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3. Administering [177Lu]Lu-PSMA-617 Prior to Radical Prostatectomy in Men with High-risk Localised Prostate Cancer (LuTectomy): A Single-centre, Single-arm, Phase 1/2 Study

Author

Eapen, Renu S., Buteau, James P., Jackson, Price, Mitchell, Catherine, Oon, Sheng F., Alghazo, Omar, McIntosh, Lachlan, Dhiantravan, Nattakorn, Scalzo, Mark J., O'Brien, Jonathan, Sandhu, Shahneen, Azad, Arun A., Williams, Scott G., Sharma, Gaurav, Haskali, Mohammad B., Bressel, Mathias, Chen, Kenneth, Jenjitranant, Pocharapong, McVey, Aoife, Moon, Daniel, Lawrentschuk, Nathan, Neeson, Paul J., Murphy, Declan G., and Hofman, Michael S.

Published
2024
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5. Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge

Author

Ma, Jun, Zhang, Yao, Gu, Song, An, Xingle, Wang, Zhihe, Ge, Cheng, Wang, Congcong, Zhang, Fan, Wang, Yu, Xu, Yinan, Gou, Shuiping, Thaler, Franz, Payer, Christian, Štern, Darko, Henderson, Edward G.A., McSweeney, Dónal M., Green, Andrew, Jackson, Price, McIntosh, Lachlan, Nguyen, Quoc-Cuong, Qayyum, Abdul, Conze, Pierre-Henri, Huang, Ziyan, Zhou, Ziqi, Fan, Deng-Ping, Xiong, Huan, Dong, Guoqiang, Zhu, Qiongjie, He, Jian, and Yang, Xiaoping

Published
2022
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10. Dose-effect Relationship of Kidney Function After Stereotactic Ablative Body Radiotherapy for Primary Renal Cell Carcinoma: Trog 15.03 Fastrack Ii

Author

Gaudreault, Mathieu, primary, Hardcastle, Nicholas, additional, Jackson, Price, additional, McIntosh, Lachlan, additional, Higgs, Braden, additional, Pryor, David, additional, Sidhom, Mark, additional, Dykyj, Rachael, additional, Moore, Alisha, additional, Kron, Tomas, additional, and Siva, Shankar, additional

Published
2024
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12. Evaluation of manual and automated approaches for segmentation and extraction of quantitative indices from [18F]FDG PET-CT images

Author

Krokos, Georgios, Kotwal, Tejas, Malaih, Afnan, Barrington, Sally, Jackson, Price, Hicks, Rodney J., Marsden, Paul K., Fischer, Barbara Malene, Krokos, Georgios, Kotwal, Tejas, Malaih, Afnan, Barrington, Sally, Jackson, Price, Hicks, Rodney J., Marsden, Paul K., and Fischer, Barbara Malene

Abstract

Utilisation of whole organ volumes to extract anatomical and functional information from computed tomography (CT) and positron emission tomography (PET) images may provide key information for the treatment and follow-up of cancer patients. However, manual organ segmentation, is laborious and time-consuming. In this study, a CT-based deep learning method and a multi-atlas method were evaluated for segmenting the liver and spleen on CT images to extract quantitative tracer information from Fluorine-18 fluorodeoxyglucose ([18F]FDG) PET images of 50 patients with advanced Hodgkin lymphoma (HL). Manual segmentation was used as the reference method. The two automatic methods were also compared with a manually defined volume of interest (VOI) within the organ, a technique commonly performed in clinical settings. Both automatic methods provided accurate CT segmentations, with the deep learning method outperforming the multi-atlas with a DICE coefficient of 0.93 ± 0.03 (mean ± standard deviation) in liver and 0.87 ± 0.17 in spleen compared to 0.87 ± 0.05 (liver) and 0.78 ± 0.11 (spleen) for the multi-atlas. Similarly, a mean relative error of −3.2% for the liver and −3.4% for the spleen across patients was found for the mean standardized uptake value (SUVmean) using the deep learning regions while the corresponding errors for the multi-atlas method were −4.7% and −9.2%, respectively. For the maximum SUV (SUVmax), both methods resulted in higher than 20% overestimation due to the extension of organ boundaries to include neighbouring, high-uptake regions. The conservative VOI method which did not extend into neighbouring tissues, provided a more accurate SUVmax estimate. In conclusion, the automatic, and particularly the deep learning method could be used to rapidly extract information of the SUVmean within the liver and spleen. However, activity from neighbouring organs and lesions can lead to high biases in SUVmax and current practices of manually defining a volume of intere, Utilisation of whole organ volumes to extract anatomical and functional information from computed tomography (CT) and positron emission tomography (PET) images may provide key information for the treatment and follow-up of cancer patients. However, manual organ segmentation, is laborious and time-consuming. In this study, a CT-based deep learning method and a multi-atlas method were evaluated for segmenting the liver and spleen on CT images to extract quantitative tracer information from Fluorine-18 fluorodeoxyglucose ([18F]FDG) PET images of 50 patients with advanced Hodgkin lymphoma (HL). Manual segmentation was used as the reference method. The two automatic methods were also compared with a manually defined volume of interest (VOI) within the organ, a technique commonly performed in clinical settings. Both automatic methods provided accurate CT segmentations, with the deep learning method outperforming the multi-atlas with a DICE coefficient of 0.93 ± 0.03 (mean ± standard deviation) in liver and 0.87 ± 0.17 in spleen compared to 0.87 ± 0.05 (liver) and 0.78 ± 0.11 (spleen) for the multi-atlas. Similarly, a mean relative error of -3.2% for the liver and -3.4% for the spleen across patients was found for the mean standardized uptake value (SUVmean) using the deep learning regions while the corresponding errors for the multi-atlas method were -4.7% and -9.2%, respectively. For the maximum SUV (SUVmax), both methods resulted in higher than 20% overestimation due to the extension of organ boundaries to include neighbouring, high-uptake regions. The conservative VOI method which did not extend into neighbouring tissues, provided a more accurate SUVmaxestimate. In conclusion, the automatic, and particularly the deep learning method could be used to rapidly extract information of the SUVmeanwithin the liver and spleen. However, activity from neighbouring organs and lesions can lead to high biases in SUVmaxand current practices of manually defining a volume of intere

Published
2024

13. Clinical Trial Protocol for VIOLET: A Single-Center, Phase I/II Trial Evaluation of Radioligand Treatment in Patients with Metastatic Castration-Resistant Prostate Cancer with [161Tb]Tb-PSMA-I&T.

Author

Buteau, James P., Kostos, Louise, Alipour, Ramin, Jackson, Price, McInstosh, Lachlan, Emmerson, Brittany, Haskali, Mohammad B., Xie, Jing, Medhurst, Elizabeth, Ravi, Rajeev, Gonzalez, Brian D., Fettke, Heidi, Blyth, Benjamin, Furic, Luc, Owen, Katie, Sandhu, Shahneen, Murphy, Declan G., Azad, Arun A., and Hofman, Michael S.

Published
2024
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20. VIOLET: A phase I/II trial evaluation of radioligand treatment in men with metastatic castration-resistant prostate cancer with [161Tb]Tb-PSMA-I&T.

Author

Buteau, James Patrick, primary, Kostos, Louise Kathleen, additional, Alipour, Ramin, additional, Jackson, Price, additional, McIntosh, Lachlan, additional, Emmerson, Brittany, additional, Haskali, Mohammad B, additional, Yeung, Theresa, additional, Xie, Sophia, additional, Medhurst, Elizabeth, additional, Ravi, Rajeev, additional, Gonzalez, Brian D., additional, Fettke, Heidi, additional, Ng, Nicole, additional, Docanto, Maria, additional, Bukczynska, Patricia, additional, Blyth, Benjamin, additional, Furic, Luc, additional, Azad, Arun, additional, and Hofman, Michael S, additional

Published
2023
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21. Comparison of dual-energy CT with positron emission tomography for lung perfusion imaging in patients with non-small cell lung cancer

Author

Gaudreault, Mathieu, primary, Korte, James, additional, Bucknell, Nicholas, additional, Jackson, Price, additional, Sakyanun, Pitchaya, additional, McIntosh, Lachlan, additional, Woon, Beverley, additional, Buteau, James P, additional, Hofman, Michael S, additional, Mulcahy, Tony, additional, Kron, Tomas, additional, Siva, Shankar, additional, and Hardcastle, Nicholas, additional

Published
2023
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22. Safety of Lutetium-177 prostate-specific membrane antigen-617 (PSMA-617) radioligand therapy in the setting of severe renal impairment: a case report and literature review

Author

Sutherland, Duncan E. K., primary, Kashyap, Raghava, additional, Jackson, Price, additional, Buteau, James P., additional, Murphy, Declan G., additional, Kelly, Brian, additional, Spain, Lavinia, additional, Sandhu, Shahneen, additional, Azad, Arun A., additional, Medhurst, Elizabeth, additional, Kong, Grace, additional, and Hofman, Michael S., additional

Published
2023
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23. sj-docx-1-tam-10.1177_17588359231177018 – Supplemental material for Safety of Lutetium-177 prostate-specific membrane antigen-617 (PSMA-617) radioligand therapy in the setting of severe renal impairment: a case report and literature review

Author

Sutherland, Duncan E. K., Kashyap, Raghava, Jackson, Price, Buteau, James P., Murphy, Declan G., Kelly, Brian, Spain, Lavinia, Sandhu, Shahneen, Azad, Arun A., Medhurst, Elizabeth, Kong, Grace, and Hofman, Michael S.

Subjects
110203 Respiratory Diseases, FOS: Clinical medicine, 111702 Aged Health Care, FOS: Health sciences, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified, 111299 Oncology and Carcinogenesis not elsewhere classified
Abstract

Supplemental material, sj-docx-1-tam-10.1177_17588359231177018 for Safety of Lutetium-177 prostate-specific membrane antigen-617 (PSMA-617) radioligand therapy in the setting of severe renal impairment: a case report and literature review by Duncan E. K. Sutherland, Raghava Kashyap, Price Jackson, James P. Buteau, Declan G. Murphy, Brian Kelly, Lavinia Spain, Shahneen Sandhu, Arun A. Azad, Elizabeth Medhurst, Grace Kong and Michael S. Hofman in Therapeutic Advances in Medical Oncology

Published
2023
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30. A deep learning model to automate skeletal muscle area measurement on computed tomography images

Author

Amarasinghe, Kaushalya C., Lopes, Jamie, Beraldo, Julian, Kiss, Nicole, Bucknell, Nicholas, Everitt, Sarah, Jackson, Price, Litchfield, Cassandra, Denehy, Linda, Blyth, Benjamin J., Siva, Shankar, MacManus, Michael, Ball, David, Li, Jason, Hardcastle, Nicholas, Amarasinghe, Kaushalya C., Lopes, Jamie, Beraldo, Julian, Kiss, Nicole, Bucknell, Nicholas, Everitt, Sarah, Jackson, Price, Litchfield, Cassandra, Denehy, Linda, Blyth, Benjamin J., Siva, Shankar, MacManus, Michael, Ball, David, Li, Jason, and Hardcastle, Nicholas

Abstract

Background: Muscle wasting (Sarcopenia) is associated with poor outcomes in cancer patients. Early identification of sarcopenia can facilitate nutritional and exercise intervention. Cross-sectional skeletal muscle (SM) area at the third lumbar vertebra (L3) slice of a computed tomography (CT) image is increasingly used to assess body composition and calculate SM index (SMI), a validated surrogate marker for sarcopenia in cancer. Manual segmentation of SM requires multiple steps, which limits use in routine clinical practice. This project aims to develop an automatic method to segment L3 muscle in CT scans. Methods: Attenuation correction CTs from full body PET-CT scans from patients enrolled in two prospective trials were used. The training set consisted of 66 non-small cell lung cancer (NSCLC) patients who underwent curative intent radiotherapy. An additional 42 NSCLC patients prescribed curative intent chemo-radiotherapy from a second trial were used for testing. Each patient had multiple CT scans taken at different time points prior to and post- treatment (147 CTs in the training and validation set and 116 CTs in the independent testing set). Skeletal muscle at L3 vertebra was manually segmented by two observers, according to the Alberta protocol to serve as ground truth labels. This included 40 images segmented by both observers to measure inter-observer variation. An ensemble of 2.5D fully convolutional neural networks (U-Nets) was used to perform the segmentation. The final layer of U-Net produced the binary classification of the pixels into muscle and non-muscle area. The model performance was calculated using Dice score and absolute percentage error (APE) in skeletal muscle area between manual and automated contours. Results: We trained five 2.5D U-Nets using 5-fold cross validation and used them to predict the contours in the testing set. The model achieved a mean Dice score of 0.92 and an APE of 3.1% on the independent testing s

Published
2021

32. A Deep Learning Model to Automate Skeletal Muscle Area Measurement on Computed Tomography Images

Author

Amarasinghe, Kaushalya C., primary, Lopes, Jamie, additional, Beraldo, Julian, additional, Kiss, Nicole, additional, Bucknell, Nicholas, additional, Everitt, Sarah, additional, Jackson, Price, additional, Litchfield, Cassandra, additional, Denehy, Linda, additional, Blyth, Benjamin J., additional, Siva, Shankar, additional, MacManus, Michael, additional, Ball, David, additional, Li, Jason, additional, and Hardcastle, Nicholas, additional

Published
2021
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33. A comparison of 2D and 3D kidney absorbed dose measures in patients receiving 177Lu-DOTATATE

Author

Willowson, Kathy P, Ryu, HyunJu, Jackson, Price, Singh, Anita, Eslick, Enid, and Bailey, Dale L

Subjects
NET, lcsh:Medical physics. Medical radiology. Nuclear medicine, lcsh:Biology (General), Dosimetry, lcsh:R895-920, Original Article, Kidney, lcsh:QH301-705.5, Lutate
Abstract

Objective(s): To investigate and compare quantitative accuracy of kidney absorbed dose measures made from both 2D and 3D imaging in patients receiving 177Lu-DOTATATE (Lutate) for treatment of neuroendocrine tumours (NETs). Methods: Patients receiving Lutate therapy underwent both whole body planar imaging and SPECT/CT imaging over the kidneys at time points 0.5, 4, 24, and 96-120 hours after injection. Planar data were corrected for attenuation using transmission data, and were converted to units of absolute activity via two methods, using either a calibration standard in the field of view or relative to pre-voiding image total counts. Hand drawn regions of interest were used to generate time activity curves and kidney absorbed dose estimates in OLINDA-EXM. Fully quantitative SPECT data were generated using CT-derived corrections for both scatter and attenuation, before correction for dead time and application of a camera specific sensitivity factor to convert data to units of absolute activity. Volumes of interest were defined for kidney using the co-registered x-ray CT, before time activity curves and absorbed dose measures were generated in OLINDA-EXM, both with and without corrections made to the model for patient specific kidney volumes. Quantitative SPECT data were also used to derive dose maps through dose kernel convolution (DKC), which was treated as the gold standard. Results: A total of 50 studies were analysed, corresponding to various cycles of treatment from 21 patients. Planar absorbed dose estimates were consistently higher than SPECT derived estimates by, on average, a factor of 3. Conclusion: Quantitative SPECT is considered the gold standard approach for organ specific dosimetry however often relies on in house software. As such planar methods for estimating absorbed dose are much more widely available, and in particular, are often the only source of reference in previously published data. For the case of Lutate dosimetry, planar measures may lead to a three-fold increase in measures of kidney absorbed dose.

Published
2018

34. Clinical Trial Protocol for LuTectomy: A Single-arm Study of the Dosimetry, Safety, and Potential Benefit of 177Lu-PSMA-617 Prior to Prostatectomy

Author

Dhiantravan, Nattakorn, primary, Violet, John, additional, Eapen, Renu, additional, Alghazo, Omar, additional, Scalzo, Mark, additional, Jackson, Price, additional, Keam, Simon P., additional, Mitchell, Catherine, additional, Neeson, Paul J., additional, Sandhu, Shahneen, additional, Williams, Scott G., additional, Moon, Daniel, additional, Lawrentschuk, Nathan, additional, Azad, Arun, additional, Hofman, Michael S., additional, and Murphy, Declan G., additional

Published
2021
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35. Study of the dosimetry, safety, and potential benefit of 177Lu-PSMA-617 radionuclide therapy prior to radical prostatectomy in men with high-risk localized prostate cancer (LuTectomy study).

Author

Alghazo, Omar, primary, Eapen, Renu, additional, Dhiantravan, Nattakorn, additional, Violet, John A., additional, Jackson, Price, additional, Scalzo, Mark, additional, Keam, Simon P., additional, Mitchell, Catherine, additional, Neeson, Paul J., additional, Sandhu, Shahneen Kaur, additional, Williams, Scott, additional, Moon, Daniel, additional, Lawrentschuk, Nathan, additional, Azad, Arun, additional, Hofman, Michael S, additional, and Murphy, Declan G., additional

Published
2021
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36. Single-arm prospective interventional study assessing feasibility of using gallium-68 ventilation and perfusion PET/CT to avoid functional lung in patients with stage III non-small cell lung cancer

Author

Bucknell, Nicholas, primary, Hardcastle, Nicholas, additional, Jackson, Price, additional, Hofman, Michael, additional, Callahan, Jason, additional, Eu, Peter, additional, Iravani, Amir, additional, Lawrence, Rhonda, additional, Martin, Olga, additional, Bressel, Mathias, additional, Woon, Beverley, additional, Blyth, Benjamin, additional, MacManus, Michael, additional, Byrne, Keelan, additional, Steinfort, Daniel, additional, Kron, Tomas, additional, Hanna, Gerard, additional, Ball, David, additional, and Siva, Shankar, additional

Published
2020
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38. Peptide Receptor Radionuclide Therapy with 67Cu-CuSarTATE Is Highly Efficacious Against a Somatostatin-Positive Neuroendocrine Tumor Model

Author

Cullinane, Carleen, primary, Jeffery, Charmaine M., additional, Roselt, Peter D., additional, van Dam, Ellen M., additional, Jackson, Susan, additional, Kuan, Kevin, additional, Jackson, Price, additional, Binns, David, additional, van Zuylekom, Jessica, additional, Harris, Matthew J., additional, Hicks, Rodney J., additional, and Donnelly, Paul S., additional

Published
2020
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39. Radiation Dosimetry in 177Lu-PSMA-617 Therapy.

Author

Jackson, Price, Hofman, Michael, McIntosh, Lachlan, Buteau, James Patrick, and Ravi Kumar, Aravind

Abstract

Radionuclide therapy using the small molecule PSMA bound to the beta-emitting radionuclide, Lutetium-177 (177Lu-PSMA) has demonstrated efficacy and survival benefit castrate resistant metastatic disease and represents a novel new line of therapy. Whilst dosimetry was critical for early development, it was not incorporated into either the TheraP or VISION randomized studies, highlighting the difficulty of adopting dosimetry in routine clinical practice. Accumulated clinical experience has also shown that the common (and generally low grade) toxicities such as nausea, xerostomia, and cytopenias are not readily predicted on the basis of dosimetry estimates. The majority of dosimetry and clinical literature deals with the radiopharmaceutical 177Lu-PSMA-617 which displays relatively consistent patterns of retention among normal tissues and high specificity for metastatic prostate cancer phenotypes. Population dosimetry incorporating estimates to the kidneys, salivary glands, and bone marrow have been widely reported the typical range of doses is becoming well established. There is growing interest on tumor dosimetry in 177Lu-PSMA-617 therapy as an overall modest side-effect profile from primary organ retention has been observed. A focus away from normal organ dosimetry to whole body tumor dosimetry may enable early prediction of treatment failure. Given the safety of 177Lu-PSMA there is also potential to escalate administered radioactivity to further improve outcomes. Importantly, the variability of uptake between individuals, both to tumor and normal organs, has also been highlighted which provides some rationale for the utility of personalized radiation analysis to optimize treatment based on potential toxicity thresholds or tumor control. Methods to perform dosimetry using serial post treatment imaging may incorporate planar, 3D SPECT, or hybrid datasets. Reliable measurements may be obtained through either method, however, continued developments in computational analysis are better suited to fully 3D imaging; particularly in conjunction with volumetric CT to assist with alignment and contouring. Dose analysis over sequential treatment cycles is vital to understand the radiobiology of these treatments which is unique compared to external beam therapy due to dose rate, fractionation scheme, and potential for intratumoral nonuniformity. [ABSTRACT FROM AUTHOR]

Published
2022
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41. Dose-Effect Relationship of Kidney Function After SABR for Primary Renal Cell Carcinoma: TROG 15.03 FASTRACK II.

Author

Gaudreault, Mathieu, Hardcastle, Nicholas, Jackson, Price, McIntosh, Lachlan, Higgs, Braden, Pryor, David, Sidhom, Mark, Dykyj, Rachael, Moore, Alisha, Kron, Tomas, and Siva, Shankar

Subjects
*SINGLE-photon emission computed tomography, *STEREOTACTIC radiotherapy, *RENAL cell carcinoma, *GLOMERULAR filtration rate, *RENAL cancer
Abstract

Stereotactic ablative body radiotherapy (SABR) is a novel option to treat primary renal cell carcinoma. However, a high radiation dose may be received by the treated kidney, which may affect its function posttreatment. This study investigates the dose-effect relationship of kidney SABR with posttreatment renal function. This was a prespecified secondary endpoint of the multicenter FASTRACK II (Focal Ablative STereotactic RAdiotherapy for Cancers of the Kidney phase II) clinical trial (National Clinical Trial 02613819). Patients received either 26 Gy in a single fraction (SF) for tumors with a maximal diameter of 4 cm or less or 42 Gy in 3 fractions (multifraction [MF]) for larger tumors. To determine renal function change, 99mTc-dimercaptosuccinic acid (DMSA) single-photon emission computed tomography/computed tomography (SPECT/CT) scans were acquired, and the glomerular filtration rate was estimated at baseline, 12, and 24 months posttreatment. Imaging data sets were rigidly registered to the planning CT where kidneys were segmented to calculate dose-response curves. From 71 enrolled patients, 36 (51%) and 26 (37%) patients were included in this study based on availability of posttreatment data at 12 and 24 months, respectively. The ipsilateral kidney glomerular filtration rate decreased from baseline by 42% and 39% in the SF cohort and by 45% and 62% in the MF cohort, at 12 and 24 months, respectively (P <.03). The loss in renal function was 3.6%/Gy ± 0.8%/Gy and 4.5%/Gy ± 1.0%/Gy in the SF cohort and 1.7%/Gy ± 0.1%/Gy and 1.7%/Gy ± 0.2%/Gy in the MF cohort at 12 and 24 months, respectively. The major loss in renal function occurred in high-dose regions, where dose-response curves converged to a plateau. For the first time in a multicenter study, the dose-effect relationship at 12 and 24 months post-SABR treatment for primary renal cell carcinoma was quantified. Kidney function reduces linearly with dose up to 100 Gy BED 3. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Long-Term Follow-up and Outcomes of Retreatment in an Expanded 50-Patient Single-Center Phase II Prospective Trial of 177Lu-PSMA-617 Theranostics in Metastatic Castration-Resistant Prostate Cancer

Author

Violet, John, primary, Sandhu, Shahneen, additional, Iravani, Amir, additional, Ferdinandus, Justin, additional, Thang, Sue-Ping, additional, Kong, Grace, additional, Kumar, Aravind Ravi, additional, Akhurst, Tim, additional, Pattison, David, additional, Beaulieu, Alexis, additional, Mooi, Jennifer, additional, Tran, Ben, additional, Guo, Christina, additional, Kalff, Victor, additional, Murphy, Declan G, additional, Jackson, Price, additional, Eu, Peter, additional, Scalzo, Mark, additional, Williams, Scott, additional, Hicks, Rodney J., additional, and Hofman, Michael S., additional

Published
2019
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46. Results of a 50 patient single-center phase II prospective trial of Lutetium-177 PSMA-617 theranostics in metastatic castrate-resistant prostate cancer.

Author

Hofman, Michael, primary, Violet, John A, additional, Hicks, Rodney J, additional, Ferdinandus, Justin, additional, Thang, Sue Ping, additional, Iravani, Amir, additional, Kong, Grace, additional, Ravi Kumar, Aravind, additional, Akhurst, Timothy J., additional, Mooi, Jennifer, additional, Guo, Christina, additional, Tran, Ben, additional, Jackson, Price, additional, Scalzo, Mark, additional, Eu, Peter, additional, Williams, Scott, additional, and Sandhu, Shahneen Kaur, additional

Published
2019
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50. 64Cu-SARTATE PET Imaging of Patients with Neuroendocrine Tumors Demonstrates High Tumor Uptake and Retention, Potentially Allowing Prospective Dosimetry for Peptide Receptor Radionuclide Therapy

Author

Hicks, Rodney J., primary, Jackson, Price, additional, Kong, Grace, additional, Ware, Robert E., additional, Hofman, Michael S., additional, Pattison, David A., additional, Akhurst, Timothy A., additional, Drummond, Elizabeth, additional, Roselt, Peter, additional, Callahan, Jason, additional, Price, Roger, additional, Jeffery, Charmaine M., additional, Hong, Emily, additional, Noonan, Wayne, additional, Herschtal, Alan, additional, Hicks, Lauren J., additional, Hedt, Amos, additional, Harris, Matthew, additional, Paterson, Brett M., additional, and Donnelly, Paul S., additional

Published
2018
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