Publications by authors named "Mark McDonald"

135 Publications

Improving the predictability of time to death in controlled donation after circulatory death lung donors.

Transpl Int 2021 Mar 16. Epub 2021 Mar 16.

Lung Transplant Service, The Alfred Hospital and Monash University, Melbourne, Vic., Australia.

Although the use of donation after circulatory death (DCD) donors has increased lung transplant activity, 25-40% of intended DCD donors do not convert to actual donation because of no progression to asystole in the required time frame after withdrawal of cardiorespiratory support (WCRS). No studies have specifically focussed on DCD lung donor progression. This retrospective study reviewed intended DCD lung donors to make a prediction model of the likelihood of progression to death using logistic regression and classification and regression tree (CART). Between 2014 and 2018, 159 of 334 referred DCD donors were accepted, with 100 progressing to transplant, while 59 (37%) did not progress. In logistic regression, a length of ICU stay ≤ 5 days, severe infra-tentorial brain damage on imaging and use of vasopressin were related with the progression to actual donation. CART modelling of the likelihood of death within 90-minute post-WCRS provided prediction with a sensitivity of 1.00 and positive predictive value of 0.56 in the validation data set. In the nonprogressed DCD group, 26 died within 6 h post-WCRS. Referral received early after ICU admission, with nonspontaneous ventilatory mode, deep coma and severe infra-tentorial damage were relevant predictors. The CART model is useful to exclude DCD donor candidates with low probability of progression.
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http://dx.doi.org/10.1111/tri.13862DOI Listing
March 2021

Learning-Based Stopping Power Mapping on Dual-Energy CT for Proton Radiation Therapy.

Int J Part Ther 2021 12;7(3):46-60. Epub 2021 Feb 12.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, USA.

Purpose: Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy.

Materials And Methods: The proposed method uses a residual attention cycle-consistent generative adversarial network to bring DECT-to-RSP mapping close to a 1-to-1 mapping by introducing an inverse RSP-to-DECT mapping. To evaluate the proposed method, we retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions and acted as learning targets in the training process for DECT datasets; they were evaluated against results from the proposed method using a leave-one-out cross-validation strategy.

Results: The predicted RSP maps showed an average normalized mean square error of 2.83% across the whole body volume and an average mean error less than 3% in all volumes of interest. With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences from ground truth in dose volume histogram metrics for clinical target volumes were less than 0.2 Gy for D and D with no statistical significance. Maximum difference in dose volume histogram metrics of organs at risk was around 1 Gy on average.

Conclusion: These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning-based method and show its potential feasibility for proton treatment planning and dose calculation.
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http://dx.doi.org/10.14338/IJPT-D-20-00020.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886267PMC
February 2021

Synthetic dual-energy CT for MRI-only based proton therapy treatment planning using label-GAN.

Phys Med Biol 2021 Mar 9;66(6):065014. Epub 2021 Mar 9.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, United States of America.

MRI-only treatment planning is highly desirable in the current proton radiation therapy workflow due to its appealing advantages such as bypassing MR-CT co-registration, avoiding x-ray CT exposure dose and reduced medical cost. However, MRI alone cannot provide stopping power ratio (SPR) information for dose calculations. Given that dual energy CT (DECT) can estimate SPR with higher accuracy than conventional single energy CT, we propose a deep learning-based method in this study to generate synthetic DECT (sDECT) from MRI to calculate SPR. Since the contrast difference between high-energy and low-energy CT (LECT) is important, and in order to accurately model this difference, we propose a novel label generative adversarial network-based model which can not only discriminate the realism of sDECT but also differentiate high-energy CT (HECT) and LECT from DECT. A cohort of 57 head-and-neck cancer patients with DECT and MRI pairs were used to validate the performance of the proposed framework. The results of sDECT and its derived SPR maps were compared with clinical DECT and the corresponding SPR, respectively. The mean absolute error for synthetic LECT and HECT were 79.98 ± 18.11 HU and 80.15 ± 16.27 HU, respectively. The corresponding SPR maps generated from sDECT showed a normalized mean absolute error as 5.22% ± 1.23%. By comparing with the traditional Cycle GANs, our proposed method significantly improves the accuracy of sDECT. The results indicate that on our dataset, the sDECT image form MRI is close to planning DECT, and thus shows promising potential for generating SPR maps for proton therapy.
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http://dx.doi.org/10.1088/1361-6560/abe736DOI Listing
March 2021

High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Biomed Phys Eng Express 2020 04 27;6(3):035029. Epub 2020 Apr 27.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, United States of America.

Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-view at native gantry angles. However, PPI has poor inherent contrast and spatial resolution. To deal with this issue, we propose a deep-learning-based method to use kV digitally reconstructed radiographs (DRR) to improve PPI image quality. Method; We used a residual generative adversarial network (GAN) framework to learn the nonlinear mapping between PPIs and DRRs. Residual blocks were used to force the model to focus on the structural differences between DRR and PPI. To assess the accuracy of our method, we used 149 images for training and 30 images for testing. PPIs were acquired using a double-scattered proton beam. The DRRs acquired from CT acted as learning targets in the training process and were used to evaluate results from the proposed method using a six-fold cross-validation scheme. Results; Qualitatively, the corrected PPIs showed enhanced spatial resolution and captured fine details present in the DRRs that are missed in the PPIs. The quantitative results for corrected PPIs show average normalized mean error (NME), normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index of -0.1%, 0.3%, 39.14 dB, and 0.987, respectively. Conclusion; The results indicate the proposed method can generate high quality corrected PPIs and this work shows the potential to use a deep-learning model to make PPI available in proton radiotherapy. This will allow for beam's-eye-view (BEV) imaging with the particle used for treatment, leading to a valuable alternative to orthogonal x-rays or cone-beam CT for patient position verification.
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http://dx.doi.org/10.1088/2057-1976/ab8a74DOI Listing
April 2020

Socioeconomic Factors Influence the Impact of Tumor HPV Status on Outcome of Patients With Oropharyngeal Squamous Cell Carcinoma.

JCO Oncol Pract 2021 Mar 12;17(3):e313-e322. Epub 2021 Jan 12.

Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA.

Purpose: Human papilloma virus (HPV) association remains one of the most important predictors of clinical outcome in oropharyngeal squamous cell carcinoma (OPSCC). We aimed to determine whether the relationship between HPV status and overall survival was influenced by socioeconomic factors.

Materials And Methods: Using the National Cancer Database, we examined the relationship between socioeconomic status and overall survival, controlling for demographics and socioeconomic variables (age at diagnosis, race, sex, clinical stage, facility type, facility location, insurance status, median-income quartiles, percent of no high-school education quartiles, rural-urban dwelling, Charlson-Deyo score, primary site, and treatment type).

Results: HPV-positive patients with private insurance have improved overall survival compared with HPV-positive patients who are uninsured (hazard ratio [HR], 0.51, 95% CI, 0.41 to 0.63, < .001). HPV-negative patients with private insurance have improved overall survival compared with HPV-negative patients who were uninsured (HR, 0.62, 95% CI, 0.53 to 0.73, < .001). HPV-positive patients living in the south had improved overall survival compared with HPV-positive patients living in the west (HR, 0.83, 95% CI, 0.72 to 0.96, = .013). As assessed through interaction, relationships between survival and insurance ( = .004), rural-urban status ( = .009), and facility location ( = .021) statistically differed between HPV-positive and HPV-negative patients.

Conclusion: HPV status impact on overall survival for patients with OPSCC is influenced by socioeconomic factors including insurance status and treatment facility. A deeper understanding of these interactions is needed to improve equity of care for patients with OPSCC.
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http://dx.doi.org/10.1200/OP.20.00671DOI Listing
March 2021

Head-and-neck organs-at-risk auto-delineation using dual pyramid networks for CBCT-guided adaptive radiotherapy.

Phys Med Biol 2021 Feb 11;66(4):045021. Epub 2021 Feb 11.

Department of Radiation Oncology, Emory University, Atlanta, GA, United States of America.

Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated approach aided by synthetic MRI for rapid and accurate CBCT multi-organ contouring in head-and-neck (HN) cancer patients. MRI has superb soft-tissue contrasts, while CBCT offers bony-structure contrasts. Using the complementary information provided by MRI and CBCT is expected to enable accurate multi-organ segmentation in HN cancer patients. In our proposed method, MR images are firstly synthesized using a pre-trained cycle-consistent generative adversarial network given CBCT. The features of CBCT and synthetic MRI (sMRI) are then extracted using dual pyramid networks for final delineation of organs. CBCT images and their corresponding manual contours were used as pairs to train and test the proposed model. Quantitative metrics including Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), mean surface distance, and residual mean square distance (RMS) were used to evaluate the proposed method. The proposed method was evaluated on a cohort of 65 HN cancer patients. CBCT images were collected from those patients who received proton therapy. Overall, DSC values of 0.87 ± 0.03, 0.79 ± 0.10/0.79 ± 0.11, 0.89 ± 0.08/0.89 ± 0.07, 0.90 ± 0.08, 0.75 ± 0.06/0.77 ± 0.06, 0.86 ± 0.13, 0.66 ± 0.14, 0.78 ± 0.05/0.77 ± 0.04, 0.96 ± 0.04, 0.89 ± 0.04/0.89 ± 0.04, 0.83 ± 0.02, and 0.84 ± 0.07 for commonly used OARs for treatment planning including brain stem, left/right cochlea, left/right eye, larynx, left/right lens, mandible, optic chiasm, left/right optic nerve, oral cavity, left/right parotid, pharynx, and spinal cord, respectively, were achieved. This study provides a rapid and accurate OAR auto-delineation approach, which can be used for adaptive radiation therapy.
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http://dx.doi.org/10.1088/1361-6560/abd953DOI Listing
February 2021

Video-based Facial Weakness Analysis.

IEEE Trans Biomed Eng 2021 Jan 6;PP. Epub 2021 Jan 6.

Objective: Facial weakness is a common sign of neurological diseases such as Bell's palsy and stroke. However, recognizing facial weakness still remains as a challenge, because it requires experience and neurological training.

Methods: We propose a framework for facial weakness detection, which models the temporal dynamics of both shape and appearance-based features of each target frame through a bi-directional long short-term memory network (Bi-LSTM). The system is evaluated on a in-the-wild video dataset that is verified by three board-certified neurologists. In addition, three emergency medical services (EMS) personnel and three upper level residents rated the dataset. We compare the evaluation of the proposed algorithm with other comparison methods as well as the human raters.

Results: Experimental evaluation demonstrates that: (1) the proposed algorithm achieves the accuracy, sensitivity, and specificity of 94.3%, 91.4%, and 95.7%, which outperforms other comparison methods and achieves the equal performance to paramedics; (2) the framework can provide visualizable and interpretable results that increases model transparency and interpretability; (3) a prototype is implemented as a proof-of-concept showcase to show the feasibility of an inexpensive solution for facial weakness detection.

Conclusion: The experiment results suggest that the proposed framework can identify facial weakness effectively.

Significance: We provide a proof-of-concept study, showing that such technology could be used by non-neurologists to more readily identify facial weakness in the field, leading to increasing coverage and earlier treatment.
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http://dx.doi.org/10.1109/TBME.2021.3049739DOI Listing
January 2021

A retrospective review of declined lung donors: estimating the potential of ex-vivo lung perfusion.

Ann Thorac Surg 2020 Oct 26. Epub 2020 Oct 26.

Lung Transplant Service, The Alfred Hospital and Monash University, Melbourne, Australia.

Background: Even in the extended-criteria era, the reasons for declining lung donors are not always clear. Furthermore, it has not been determined how many actual declined lungs would be retrieved by ex-vivo lung perfusion (EVLP) beyond that already achieved in centers with an existing high utilization rate.

Methods: This retrospective study reviewed all lung donor referrals between 2014-2018, including detailed formal referrals and preliminary notifications. This study categorized reasons for lung donor non-acceptance and estimated how many declined grafts could have been theoretically retrievable by using EVLP.

Results: In total, 966 lung donor candidates were referred, including 313 transplanted donors, 336 declined donors after detailed referrals (Group A) and 258 preliminary declined. In the Group A, the primary reasons for refusal were lung quality issues (49%), general medical issues (25%), and organization issues (26%), combined with secondary reasons in many cases. Main lung quality issues were an extensive smoking history, abnormal chest radiography and underlying lung disease. Although 73 declined lung donors had indications for EVLP, the retrievable lungs decreased to only 30 cases after considering the details of all clinical contraindications and organizational issues. However, 59 intended donation after circulatory death donors did not progress to death after withdrawal of cardiorespiratory support in the required timeframe, and EVLP may have an emerging additional role here.

Conclusions: Based on commonly cited criteria for EVLP indication, the number of EVLP retrievable lung donors represented only a small portion of declined donor lungs referred to our center from the state donation network.
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http://dx.doi.org/10.1016/j.athoracsur.2020.08.042DOI Listing
October 2020

Significant impact of COVID-19 on organ donation and transplantation in a low-prevalence country: Australia.

Kidney Int 2020 12 21;98(6):1616-1618. Epub 2020 Oct 21.

Transplantation Society of Australia and New Zealand, Sydney, Australia; Department of Renal Medicine, Royal Adelaide Hospital, Adelaide, Australia.

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http://dx.doi.org/10.1016/j.kint.2020.10.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575441PMC
December 2020

Overall Survival After Treatment of Localized Prostate Cancer With Proton Beam Therapy, External-Beam Photon Therapy, or Brachytherapy.

Clin Genitourin Cancer 2020 Aug 28. Epub 2020 Aug 28.

Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA. Electronic address:

Background: There are few comparative outcomes data regarding the therapeutic delivery of proton beam therapy (PBT) versus the more widely used photon-based external-beam radiation (EBRT) and brachytherapy (BT). We evaluated the impact of PBT on overall survival (OS) compared to EBRT or BT on patients with localized prostate cancer.

Patients And Methods: The National Cancer Data Base (NCDB) was queried for 2004-2015. Men with clinical stage T1-3, N0, M0 prostate cancer treated with radiation, without surgery or chemotherapy, were included. OS, the primary clinical outcome, was fit by Cox proportional hazard model. Propensity score matching was implemented for covariate balance.

Results: There were 276,880 eligible patients with a median follow-up of 80.9 months. A total of 4900 (1.8%) received PBT, while 158,111 (57.1%) received EBRT and 113,869 (41.1%) BT. Compared to EBRT and BT, PBT patients were younger and were less likely to be in the high-risk group. On multivariable analysis, compared to PBT, men had worse OS after EBRT (adjusted hazard ratio [HR] = 1.72; 95% confidence interval [CI], 1.51-1.96) or BT (adjusted HR = 1.38; 95% CI, 1.21-1.58). After propensity score matching, the OS benefit of PBT remained significant compared to EBRT (HR = 1.64; 95% CI, 1.32-2.04) but not BT (adjusted HR = 1.18; 95% CI, 0.93-1.48). The improvement in OS with PBT was most prominent in men ≤ 65 years old with low-risk disease compared to other subgroups (interaction P < .001).

Conclusion: In this national data set, PBT was associated with a significant OS benefit compared to EBRT, and with outcomes similar to BT. These results remain to be validated by ongoing prospective trials.
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http://dx.doi.org/10.1016/j.clgc.2020.08.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914293PMC
August 2020

Common Criteria for Ex Vivo Lung Perfusion Have No Significant Impact on Posttransplant Outcomes.

Ann Thorac Surg 2021 04 2;111(4):1156-1163. Epub 2020 Sep 2.

Lung Transplant Service, Alfred Hospital, Melbourne, Australia.

Background: Although it is intense in health care resources, by facilitating assessment and reconditioning, ex vivo lung perfusion (EVLP) has the potential to expand the donor pool and improve lung transplant outcomes. However, inclusion criteria used in EVLP trials have not been validated.

Methods: This retrospective study from 2014 to 2018 reviewed our local state-based donation organization donor records as well as subsequent recipient outcomes to explore the relation between EVLP indications used in clinical trials and recipient outcomes. The primary outcome was primary graft dysfunction grade 3 at 24 hours, with 30-day mortality and posttransplant survival time as secondary outcomes, compared with univariate and multivariate analysis.

Results: From 705 lung donor referrals, 304 lung transplantations were performed (use rate of 42%); 212 of recipients (70%) met at least 1 of the commonly cited EVLP initiation criteria. There was no significant difference in primary graft dysfunction grade 3 or 30-day mortality between recipients with or without an EVLP indication (10.2% versus 7.8%, P = .51; and 2.4% versus 0%, P = .14, respectively). Multivariate analyses showed no significant relationship between commonly cited EVLP criteria and primary graft dysfunction grade 3 or survival time. Recipient outcomes were significantly associated with recipient diagnosis.

Conclusions: At least 1 commonly cited criterion for EVLP initiation was present in 70% of the transplanted donors, and yet it did not predict clinical results; acceptable outcomes were seen in both subgroups. To discover the true utility of EVLP beyond good clinical management and focus EVLP on otherwise unacceptable lungs, a reconsideration of EVLP inclusion criteria is required.
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http://dx.doi.org/10.1016/j.athoracsur.2020.06.081DOI Listing
April 2021

Inflammatory Manifestations of Systemic Diseases in the Central Nervous System.

Curr Treat Options Neurol 2020 29;22(9):26. Epub 2020 Jul 29.

Division of Neuroimmunology, Department of Neurology, University of Virginia, 1222 Lee Street, Charlottesville, VA 22908 USA.

Purpose Of Review: This review presents the current recommended therapeutic interventions for inflammatory disease in the central nervous system (CNS) secondary to systemic diseases of immune dysregulation. Treatment recommendations for CNS inflammation associated with rheumatologic conditions, immune-related adverse effects from immune checkpoint inhibitors (ICIs), and demyelinating disease from tumor necrosis factor-α (anti-TNFs) are explored. Additional therapeutic options for inflammation related to postviral syndromes and genetic immunodeficiencies are also discussed.

Recent Findings: In addition to treatment of mild, moderate, and severe CNS rheumatologic disease as guided by the European League Against Rheumatism (EULAR), early consideration of rituximab for severe IgG4-related disease and induction with anti-TNF therapy for severe neurosarcoidosis should be considered. Although often not first line, treatment options for CNS inflammatory diseases based on disease mechanism are emerging, including tocilizumab for Behcet's disease, natalizumab for ICI associated autoimmune encephalitis, and abatacept for treatment of infiltrative disease secondary to CTLA-4 deficiency. Hematopoietic stem cell treatments represent highly efficacious but risky options for autoimmunity related to genetic immunodeficiency.

Summary: While early high dose steroids remains first line therapy for most CNS inflammatory conditions, a rapidly expanding arsenal of immune targeted therapies offers clinicians tailored disease specific options for treatment.
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http://dx.doi.org/10.1007/s11940-020-00636-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387810PMC
July 2020

Head and neck multi-organ auto-segmentation on CT images aided by synthetic MRI.

Med Phys 2020 Sep 2;47(9):4294-4302. Epub 2020 Aug 2.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA.

Purpose: Because the manual contouring process is labor-intensive and time-consuming, segmentation of organs-at-risk (OARs) is a weak link in radiotherapy treatment planning process. Our goal was to develop a synthetic MR (sMR)-aided dual pyramid network (DPN) for rapid and accurate head and neck multi-organ segmentation in order to expedite the treatment planning process.

Methods: Forty-five patients' CT, MR, and manual contours pairs were included as our training dataset. Nineteen OARs were target organs to be segmented. The proposed sMR-aided DPN method featured a deep attention strategy to effectively segment multiple organs. The performance of sMR-aided DPN method was evaluated using five metrics, including Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), mean surface distance (MSD), residual mean square distance (RMSD), and volume difference. Our method was further validated using the 2015 head and neck challenge data.

Results: The contours generated by the proposed method closely resemble the ground truth manual contours, as evidenced by encouraging quantitative results in terms of DSC using the 2015 head and neck challenge data. Mean DSC values of 0.91 ± 0.02, 0.73 ± 0.11, 0.96 ± 0.01, 0.78 ± 0.09/0.78 ± 0.11, 0.88 ± 0.04/0.88 ± 0.06 and 0.86 ± 0.08/0.85 ± 0.1 were achieved for brain stem, chiasm, mandible, left/right optic nerve, left/right parotid, and left/right submandibular, respectively.

Conclusions: We demonstrated the feasibility of sMR-aided DPN for head and neck multi-organ delineation on CT images. Our method has shown superiority over the other methods on the 2015 head and neck challenge data results. The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs.
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http://dx.doi.org/10.1002/mp.14378DOI Listing
September 2020

Technical Note: Plan-delivery-time constrained inverse optimization method with minimum-MU-per-energy-layer (MMPEL) for efficient pencil beam scanning proton therapy.

Med Phys 2020 Sep 28;47(9):3892-3897. Epub 2020 Jul 28.

Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, USA.

Purpose: This work aims to reduce dose delivery time of pencil beam scanning (PBS) proton plans, which is the dominant factor of total plan delivery time. A proton PBS system, such as Varian ProBeam proton therapy system, can be equipped with the proton dose rate that is linearly proportional to the minimum monitor unit (MU) (i.e., number of protons) of PBS spots before saturation. Thus dose delivery time can be potentially reduced by increasing the MU threshold. However, commercially available treatment planning systems and current methods only allow for a single MU threshold globally for all PBS spots (i.e., all energy layers), and consequently the room to increase this minimum-MU for reducing dose delivery time is very limited since higher minimum-MU can greatly degrade treatment plan quality.

Methods: Two major innovations of this work are the proposal of using variable MU thresholds locally adaptive to each energy layer, that is, minimum-MU-per-energy-layer (MMPEL), for reducing dose delivery time, and the joint optimization of plan delivery time and plan quality. Minimum-MU-per-energy-layer is formulated as a constrained optimization problem with objectives of dose-volume-histogram based planning constraints and plan delivery time, and minimum-MU constraints per energy layer for deliverable PBS spots. Minimum-MU-per-energy-layer is solved by iterative convex relaxations via alternating direction method of multipliers.

Results: Representative prostate, lung, brain, head-and-neck, breast, liver and pancreas cases were used to validate MMPEL. Minimum-MU-per-energy-layer reduced dose delivery time to 53%, 67%, 67%, 53%, 54%, 32%, and 14% respectively while maintaining a similar plan quality. Accepting a slightly degraded plan quality that still met all physician planning constraints, the treatment time could be further reduced to 26%, 35%, 41%, 34%, 32%, 16%, and 11% respectively, or in another word MMPEL accelerated the PBS plan delivery by 2-10 fold.

Conclusions: A new proton PBS treatment planning method MMPEL with variable energy-adaptive MU thresholds is developed to optimize dose delivery time jointly with plan quality. The preliminary results suggest that MMPEL could substantially reduce dose delivery time.
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http://dx.doi.org/10.1002/mp.14363DOI Listing
September 2020

Influence of the donor history of tobacco and marijuana smoking on early and intermediate lung transplant outcomes.

J Heart Lung Transplant 2020 09 11;39(9):962-969. Epub 2020 Jun 11.

Lung Transplant Service, The Alfred Hospital and Monash University, Melbourne, Victoria, Australia.

Background: Donor smoking histories are common in the lung donor pool, which are known to adversely affect post-lung transplant (LTx) outcomes. However, no evidence is available about smoking status (current/former), cumulative dose effect, or the combined effect of tobacco with marijuana.

Methods: We retrospectively reviewed our local state-based donation organization records and subsequent LTx recipient outcomes. The primary outcome was 3-year graft survival, with cause of death as secondary outcomes. Univariate and multivariate Cox regression analyses were used to explore smoking status or cumulative dose effect.

Results: Between 2014 and 2018, 304 LTxs were performed: 133 (44%) LTxs were from never-smoker donors, 68 (22%) from former-smoker donors, and 103 (34%) from current-smoker donors. Of the current-smoker donors, 48% had a marijuana use history. There was no significant difference in early mortality, although recipients who received transplants from current-smoker donors had a lower 3-year graft survival than those who received transplants from never smokers. Multivariate modeling showed that current tobacco smoking (hazard ratio: 2.13, 95% CI: 1.13-3.99) and a more than 5-year weekly marijuana use (hazard ratio: 2.97, 95% CI: 1.29-6.87) were independent donor factors affecting graft survival. Chronic lung allograft dysfunction accounted for a higher proportion of the causes of death within 3 years after LTx where lungs from current/former smokers were utilized compared with those from never smokers (chronic lung allograft dysfunction-cause mortality: 11%, 7%, 0%, respectively).

Conclusions: More than 50% of LTx donors had smoking histories. Current tobacco use or more than 5-year weekly marijuana smoking history adversely affected 3-year graft survival. Our findings support the importance of obtaining a detailed donor tobacco and marijuana smoking history.
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http://dx.doi.org/10.1016/j.healun.2020.05.019DOI Listing
September 2020

Cone-beam CT-derived relative stopping power map generation via deep learning for proton radiotherapy.

Med Phys 2020 Sep 27;47(9):4416-4427. Epub 2020 Jul 27.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA.

Purpose: In intensity-modulated proton therapy (IMPT), protons are used to deliver highly conformal dose distributions, targeting tumors, and sparing organs-at-risk. However, due to uncertainties in both patient setup and relative stopping power (RSP) calculation, margins are added to the treatment volume during treatment planning, leading to higher doses to normal tissues. Cone-beam computed tomography (CBCT) images are taken daily before treatment; however, the poor image quality of CBCT limits the use of these images for online dose calculation. In this work, we use a deep-learning-based method to predict RSP maps from daily CBCT images, allowing for online dose calculation in a step toward adaptive radiation therapy.

Methods: Twenty-three head-and-neck cancer patients were simulated using a Siemens TwinBeam dual-energy CT (DECT) scanner. Mixed-energy scans (equivalent to a 120 kVp single-energy CT scan) were converted to RSP maps for treatment planning. Cone-beam computed tomography images were taken on the first day of treatment, and the planning RSP maps were registered to these images. A deep learning network based on a cycle-GAN architecture, relying on a compound loss function designed for structural and contrast preservation, was then trained to create an RSP map from a CBCT image. Leave-one-out and holdout cross validations were used for evaluation, and mean absolute error (MAE), mean error (ME), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used to quantify the differences between the CT-based and CBCT-based RSP maps. The proposed method was compared to a deformable image registration-based method which was taken as the ground truth and two other deep learning methods. For one patient who underwent resimulation, the new planning RSP maps and CBCT images were used for further evaluation and validation.

Results: The CBCT-based RSP generation method was evaluated on 23 head-and-neck cancer patients. From leave-one-out testing, the MAE between CT-based and CBCT-based RSP was 0.06 ± 0.01 and the ME was -0.01 ± 0.01. The proposed method statistically outperformed the comparison DL methods in terms of MAE and ME when compared to the planning CT. In terms of dose comparison, the mean gamma passing rate at 3%/3 mm was 94% when three-dimensional (3D) gamma index was calculated per plan and 96% when gamma index was calculated per field.

Conclusions: The proposed method provides sufficiently accurate RSP map generation from CBCT images, allowing for evaluation of daily dose based on CBCT and possibly allowing for CBCT-guided adaptive treatment planning for IMPT.
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http://dx.doi.org/10.1002/mp.14347DOI Listing
September 2020

Acute Neurological Care in the COVID-19 Era: The Pandemic Health System silience () Consortium Pathway.

Front Neurol 2020 29;11:579. Epub 2020 May 29.

Pandemic Health System REsilience PROGRAM (REPROGRAM) Consortium, REPROGRAM Acute Care Sub-committee†, Sydney, NSW, Australia.

The management of acute neurological conditions, particularly acute ischemic stroke, in the context of Coronavirus disease 2019 (COVID-19), is of importance, considering the risk of infection to the healthcare workers and patients and emerging evidence of the neuroinvasive potential of the virus. There are variations in expert guidelines further complicating the picture for clinicians in acute settings. In this light, there is a compelling need for further formulation of recommendations that compile these variations seen in the numerous guidelines present. Health system protocols for managing ongoing acute neurological care and intervention need consideration of safety and well-being of the frontline healthcare workers and the patients. We examine existing pathways and their efficacy to mitigate viral exposure to the healthcare workers and patients and synthesize a systemic approach to manage patients with acute neurological conditions in the COVID-19 scenario. Early experiences with a COVID-19 positive stroke patient treated with endovascular thrombectomy is presented to highlight the urgent need for adequate personal protective equipment (PPE) during acute neuro-interventional procedures.
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http://dx.doi.org/10.3389/fneur.2020.00579DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273748PMC
May 2020

Radiation as a Single-Modality Treatment in Localized Pancreatic Cancer.

Pancreas 2020 07;49(6):822-829

From the Department of Hematology and Oncology, Winship Cancer Institute.

Objectives: Locally advanced pancreatic cancer (LAPC) is managed with multimodality therapy. We aim to evaluate the outcome of single-modality radiation therapy for LAPC.

Methods: Locally advanced pancreatic cancer patients were identified between 2004 and 2013 using the National Cancer Database excluding patients who received chemotherapy or surgery.

Results: A total of 6590 patients were included. The mean age was 73.5 (range, 28-90) years, 83.2% were white, and 54.4% were female. Tumors of 4 cm or greater (>T3 stage) accounted for 52.7%. The median radiation dose was 39.6 Gy. Stereotactic body radiation (SBRT) delivered to 64 patients and external-beam/intensity modulated radiotherapy in 416 patients. Radiation therapy was associated with improved overall survival (OS) compared with no treatment in univariate and multivariable analyses. The medians OS for patients who received SBRT, external-beam/intensity modulated radiotherapy, or no radiation were 8.6, 6.7, and 3.4 months, respectively (P < 0.001). There is a significant difference in 12-month OS for the SBRT cohort (31.9%; 95% confidence interval [CI], 20.9%-43.5%) compared with patients who received no radiation (15.1%; 95% CI, 14.2%-16.0%), and on multivariable analysis (hazard ratio, 0.50; 95% CI, 0.38-0.65; P < 0.001).

Conclusions: The current study suggests potential benefit for radiation therapy alone in comparison with no treatment in LAPC.
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http://dx.doi.org/10.1097/MPA.0000000000001584DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8011591PMC
July 2020

Outcomes and Predictive Value of Post-adjuvant Therapy PET/CT for Locally Advanced Oral Squamous Cell Carcinoma.

Laryngoscope 2020 12 14;130(12):E850-E857. Epub 2020 Feb 14.

Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, Georgia, USA.

Objectives/hypothesis: For locally advanced oral squamous cell carcinoma (OSCC) treated by surgery and adjuvant therapy, consensus has yet to be reached on whether the optimal time to initiate surveillance positron emission tomography/computed tomography (PET/CT) scan is before or after adjuvant therapy. In this study, we characterize the utility of PET/CT scans obtained 3 months after adjuvant therapy.

Study Design: PET/CT scans were obtained for 220 patients with stage III, IVA, or IVB OSCC who underwent resection followed by adjuvant radiotherapy or chemoradiotherapy.

Methods: Using the Neck Imaging Reporting and Data System, PET/CT scans were dichotomized as suspicious (primary or neck category ≥3, or distant lesion present) versus nonsuspicious. We then computed differences in locoregional progression, distant progression, and overall survival; positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity; and success rate of salvage.

Results: Sixty-seven patients (30%) had suspicious PET/CT scans, which were significantly associated with local failure (hazard ratio [HR] 14.0, 95% confidence interval [CI] 7.3-26.6), distant failure (HR 18.4, 95% CI 9.6-35.3), and poorer overall survival (HR 9.5, 95% CI 5.0-17.9). Overall PPV, locoregional PPV, NPV, sensitivity, and specificity were 85%, 79%, 73%, 58%, and 92%, respectively. Among those with biopsy-confirmed progression, 37 patients (65%) underwent salvage therapy; four (11%) were without evidence of disease at last follow-up.

Conclusions: For locally advanced OSCC, PET/CT scan 3 months after adjuvant therapy is strongly predictive of disease recurrence and survival, demonstrating improved performance over postoperative imaging in previous studies. Following a suspicious post-adjuvant therapy PET/CT scan, cure of locoregional recurrence is possible but unlikely.

Level Of Evidence: 4 Laryngoscope, 2020.
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http://dx.doi.org/10.1002/lary.28509DOI Listing
December 2020

Demographic and Socioeconomic Factors Associated With Metastases at Presentation in HPV-Related Squamous Cell Carcinoma of the Head and Neck: An NCDB Analysis.

JCO Oncol Pract 2020 06 27;16(6):e476-e487. Epub 2020 Jan 27.

Department of Hematology and Medical Oncology, Emory University, Atlanta, GA.

Purpose: Human papillomavirus (HPV)-related squamous cell carcinomas of the head and neck (SCCHNs) tend to have a distinct prognosis. Socioeconomic and demographic factors associated with metastatic disease at presentation and diagnosis in patients with HPV-related SCCHN tumors were examined.

Methods: The National Cancer Database (NCDB) was queried to assess patients with HPV-related oropharyngeal carcinomas (HPVOPCAs) and HPV-related nonoropharyngeal carcinomas (HPVNOPCAs) diagnosed between 2010 and 2014. Rate of metastases at presentation was analyzed using clinical M stage. Multivariable analysis was performed evaluating race, ethnicity, sex, age, facility location, facility type, insurance status, income, education, and tumor and nodal stage using logistic regression.

Results: A total of 12,857 patients with HPVOPCA and 952 patients with HPVNOPCA were included. Private insurance was carried by 64% and 47% of patients with HPVOPCA and HPVNOPCA, respectively. HPVOPCA was located in the tonsil in 56% of patients. For both HPVOPCA and HPVNOPCA, there was no meaningful difference in distant metastasis at presentation based on facility type or location, sex, race, Hispanic ethnicity, or urban or rural location. For HPVOPCA, there were significantly lower odds of metastasis in privately insured patients compared with uninsured patients (odds ratio [OR], 0.37; 95% CI, 0.21 to 0.64; < .001) and higher odds of metastasis for patients living in census tracts with the lowest rates of high school graduates compared with the highest rates (OR, 1.81; 95% CI, 1.02 to 3.19; = .041) and for patients with higher tumor stage (OR, 3.67, 95% CI, 2.25 to 5.99; < .001) and nodal stage (OR, 3.34; 95% CI, 2.11 to 5.29; < .001). For HPVNOPCA, neither higher T or N stage nor any demographic features were found to be associated with metastasis at presentation.

Conclusion: This large retrospective analysis identifies likely modifiable risk factors for metastatic presentation in HPVOPCA. Educational interventions may result in modifications of these patterns.
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http://dx.doi.org/10.1200/JOP.19.00400DOI Listing
June 2020

MRI-Based Proton Treatment Planning for Base of Skull Tumors.

Int J Part Ther 2019 30;6(2):12-25. Epub 2019 Sep 30.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA.

Purpose: To introduce a novel, deep-learning method to generate synthetic computed tomography (SCT) scans for proton treatment planning and evaluate its efficacy.

Materials And Methods: 50 Patients with base of skull tumors were divided into 2 nonoverlapping training and study cohorts. Computed tomography and magnetic resonance imaging pairs for patients in the training cohort were used for training our novel 3-dimensional generative adversarial network (cycleGAN) algorithm. Upon completion of the training phase, SCT scans for patients in the study cohort were predicted based on their magnetic resonance images only. The SCT scans obtained were compared against the corresponding original planning computed tomography scans as the ground truth, and mean absolute errors (in Hounsfield units [HU]) and normalized cross-correlations were calculated. Proton plans of 45 Gy in 25 fractions with 2 beams per plan were generated for the patients based on their planning computed tomographies and recalculated on SCT scans. Dose-volume histogram endpoints were compared. A γ-index analysis along 3 cardinal planes intercepting at the isocenter was performed. Proton distal range along each beam was calculated.

Results: Image quality metrics show agreement between the generated SCT scans and the ground truth with mean absolute error values ranging from 38.65 to 65.12 HU and an average of 54.55 ± 6.81 HU and a normalized cross-correlation average of 0.96 ± 0.01. The dosimetric evaluation showed no statistically significant differences ( > 0.05) within planning target volumes for dose-volume histogram endpoints and other metrics studied, with the exception of the dose covering 95% of the target volume, with a relative difference of 0.47%. The γ-index analysis showed an average passing rate of 98% with a 10% threshold and 2% and 2-mm criteria. Proton ranges of 48 of 50 beams (96%) in this study were within clinical tolerance adopted by 4 institutions.

Conclusions: This study shows our method is capable of generating SCT scans with acceptable image quality, dose distribution agreement, and proton distal range compared with the ground truth. Our results set a promising approach for magnetic resonance imaging-based proton treatment planning.
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http://dx.doi.org/10.14338/IJPT-19-00062.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6986397PMC
September 2019

A standardized commissioning framework of Monte Carlo dose calculation algorithms for proton pencil beam scanning treatment planning systems.

Med Phys 2020 Apr 4;47(4):1545-1557. Epub 2020 Feb 4.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA.

Purpose: Treatment planning systems (TPSs) from different vendors can involve different implementations of Monte Carlo dose calculation (MCDC) algorithms for pencil beam scanning (PBS) proton therapy. There are currently no guidelines for validating non-water materials in TPSs. Furthermore, PBS-specific parameters can vary by 1-2 orders of magnitude among different treatment delivery systems (TDSs). This paper proposes a standardized framework on the use of commissioning data and steps to validate TDS-specific parameters and TPS-specific heterogeneity modeling to potentially reduce these uncertainties.

Methods: A standardized commissioning framework was developed to commission the MCDC algorithms of RayStation 8A and Eclipse AcurosPT v13.7.20 using water and non-water materials. Measurements included Bragg peak depth-dose and lateral spot profiles and scanning field outputs for Varian ProBeam. The phase-space parameters were obtained from in-air measurements and the number of protons per MU from output measurements of 10 × 10 cm square fields at a 2 cm depth. Spot profiles and various PBS field measurements at additional depths were used to validate TPS. Human tissues in TPS, Gammex phantom materials, and artificial materials were used for the TPS benchmark and validation.

Results: The maximum differences of phase parameters, spot sigma, and divergence between MCDC algorithms are below 4.5 µm and 0.26 mrad in air, respectively. Comparing TPS to measurements at depths, both MC algorithms predict the spot sigma within 0.5 mm uncertainty intervals, the resolution of the measurement device. Beam Configuration in AcurosPT is found to underestimate number of protons per MU by ~2.5% and requires user adjustment to match measured data, while RayStation is within 1% of measurements using Auto model. A solid water phantom was used to validate the range accuracy of non-water materials within 1% in AcurosPT.

Conclusions: The proposed standardized commissioning framework can detect potential issues during PBS TPS MCDC commissioning processes, and potentially can shorten commissioning time and improve dosimetric accuracies. Secondary MCDC can be used to identify the root sources of disagreement between primary MCDC and measurement.
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http://dx.doi.org/10.1002/mp.14021DOI Listing
April 2020

Facial Weakness Analysis and Quantification of Static Images.

IEEE J Biomed Health Inform 2020 08 7;24(8):2260-2267. Epub 2020 Jan 7.

Facial weakness is a symptom commonly associated to lack of facial muscle control due to neurological injury. Several diseases are associated with facial weakness such as stroke and Bell's palsy. The use of digital imaging through mobile phones, tablets, personal computers and other devices could provide timely opportunity for detection, which if accurate enough can improve treatment by enabling faster patient triage and recovery progress monitoring. Most of the existing facial weakness detection approaches from static images are based on facial landmarks from which geometric features can be calculated. Landmark-based methods, however, can suffer from inaccuracies in face landmarks localization. In this study, We also experimentally evaluate the performance of several feature extraction methods for measuring facial weakness, including the landmark-based features, as well as intensity-based features on a neurologist-certified dataset that comprises 186 images of normal, 125 images of left facial weakness, and 126 images of right facial weakness. We demonstrate that, for the application of facial weakness detection from single (static) images, approaches that incorporate the Histogram of Oriented Gradients (HoG) features tend to be more accurate.
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http://dx.doi.org/10.1109/JBHI.2020.2964520DOI Listing
August 2020

Cocaine Use is Associated with More Rapid Clot Formation and Weaker Clot Strength in Acute Stroke Patients.

Int J Cerebrovasc Dis Stroke 2019 18;2(1). Epub 2019 Jan 18.

Departments of Neurosurgery and Neurology, University of Texas Medical School at Houston, Texas, USA.

Introduction: 1.1.Cocaine use is a known risk factor for stroke and has been associated with worse outcomes. Cocaine may cause an altered coagulable state by a number of different proposed mechanisms, including platelet activation, endothelial injury, and tissue factor expression. This study analyzes the effect of cocaine use on Thrombelastography (TEG) in acute stroke patients.

Patient And Methods: 1.2.Patients presenting with Acute Ischemic Stroke (AIS) and spontaneous Intracerebral Hemorrhage (ICH) to a single academic center between 2009 and 2014 were prospectively enrolled. Blood was collected for TEG analysis at the time of presentation. Patient demographics and baseline TEG values were compared between two groups: cocaine and non-cocaine users. Multivariable Quantile regression models were used to compare the median TEG components between groups after controlling for the effect of confounders.

Results: 1.3.91 patients were included, 53 with AIS and 38 with ICH. 8 (8.8%) patients were positive for cocaine, 4 (50%) with AIS, and 4 (50%) with ICH. There were no significant differences in age, blood pressure, platelet count, or PT/PTT between the cocaine positive and cocaine negative group. Following multivariable analysis, and adjusting for factors known to influence TEG including stroke subtype, cocaine use was associated with shortened median R time (time to initiate clotting) of 3.8 minutes compared to 4.8 minutes in non-cocaine users (p=0.04). Delta (thrombin burst) was also earlier among cocaine users (0.4 minutes) compared with non-cocaine users (0.5 min, p=0.04). The median MA and G (measurements of final clot strength) were reduced in cocaine users (MA=62.5 mm, G=7.8 dynes/cm2) compared to non-cocaine users (MA=66.5 mm, G=10.1 dynes/cm2; p=0.047, p=0.04, respectively).

Conclusion: 1.4.Cocaine users demonstrate more rapid clot formation but reduced overall clot strength based on admission TEG values.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824539PMC
January 2019

Standardized Implementation of Evidence-based Guidelines to Decrease Blood Transfusions in Pediatric Intensive Care Units.

Pediatr Qual Saf 2019 May-Jun;4(3):e165. Epub 2019 Apr 9.

Division of Pediatric Critical Care, Norton Children's Hospital /University of Louisville School of Medicine Louisville, KY.

Introduction: Despite evidence that red blood cell (RBC) transfusions may be associated with more harm than benefit, current transfusion practices vary significantly. This multicenter, quality improvement study aimed to sustainably decrease the rate of RBC transfusions in pediatric intensive care units (PICUs).

Methods: This 16-month prospective study included 5 PICUs. We implemented a standardized project plan including education, bedside tools, real-time reminders, and email feedback. We collected data from consecutive transfusions during pre-implementation (Phase I), postimplementation (Phase II), and post-stabilization phases (Phase III).

Results: Of the 2,064 RBC transfusions, we excluded 35% (N = 729) from analysis in patients undergoing extracorporeal membrane oxygenation. Transfusion/1,000 admissions improved throughout the study periods from a baseline 209.6 -199.8 in Phase II and 195.8 in Phase III ( value < 0.05). There were fewer transfusions outside of the hemoglobin threshold guideline, decreasing from 81% of transfusions outside of guidelines in Phase I to 74% in Phases II and III, < 0.05. Study phase, site, co-management status, service of requesting provider, admit reason, previous transfusion status, and age were associated with transfusion above guideline threshold.

Conclusions: Multicenter collaboration can successfully deploy a standardized plan that adheres to implementation science principles to sustainably decrease the rate of RBC transfusion outside of guideline thresholds. However, we did not decrease the total number of transfusions in our study. The complexity of multiple specialties co-managing patients is common in the contemporary PICU. Educational initiatives aimed at one specialty may have limited effectiveness in a multifaceted system of care.
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http://dx.doi.org/10.1097/pq9.0000000000000165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594784PMC
April 2019

Survival outcomes in patients with gastric and gastroesophageal junction adenocarcinomas treated with perioperative chemotherapy with or without preoperative radiotherapy.

Cancer 2020 01 18;126(1):37-45. Epub 2019 Sep 18.

Department of Radiation Oncology, Winship Cancer Institute, Emory University, Atlanta, Georgia.

Background: Perioperative chemotherapy (POC) is one standard approach for the treatment of resectable cancers of the stomach and gastroesophageal junction (GEJ), whereas there has been growing interest in preoperative therapies. The objective of the current study was to compare survival between patients treated with preoperative chemoradiotherapy and adjuvant chemotherapy (PCRT) with those receiving POC using a large database.

Methods: The National Cancer Data Base was queried for patients diagnosed between 2004 and 2013 with American Joint Committee on Cancer clinical group stage IB to stage IIIC (excluding T2N0 disease) adenocarcinoma of the stomach or GEJ. Patients treated with definitive surgery and POC with or without preoperative radiotherapy of 41 to 54 Gy were included. Overall survival (OS) was defined from the date of definitive surgery and estimated using the Kaplan-Meier method. A total of 14 patient and treatment variables were used for propensity score matching (PSM).

Results: A total of 1048 patients were analyzed: 53.2% received POC and 46.8% received PCRT. The primary tumor site was the GEJ in 69.1% of patients and stomach in 30.9% of patients. The median age of the patients was 60 years, and the median follow-up was 25.8 months. The use of PCRT was associated with a greater pathologic complete response rate of 13.1% versus 8.2% (P = .01). POC was associated with a decreased risk of death in unmatched groups (hazard ratio [HR], 0.83; P = .043). Using PSM cohorts, POC decreased the risk of death with a median OS of 45.1 months versus 31.4 months (HR, 0.70; P = .016). The 2-year OS rate was 72.9% versus 62.5% and the 5-year OS rate was 40.7% versus 33.1% for POC versus PCRT, respectively. Survival favored POC in PSM gastric (HR, 0.41; P = .07) and GEJ (HR, 0.77; P = .08) patient subgroups.

Conclusions: The addition of preoperative radiotherapy to POC appears to be associated with an increased risk of death in patients with resectable gastric and GEJ cancers.
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http://dx.doi.org/10.1002/cncr.32516DOI Listing
January 2020

Minimum-MU and sparse-energy-layer (MMSEL) constrained inverse optimization method for efficiently deliverable PBS plans.

Phys Med Biol 2019 10 10;64(20):205001. Epub 2019 Oct 10.

Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA, United States of America.

The deliverability of proton pencil beam scanning (PBS) plans is subject to the minimum monitor-unit (MU) constraint, while the delivery efficiency depends on the number of proton energy layers. This work develops an inverse optimization method for generating efficiently deliverable PBS plans. The proposed minimum-MU and sparse-energy-layer (MMSEL) constrained inverse optimization method utilizes iterative convex relaxations to handle the nonconvexity from minimum-MU constraint and dose-volume constraints, and regularizes group sparsity of proton spots to minimize the number of energy layers. The tradeoff between plan quality and delivery efficiency (in terms of the number of used energy layers) is controlled by the objective weighting of group sparsity regularization. MMSEL consists of two steps: first minimize for appropriate energy layers, and then with selected energy layers solve for the deliverable PBS plan. The solution algorithm for MMSEL is developed using alternating direction method of multipliers (ADMM). Range and setup uncertainties are modelled by robust optimization. MMSEL was validated using representative prostate, lung, and head-and-neck (HN) cases. The minimum-MU constraint was strictly enforced for all cases, so that all plans were deliverable. The number of energy layers was reduced by MMSEL to 78%, 76%, and 61% for prostate, lung and HN, respectively, while the similar plan quality was achieved. The number of energy layers was reduced by MMSEL to 54%, 57%, and 37% for prostate, lung and HN, respectively, while the plan quality was comprised and acceptable. MMSEL is proposed to strictly enforce minimum-MU constraint and minimize the number of energy layers during inverse optimization for efficiently deliverable PBS plans. In particular, the preliminary results suggest MMSEL potentially enables 25% to 40% reduction of energy layers while maintaining the similar plan quality.
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http://dx.doi.org/10.1088/1361-6560/ab4529DOI Listing
October 2019

Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning.

Phys Med Biol 2019 10 21;64(20):205022. Epub 2019 Oct 21.

Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, United States of America.

The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization into 3D cycle-consistent generative adversarial networks (cycleGAN) framework to effectively learn the nonlinear mapping between MRI and CT pairs. A cohort of 17 patients with co-registered CT and MR pairs were used to test the deep learning-based sCT generation method by leave-one-out cross-validation. Image quality between the sCT and CT images, gamma analysis passing rate, dose-volume metrics, distal range displacement, and the individual pencil beam Bragg peak shift between sCT- and CT-based proton plans were evaluated. The average mean absolute error (MAE) was 51.32  ±  16.91 HU. The relative differences of the statistics of the PTV dose-volume histogram (DVH) metrics in between sCT and CT were generally less than 1%. Mean values of dose difference, absolute dose difference (in percent of the prescribed dose) were  -0.07%  ±  0.07% and 0.23%  ±  0.08%. Mean gamma analysis pass rate of 1 mm/1%, 2 mm/2%, 3 mm/3% criteria with 10% dose threshold were 92.39%  ±  5.97%, 97.95%  ±  2.95% and 98.97%  ±  1.62% respectively. The median, mean and standard deviation of absolute maximum range differences were 0.09 cm and 0.23  ±  0.25 cm. The median and mean Bragg peak shifts among the 17 patients were 0.09 cm and 0.18  ±  0.07 cm. The image similarity, dosimetric and distal range agreement between sCT and original CT suggests the feasibility of further development of an MRI-only workflow for prostate proton radiotherapy.
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http://dx.doi.org/10.1088/1361-6560/ab41afDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7765705PMC
October 2019

Acupuncture in Adult and Pediatric Headache: A Narrative Review.

Neuropediatrics 2019 12 29;50(6):346-352. Epub 2019 Aug 29.

Department of Pediatrics, University of Louisville, Louisville, Kentucky, United States.

Headaches in children and adolescents remain a very common problem with migraine being the most common headache disorder to present to medical attention. The approach to the treatment of migraine in children has consisted of treatment with acute and preventive medications, combined with lifestyle modification and behavioral interventions, such as cognitive behavioral therapy. With increasing frequency, complementary and alternative medicine (CAM) approaches, including acupuncture, are often recommended in the pediatric population to address significant disability with limited evidence-based treatment options. In this article, the authors conduct a review of acupuncture in pediatric headache, including neurobiological mechanisms, adult headache studies, pediatric headache studies, safety, and use of acupuncture in other conditions in children. This article aims to summarize the currently available evidence with which to recommend acupuncture in children for the adjunctive treatment of headache. Acupuncture appears to be safe and effective for the treatment of migraine in children.
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http://dx.doi.org/10.1055/s-0039-1695785DOI Listing
December 2019