantly between reconstructions.

An error detection method for real-time EPID-based treatment delivery quality assurance.

PURPOSE: To quantify the error detection power of a new treatment delivery error detection method. The method validates monitor unit (MU) resolved beam apertures using real-time EPID images. METHODS: The on-board EPID imager was used to measure cine-EPID (~10 Hz) images for 27 beams from 15 VMAT/SBRT clinical treatment plans and five nonclinical plans. For each frame acquisition, planned apertures were interpolated from the treatment plan multileaf collimator (MLC) positions expected during the frame acquisition interval. Inaccurate deliveries were identified by monitoring in-aperture missed fluence and out-of-aperture excess fluence beyond a specified buffer. Delivery errors were simulated by perturbing the planned MLC positions before comparison with nonperturbed measured apertures. Systematic 1-5 mm MLC leaf shifts were used to train a logistic regression model to determine the error detection threshold. Model accuracy was monitored using tenfold cross-validation. The model's error detection ability was tested with other error modes: plan control point (CP) weight perturbations, collimator rotations, random MLC leaf position errors, EPID imager shift, and stuck MLC leaf. The error detection accuracy was evaluated using the Matthews correlation coefficient (MCC) and the false positive rate (FPR). Per-beam error thresholds of >1, >5, and >10% errant frames were tested to label per-beam errors. The model also was tested for its ability to distinguish five cases with highly similar plans and compared with gamma analysis. RESULTS: Delivery errors were detected by monitoring intended per-frame images with a 2 mm MLC buffer. Frame-by-frame aperture errors were identified with an optimal threshold of 0.3% of the expected aperture area. The per-frame FPR was 0.02%. The MCC was 1.00 (perfect classification) for detection based on 1% of frames for random CP weight shift, 3 mm random MLC shifts, 90° and 180° collimator rotations, and an MLC leaf stuck after 10% of the beam delivery. The MCC for 2°, 4°, and 8° collimator rotation were 0.53, 0.76, and 0.96, respectively, for the 1% of beam delivery threshold. The 3 mm EPID shift had poor detection, with a minimum MCC of 0.14. The highly similar plans were reliably detected by the aperture check but were not detectable with gamma analysis. CONCLUSION: The high error detection sensitivity and low FPR makes the aperture check error detection method well suited to pretreatment and during-treatment beam delivery quality assurance (QA). The aperture check detects subtle beam delivery errors, including those resulting from MLC leaf positioning deviations, CP MU shifts, and stuck MLC leaves. Furthermore, the method can distinguish between highly similar treatment plans. Since the aperture check method monitors for the aperture shapes over a given MU interval, it is also sensitive to errors in MU per CP, without requiring dosimetric calibration of the EPID. The aperture check is one part of a Swiss cheese error detection scheme, which provides redundant error testing of multiple error modes, including nonaperture related errors. The rapid error detection, at 1% of a beam's delivery, make the aperture check a potential candidate for QA of on-line adaptive radiotherapy, or other situations in which pretreatment delivery QA is impractical.

An Automated Workflow to Improve Efficiency in Radiation Therapy Treatment Planning by Prioritizing Organs at Risk.

PURPOSE: Manual delineation (MD) of organs at risk (OAR) is time and labor intensive. Auto-delineation (AD) can reduce the need for MD, but because current algorithms are imperfect, manual review and modification is still typically used. Recognizing that many OARs are sufficiently far from important dose levels that they do not pose a realistic risk, we hypothesize that some OARs can be excluded from MD and manual review with no clinical effect. The purpose of this study was to develop a method that automatically identifies these OARs and enables more efficient workflows that incorporate AD without degrading clinical quality. METHODS AND MATERIALS: Preliminary dose map estimates were generated for n = 10 patients with head and neck cancers using only prescription and target-volume information. Conservative estimates of clinical OAR objectives were computed using AD structures with spatial expansion buffers to account for potential delineation uncertainties. OARs with estimated dose metrics below clinical tolerances were deemed low priority and excluded from MD and/or manual review. Final plans were then optimized using high-priority MD OARs and low-priority AD OARs and compared with reference plans generated using all MD OARs. Multiple different spatial buffers were used to accommodate different potential delineation uncertainties. RESULTS: Sixty-seven out of 201 total OARs were identified as low-priority using the proposed methodology, which permitted a 33% reduction in structures requiring manual delineation/review. Plans optimized using low-priority AD OARs without review or modification met all planning objectives that were met when all MD OARs were used, indicating clinical equivalence. CONCLUSIONS: Prioritizing OARs using estimated dose distributions allowed a substantial reduction in required MD and review without affecting clinically relevant dosimetry.

Intracranial disease control for EGFR-mutant and ALK-rearranged lung cancer with large volume or symptomatic brain metastases.

PURPOSE/OBJECTIVE(S): Tyrosine kinase inhibitors (TKIs) are commonly employed for patients with brain metastases from lung cancer and specific driver mutations. We sought to identify the correlation between intracranial tumor burden and outcomes in patients with brain metastases treated with TKIs. MATERIALS/METHODS: We identified and retrospectively reviewed cases of EGFR-mutant or ALK-rearranged lung cancer with brain metastases at any time during their cancer course. Clinical characteristics and treatment information were abstracted from the medical records. Brain metastases were contoured to calculate total volume of disease at diagnosis and after initial therapy. High intracranial burden was defined as either > 10 brain metastases, volume of brain metastases > 15 cc, or largest lesion > 3 cm. Intracranial response was determined according to Response Assessment in Neuro-Oncology (RANO) criteria on the patient level. We determined the correlation between clinical and imaging characteristics and intracranial progression free survival (IC-PFS) and overall survival (OS). RESULTS: Fifty-seven patients with EGFR (n = 49) and ALK (n = 8) alterations were identified. Median follow-up from initial brain metastasis diagnosis was 17 months. Neurological symptoms were present in 54% at brain metastasis diagnosis. For those receiving TKIs alone or TKIs with radiation, at least a partial intracranial response (≥ 65% volume reduction) at 3 months from starting therapy was achieved in 94% and 58%. Progressive intracranial disease at 3 months occurred in 6.3% and 8.3%. Patients with high intracranial burden (n = 21) had a median 17 brain metastases, 6.5 cc volume, and 1.9 cm maximal tumor diameter. Median IC-PFS and OS for patients with high intracranial burden was 13.9 and 35.4 months. Patients with high intracranial burden and neurological symptoms at diagnosis had similar IC-PFS and OS compared to those with low burden and absence of neurological symptoms (p > 0.05 for each). CONCLUSION: Most patients receiving TKIs as part of their initial therapy achieve an early and durable volumetric intracranial response, irrespective of presenting disease burden or neurologic symptoms.

Automated apparent diffusion coefficient analysis for genotype prediction in lower grade glioma: association with the T2-FLAIR mismatch sign.

PURPOSE: The prognosis of lower grade glioma (LGG) patients depends (in large part) on both isocitrate dehydrogenase (IDH) gene mutation and chromosome 1p/19q codeletion status. IDH-mutant LGG without 1p/19q codeletion (IDHmut-Noncodel) often exhibit a unique imaging appearance that includes high apparent diffusion coefficient (ADC) values not observed in other subtypes. The purpose of this study was to develop an ADC analysis-based approach that can automatically identify IDHmut-Noncodel LGG. METHODS: Whole-tumor ADC metrics, including fractional tumor volume with ADC > 1.5 × 10-3mm2/s (VADC>1.5), were used to identify IDHmut-Noncodel LGG in a cohort of N = 134 patients. Optimal threshold values determined in this dataset were then validated using an external dataset containing N = 93 cases collected from The Cancer Imaging Archive. Classifications were also compared with radiologist-identified T2-FLAIR mismatch sign and evaluated concurrently to identify added value from a combined approach. RESULTS: VADC>1.5 classified IDHmut-Noncodel LGG in the internal cohort with an area under the curve (AUC) of 0.80. An optimal threshold value of 0.35 led to sensitivity/specificity = 0.57/0.93. Classification performance was similar in the validation cohort, with VADC>1.5 ≥ 0.35 achieving sensitivity/specificity = 0.57/0.91 (AUC = 0.81). Across both groups, 37 cases exhibited positive T2-FLAIR mismatch sign-all of which were IDHmut-Noncodel. Of these, 32/37 (86%) also exhibited VADC>1.5 ≥ 0.35, as did 23 additional IDHmut-Noncodel cases which were negative for T2-FLAIR mismatch sign. CONCLUSION: Tumor subregions with high ADC were a robust indicator of IDHmut-Noncodel LGG, with VADC>1.5 achieving > 90% classification specificity in both internal and validation cohorts. VADC>1.5 exhibited strong concordance with the T2-FLAIR mismatch sign and the combination of both parameters improved sensitivity in detecting IDHmut-Noncodel LGG.

Intra-myocardial alginate hydrogel injection acts as a left ventricular mid-wall constraint in swine.

Despite positive initial outcomes emerging from preclinical and early clinical investigation of alginate hydrogel injection therapy as a treatment for heart failure, the lack of knowledge about the mechanism of action remains a major shortcoming that limits the efficacy of treatment design. To identify the mechanism of action, we examined previously unobtainable measurements of cardiac function from in vivo, ex vivo, and in silico states of clinically relevant heart failure (HF) in large animals. High-resolution ex vivo magnetic resonance imaging and histological data were used along with state-of-the-art subject-specific computational model simulations. Ex vivo data were incorporated in detailed geometric computational models for swine hearts in health (n = 5), ischemic HF (n = 5), and ischemic HF treated with alginate hydrogel injection therapy (n = 5). Hydrogel injection therapy mitigated elongation of sarcomere lengths (1.68 ± 0.10µm [treated] vs. 1.78 ± 0.15µm [untreated], p<0.001). Systolic contractility in treated animals improved substantially (ejection fraction = 43.9 ± 2.8% [treated] vs. 34.7 ± 2.7% [untreated], p<0.01). The in silico models realistically simulated in vivo function with >99% accuracy and predicted small myofiber strain in the vicinity of the solidified hydrogel that was sustained for up to 13 mm away from the implant. These findings suggest that the solidified alginate hydrogel material acts as an LV mid-wall constraint that significantly reduces adverse LV remodeling compared to untreated HF controls without causing negative secondary outcomes to cardiac function. STATEMENT OF SIGNIFICANCE: Heart failure is considered a growing epidemic and hence an important health problem in the US and worldwide. Its high prevalence (5.8 million and 23 million, respectively) is expected to increase by 25% in the US alone by 2030. Heart failure is associated with high morbidity and mortality, has a 5-year mortality rate of 50%, and contributes considerably to the overall cost of health care ($53.1 billion in the US by 2030). Despite positive initial outcomes emerging from preclinical and early clinical investigation of alginate hydrogel injection therapy as a treatment for heart failure, the lack of knowledge concerning the mechanism of action remains a major shortcoming that limits the efficacy of treatment design. To understand the mechanism of action, we combined high-resolution ex vivo magnetic resonance imaging and histological data in swine with state-of-the-art subject-specific computational model simulations. The in silico models realistically simulated in vivo function with >99% accuracy and predicted small myofiber strain in the vicinity of the solidified hydrogel that was sustained for up to 13 mm away from the implant. These findings suggest that the solidified alginate hydrogel material acts as a left ventricular mid-wall constraint that significantly reduces adverse LV remodeling compared to untreated heart failure controls without causing negative secondary outcomes to cardiac function. Moreover, if the hydrogel can be delivered percutaneously rather than via the currently used open-chest procedure, this therapy may become routine for heart failure treatment. A minimally invasive procedure would be in the best interest of this patient population; i.e., one that cannot tolerate general anesthesia and surgery, and it would be significantly more cost-effective than surgery.

Normal tissue dose and risk estimates from whole and partial breast radiation techniques.

PURPOSE: To compare radiation dose to organs at risk in patients with early-stage breast cancer treated with lumpectomy and intraoperative radiation therapy with CT-guided HDR brachytherapy (precision breast IORT; PB-IORT) and those treated with external beam whole breast irradiation (WB-DIBH) or partial breast irradiation (PB-DIBH) with deep inspiratory breath hold. METHODS: We retrospectively identified 52 consecutive patients with left-sided breast cancers treated with either PB-IORT (n = 17, 76% outer breast) on a phase I clinical trial, adjuvant PB-DIBH (n = 18, 56% outer breast, 6% cavity boost), or WB-DIBH (n = 17, 76% outer breast, 53% with lumpectomy cavity boost). Conventional (2 Gy/fraction) or moderate hypofractionation (2.66 Gy/fraction) was prescribed for the external beam cohorts and 12.5 Gy in 1 fraction to 1 cm from the balloon surface was prescribed to the HDR brachytherapy cohort. CT-based planning was used for all patients. Organ at risk doses and excess risk ratios (ERR) for secondary lung cancers, contralateral breast cancers, and cardiac toxicity were compared between treatment techniques. RESULTS: Compared to WB-DIBH and PB-DIBH, PB-IORT resulted in lower ipsilateral lung V5, V10, V20, mean, and max dose (P < .05). Mean ipsilateral lung BED3Gy was as follows: 1.32 Gy for PB-IORT, 4.33 Gy for WB-DIBH, 3.35 Gy for PB-DIBH. The ERR for lung cancer was lowest for PB-IORT (P < .001). There was significantly higher contralateral breast max dose but lower mean BED3Gy for WB-DIBH compared with PB-IORT (P = .012, P = .011, respectively). Mean contralateral breast BED3Gy was as follows: 0.10 Gy for PB-IORT, 0.06 Gy for WB-DIBH, and 0.08 Gy for PB-DIBH. The ERR for contralateral breast cancer was low for all breast techniques, but WB-DIBH showed lower ERR compared to PB-IORT (P = .019). Mean heart BED2Gy was higher with PB-IORT at 1.26 Gy compared to 0.48 Gy and 0.24 Gy for WB-DIBH and PB-DIBH, respectively (P < .001). CONCLUSIONS: Patients with early-stage breast cancer treated with PB-IORT and with tissue-sparing external beam techniques all received low organ at risk doses, but PB-IORT resulted in far lower ipsilateral lung dose compared with external beam techniques. Our data indicate the lowest mean contralateral breast BED in the WB-DIBH group, likely due to the simplicity of the field design in low-risk patients using tangential whole breast radiation. External beam using DIBH results in lowest heart dose, but all techniques were well within recommended heart constraints.

Prostate diffusion MRI with minimal echo time using eddy current nulled convex optimized diffusion encoding.

BACKGROUND: Prostate diffusion-weighted imaging (DWI) using monopolar encoding is sensitive to eddy-current-induced distortion artifacts. Twice-refocused bipolar encoding suppresses eddy current artifacts, but increases echo time (TE), leading to lower signal-to-noise ratio (SNR). Optimization of the diffusion encoding might improve prostate DWI. PURPOSE: To evaluate eddy current nulled convex optimized diffusion encoding (ENCODE) for prostate DWI with minimal TE. STUDY TYPE: Prospective cohort study. POPULATION: A diffusion phantom, an ex vivo prostate specimen, 10 healthy male subjects (27 ± 3 years old), and five prostate cancer patients (62 ± 7 years old). FIELD STRENGTH/SEQUENCE: 3T; single-shot spin-echo echoplanar DWI. ASSESSMENT: Eddy-current artifacts, TE, SNR, apparent diffusion coefficient (ADC), and image quality scores from three independent readers were compared between monopolar, bipolar, and ENCODE prostate DWI for standard-resolution (1.6 × 1.6 mm2 , partial Fourier factor [pF] = 6/8) and higher-resolution protocols (1.6 × 1.6 mm2 , pF = off; 1.0 × 1.0 mm2 , pF = 6/8). STATISTICAL TESTING: SNR and ADC differences between techniques were tested with Kruskal-Wallis and Wilcoxon signed-rank tests (P < 0.05 considered significant). RESULTS: Eddy current suppression with ENCODE was comparable to bipolar encoding (mean coefficient of variation across three diffusion directions of 9.4% and 9%). For a standard-resolution protocol, ENCODE achieved similar TE as monopolar and reduced TE by 14 msec compared to bipolar, resulting in 27% and 29% higher mean SNR in prostate transition zone (TZ) and peripheral zone (PZ) (P < 0.05) compared to bipolar, respectively. For higher-resolution protocols, ENCODE achieved the shortest TE (67 msec), with 17-21% and 58-70% higher mean SNR compared to monopolar (TE = 77 msec) and bipolar (TE = 102 msec) in PZ and TZ (P < 0.05). No significant differences were found in mean TZ (P = 0.91) and PZ ADC (P = 0.94) between the three techniques. ENCODE achieved similar or higher image quality scores than bipolar DWI in patients, with mean intraclass correlation coefficient of 0.77 for overall quality between three independent readers. DATA CONCLUSION: ENCODE minimizes TE (improves SNR) and reduces eddy-current distortion for prostate DWI compared to monopolar and bipolar encoding. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1526-1539.

Increased intratumoral infiltration in IDH wild-type lower-grade gliomas observed with diffusion tensor imaging.

PURPOSE: Diffuse lower grade gliomas (LGG) with isocitrate dehydrogenase (IDH) gene mutations (IDHMUT) have a distinct survival advantage compared with IDH wild-type (IDHWT) cases but the mechanism underlying this disparity is not well understood. Diffusion Tensor Imaging (DTI) has identified infiltrated non-enhancing tumor regions that are characterized by low isotropic (p) and high anisotropic (q) diffusion tensor components that associate with poor survival in glioblastoma. We hypothesized that similar regions are more prevalent in IDHWT (vs. IDHMUT) LGG. METHODS: p and q maps were reconstructed from preoperative DTI scans in N = 41 LGG patients with known IDH mutation and 1p/19q codeletion status. Enhancing and non-enhancing tumor volumes were autosegmented from standard (non-DTI) MRI scans. Percentage non-enhancing tumor volumes exhibiting low p and high q (Vinf) were then determined using threshold values (p = 2 × 10-3mm2/s, q = 3 × 10-4 mm2/s) and compared between IDHWT and IDHMUT LGG, and between IDHMUT LGG with and without 1p/19q codeletion. RESULTS: Vinf volumes were significantly larger in IDHWT LGG than in IDHMUT LGG (35.4 ± 18.3% vs. 15.9 ± 7.6%, P < 0.001). Vinf volumes did not significantly differ between IDHMUT LGG with and without 1p/19q codeletion (17.1 ± 9.5% vs. 14.8 ± 5.8%, P = 1.0). CONCLUSION: IDHWT LGG exhibited larger volumes with suppressed isotropic diffusion (p) and high anisotropic diffusion (q) which reflects regions with increased cell density but non-disrupted neuronal structures. This may indicate a greater prevalence of infiltrative tumor in IDHWT LGG.

Quantifying the dosimetric impact of organ-at-risk delineation variability in head and neck radiation therapy in the context of patient setup uncertainty.

The purpose of this study was to quantify the potential dosimetric impact of delineation variability (DV) in head and neck radiation therapy (RT) when inherent patient setup variability (SV) is also considered. The impact of DV was assessed by generating plans with multiple structure sets, cross-evaluating them, including SV, across sets, and determining P PQM: the probability of achieving organ-specific plan quality metrics (PQM). DV was incorporated by: (1) using multiple organ at risk (OAR) structure sets delineated by independent manual observers; and (2) randomly perturbing manually generated OARs to generate alternatives with varying levels of uncertainty (low, medium, and high DV). For each structure set, independent VMAT plans were auto-generated to meet clinical PQMs. Each plan was cross-evaluated using OARs from multiple structure sets with simulated SV including per-fraction random (σ s) and per-treatment-course systematic (Σs) setup errors. The dosimetric impact of DV was assessed by examining P PQM with and without SV/DV. Clinically significant differences were defined by those that exceeded differences caused by a +2% output variation. Without including SV, simulated DV at the medium level reduced P PQM by an average of 5.5% for all OARs with D max PQMs. This reduction decreased to 2.8% for SV = 2 mm and 2.4% for SV = 4 mm (the average P PQM reduction due to 2% output errors was 2.7%). For OARs with D mean PQMs, the average P PQM reduction was 0.9% for SV = 0 and ⩽0.1% for SV ⩾ 2 mm. The effect of DV was larger for OARs that directly abutted a target volume than for those that did not. These trends were also observed with real DV from multi-observer delineations. The dosimetric impact of DV appeared to decrease when random and systematic SV was considered. Sensitivity to DV was affected by OAR objective type (i.e. D mean versus D max objectives) as well as distance from the target volume.

Time-optimized 4D phase contrast MRI with real-time convex optimization of gradient waveforms and fast excitation methods.

PURPOSE: To shorten 4D flow acquisitions by shortening TRs with fast RF pulses and gradient waveforms. Real-time convex optimization is used to generate these gradients waveforms on the scanner. THEORY AND METHODS: RF and slab-select waveforms were shortened with a minimum phase SLR excitation and the time-optimal variable-rate selective excitation method. Real-time convex optimization was used to shorten bipolar and spoiler gradients by finding the shortest gradient waveforms that satisfied constraints on scan parameters, gradient hardware, M0 , M1 , and peripheral nerve stimulation. Waveforms were calculated and TE and/or TR values were compared for a range of scan parameters and compared to a conventional 4D flow sequence. The method was tested in flow phantoms, and in the aorta and neurovasculature of volunteers (N = 10). Additionally, eddy current error was measured in a large phantom. RESULTS: TEs and TRs were shortened by 21-32% and 20-34%, respectively, compared to the conventional sequence over a range of scan parameters. Bland-Altman analysis of 2 flow phantom configurations showed flow rate bias of 0.3 mL/s and limits of agreement (LOA) of [-6.9, 7.5] mL/s for a cardiac phantom and a bias of -0.1 mL/s with LOA = [-0.4, 0.2] mL/s for a neuro phantom. Similar agreement was also seen for flow measurements in volunteers (bias = -1.0 and -0.1 mL/s, LOA = [-34.9, 33.0] and [-0.7, 0.6] mL/s). Measured eddy currents were 39% larger with the CVX + mpVERSE method. CONCLUSION: The real-time optimized 4D flow gradients and fast slab-selection excitation methods produced up to 34% faster TRs with excellent flow measurement agreement compared to a conventional 4D flow sequence.

Highly accelerated, model-free diffusion tensor MRI reconstruction using neural networks.

PURPOSE: The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans. MATERIALS AND METHODS: This retrospective study was conducted using data acquired between 2013 and 2018 and was approved by the local institutional review board. DTI acquired in healthy volunteers (N = 10) was used to train a neural network, DiffNet, to reconstruct fractional anisotropy (FA) and mean diffusivity (MD) maps from small subsets of acquired DTI data with between 3 and 20 diffusion-encoding directions. FA and MD maps were then reconstructed in volunteers and in patients with glioblastoma multiforme (GBM, N = 12) using both DiffNet and conventional reconstructions. Accuracy and precision were quantified in volunteer scans and compared between reconstructions. The accuracy of tumor delineation was compared between reconstructed patient data by evaluating agreement between DTI-derived tumor volumes and volumes defined by contrast-enhanced T1-weighted MRI. Comparisons were performed using areas under the receiver operating characteristic curves (AUC). RESULTS: DiffNet FA reconstructions were more accurate and precise compared with conventional reconstructions for all acceleration factors. DiffNet permitted reconstruction with only three diffusion-encoding directions with significantly lower bias than the conventional method using six directions (0.01 ± 0.01 vs 0.06 ± 0.01, P < 0.001). While MD-based tumor delineation was not substantially different with DiffNet (AUC range: 0.888-0.902), DiffNet FA had higher AUC than conventional reconstructions for fixed scan time and achieved similar performance with shorter scans (conventional, six directions: AUC = 0.926, DiffNet, three directions: AUC = 0.920). CONCLUSION: DiffNet improved DTI reconstruction accuracy, precision, and tumor delineation performance in GBM while permitting reconstruction from only three diffusion-encoding directions.&!#6.

Effect of flow-encoding strength on intravoxel incoherent motion in the liver.

PURPOSE: To study the impact of variable flow-encoding strength on intravoxel incoherent motion (IVIM) liver imaging of diffusion and perfusion. THEORY: Signal attenuation in DWI arises from (1) intravoxel microvascular blood flow, which depends on the flow-encoding strength α (first gradient moment) of the diffusion-encoding waveform, and (2) intravoxel spin diffusion, which depends on the b-value of the diffusion-encoding gradient waveforms α and b-value. Both are linked to the diffusion-encoding gradient waveform and conventionally are not independently controlled. METHODS: In this work a convex optimization framework was used to generate gradient waveforms with independent α and b-value. Thirty-six unique α and b-value sample points from 5 different gradient waveforms were used to reconstruct perfusion fraction (f), coefficient of diffusion (D), and blood velocity standard deviation (Vb ) maps using a recently proposed IVIM model. Faster acquisition strategies were evaluated with 1000 random subsampling strategies of 16, 8, and 4 α and b-value. Among the subsampled reconstructions, the sampling schemes that minimized the difference with the fully sampled reconstruction were reported. RESULTS: Healthy volunteers (N = 9) were imaged on a 3T scanner. Liver perfusion and diffusion estimates using the fully sampled IVIM method were f = 0.19 ± 0.06, D = 1.15 ± 0.15 × 10-3 mm2 /s, and Vb = 5.22 ± 3.86 mm/s. No statistical differences were found between the fully sampled and 2-times undersampled reconstruction (f = 0.2 ± 0.07, D = 1.19 ± 0.15 × 10-3 mm2 /s, Vb = 5.79 ± 3.43 mm/s); 4-times undersampled (f = 0.2 ± 0.06, D = 1.15 ± 0.17 × 10-3 mm2 /s, Vb = 4.66 ± 3.61 mm/s), or 8-times undersampled ( f = 0.2 ± 0.06, D = 1.23 ± 0.22 × 10-3 mm2 /s, Vb = 4.99 ± 3.82 mm/s) approaches. CONCLUSION: We demonstrate the IVIM signal's dependence on the b-value, the diffusion-encoding time and the flow-encoding strength and observe in vivo the ballistic regime signature of microperfusion in the liver. This work also demonstrates that using an IVIM model and sampling scheme matched to the ballistic regime, pixel-wise IVIM parameter maps are possible when sampling as few as 4 IVIM signals.

TIME RESOLVED DISPLACEMENT-BASED REGISTRATION OF IN VIVO CDTI CARDIOMYOCYTE ORIENTATIONS.

In vivo cardiac microstructure acquired using cardiac diffusion tensor imaging (cDTI) is a critical component of patient-specific models of cardiac electrophysiology and mechanics. In order to limit bulk motion artifacts and acquisition time, cDTI microstructural data is acquired at a single cardiac phase necessitating registration to the reference configuration on which the patient-specific computational models are based. Herein, we propose a method to register subject-specific microstructural data to an arbitrary cardiac phase using measured cardiac displacements. We validate our approach using a subject-specific computational phantom based on data from human subjects. Compared to a geometry-based non-rigid registration method, the displacement-based registration leads to improved accuracy (less than 1° versus 10° average median error in cardiomyocyte angular differences) and tighter confidence interval (3° versus 65° average upper limit of the 95% confidence interval).

Construction and Validation of Subject-Specific Biventricular Finite-Element Models of Healthy and Failing Swine Hearts From High-Resolution DT-MRI.

Predictive computational modeling has revolutionized classical engineering disciplines and is in the process of transforming cardiovascular research. This is particularly relevant for investigating emergent therapies for heart failure, which remains a leading cause of death globally. The creation of subject-specific biventricular computational cardiac models has been a long-term endeavor within the biomedical engineering community. Using high resolution (0.3 × 0.3 × 0.8 mm) ex vivo data, we constructed a precise fully subject-specific biventricular finite-element model of healthy and failing swine hearts. Each model includes fully subject-specific geometries, myofiber architecture and, in the case of the failing heart, fibrotic tissue distribution. Passive and active material properties are prescribed using hyperelastic strain energy functions that define a nearly incompressible, orthotropic material capable of contractile function. These materials were calibrated using a sophisticated multistep approach to match orthotropic tri-axial shear data as well as subject-specific hemodynamic ventricular targets for pressure and volume to ensure realistic cardiac function. Each mechanically beating heart is coupled with a lumped-parameter representation of the circulatory system, allowing for a closed-loop definition of cardiovascular flow. The circulatory model incorporates unidirectional fluid exchanges driven by pressure gradients of the model, which in turn are driven by the mechanically beating heart. This creates a computationally meaningful representation of the dynamic beating of the heart coupled with the circulatory system. Each model was calibrated using subject-specific experimental data and compared with independent in vivo strain data obtained from echocardiography. Our methods produced highly detailed representations of swine hearts that function mechanically in a remarkably similar manner to the in vivo subject-specific strains on a global and regional comparison. The degree of subject-specificity included in the models represents a milestone for modeling efforts that captures realism of the whole heart. This study establishes a foundation for future computational studies that can apply these validated methods to advance cardiac mechanics research.