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Radiation Oncology
Click on a publication's title to access a PDF or read an abstract.
Deformable Registration
Piper JW. Evaluation of An Intensity-Based Free-Form Deformable Registration Algorithm. Medical Physics. June 2007;34(6):2353-2354.
Nelson AS, Duchateau M, Piper JW, Verellen D, De Ridder M. Evaluation of a Free-Form Intensity Based Deformable Registration Method Using the POPI Model. Med Phys 2014; 41:202.
Pirozzi S, Piper J, Nelson A, Duchateau M, Verellen D, De Ridder M. A Novel Framework for Deformable Registration Evaluation and Quality Assurance. IJROBP 2013; 87(2):S719.
Pirozzi S, Piper J, Nelson A, Duchateau M, Verellen D, De Ridder M. A Novel Framework for User-Intervened Correction of Deformable Registration. IJROBP 2013; 87(2):S144.
Nelson AS, Duchateau M, Piper WJ, Verellen D, De Ridder M. Deformable Dose Mapping Accuracy Using a Framework for User-Intervened Correction of Deformable Registration. Med Phys 2014; 41:207.
Fogh SE, Kubicek GJ, Axelrod R, Keane WM, Piper JW, Xiao Y, Machtay M. Utility of Deformable PET Fusion Gross Tumor Volumes in Head & Neck Malignancies. ASTRO Translational Advances in Radiation Oncology and Cancer Imaging 2008 Poster Presentation.
Piper JW. Evaluation of a CT to Cone-Beam CT Deformable Registration Algorithm. IJROBP. 2007;69(3 Suppl S):S418-419.
Nelli Flavio Enrico, Harwood Jeffrey Roy. A Method for Assessing the Dosimetric Consistency of Single Phase 4DCT Dose Accumulation Based on Deforming Image Registration. Physica Medica September 2016; 32(3):275.
Jason Pukala, Perry B. Johnson, Amish P. Shah, Katja M. Langen, Frank J. Bova, Robert J. Staton, Rafael R. Mañon, Patrick Kelly, and Sanford L. Meeks. Benchmarking of Five Commercial Deformable Image Registration Algorithms for Head and Neck Patients. Journal of Applied Clinical Medical Physics, VOLUME 17, NUMBER 3, 2016.
Perry B. Johnson, Kyle R. Padgett, Kuan L. Chen, Nesrin Dogan. Evaluation of the Tool "Reg Refine" for User-Guided Deformable Image Registration. Journal of Applied Clinical Medical Physics, VOLUME 17, NUMBER 3, 2016. *Some details about the deformation algorithm are incorrect and will be corrected in a future correction in the journal.
Piper J, Nelson A, Harper J. Deformable Image Registration in MIM Maestro® Evaluation and Description. March 2018.
(White Paper)Nelson AD. Validation of Manual and Assisted Alignment Techniques. June 2018.
(White Paper)Piper JW, Richmond JH, Nelson AS. VoxAlign Deformation Engine®. July 2018.
(White Paper)Pirozzi S, Kruzer A, Nelson AS. Evaluation of three deformable image registration techniques between CT and CBCT in prostate cancer radiotherapy. International Journal of Radiation Oncology, Biology, Physics. 1 November 2018. Volume 102, Issue 3, (Supplement 2018):E565.
Pirozzi S, Lamba N, Kruzer A, Nelson AS. Evaluation of a Novel Hybrid Deformable Registration Algorithm for CBCT to CBCT Deformation in Prostate Studies. International Journal of Radiation Oncology, Biology, Physics. 1 November 2018, Vol. 102, Number 3S, Supplement 2018:E546-E547.
Hammers JE, Pirozzi S, Lindsay D, Kaidar-Person O, Tan X, Chen RC, Das SK, Mavroidis P. Evaluation of a commercial DIR platform for contour propagation in prostate cancer patients treated with IMRT/VMAT. J Appl Clin Med Phys. 2020 Feb;21(2):14-25.
Padgett KR, Stoyanova R, Pirozzi S, Johnson P, Piper J, Dogan N, Pollack A. Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis J Appl Clin Med Phys. 2018 Mar;19(2):258-264.
Adaptive Radiotherapy
Hu, K, Surapaneni, A. Value of Kilovoltage Cone Beam CT (CBCT) to Track Dose in the Adaptive Radiation Treatment of Head and Neck Cancer. RSNA 2008 Scientific Assembly and Annual Meeting, Feb 18 - Feb 20, 2008, Chicago IL.
Pirozzi S, Piper J, Nelson A, Shen Z, Gardner S. Evaluation of Deformable Prostate Cone-Beam Computed Tomography (CBCT) Contouring Methods for Adaptive Radiation Therapy. IJROBP 2013; 87(2):S719.
Liu H, Greskovich J, Koyfman S, Xia P. Evaluation of Volumetric Change and Dosimetric Discrepancy with Daily Cone-Beam CT for Patients with Head-and-Neck Cancer. Med Phys 2012; 39:3782.
Pukala J, Staton R, Langen K. What Is the Importance of Dose Recalculation for Adaptive Radiotherapy Dose Assessment? Med Phys 2012; 39:3699.
Ferjani S, Huang G, Shang Q, Xia P. Using Shifting Planned Dose Matrix to Evaluate Daily Dose Changes for IMRT Prostate Treatment. Med Phys 2012; 39:3659.
Li W, Vassil A, Zhong Y, Xia P. Evaluation of Atlas-Based Auto-Segmentation on Daily In-Room CT for Prostate Cancer. Med Phys 2012; 39:3676.
Fragoso RC, Piper JW, Nelson AS, Harrison AS, Machtay M, Xiao Y. Evaluation of a Deformable Re-Contouring Method for Adaptive Therapy. ACRO Annual Meeting 2008 Poster Presentation.
Dyess A, Seuntjens J, Poon E, Parker W. Dosimetric Assessment of Treatment Using CBCT Images. Med Phys 2012; 39:3700.
Su F, Chen Z, Nath R. A Dosimetric Assessment of Rectum and Bladder Using Deformable Registration in Image-Guided Adaptive Prostate IMRT. Med Phys 2011; 38: 3448.
Poon E, Al-Wassia R, Freeman C, Parker W. Dosimetric Impact of Positioning and Anatomical Changes Over the Course of Craniospinal Irradiation Using Helical TomoTherapy. Med Phys 2011; 38:3451.
Louise S. H. Bendall, Maria Najim, Rachel Stensmyr, Emily Flower, Shan Yau, David I. Thwaites & Jonathan R. Sykes (2015) Performance Evaluation of Head and Neck Contour Adaptation with Cone Beam CT Using Two Commercial Software Systems. Acta Oncologica, 54:9, 1693-1697.
Christian A. Hvid, Ulrik V. Elstrøm, Kenneth Jensen, Markus Alber & Cai Grau (2016): Accuracy of Software-Assisted Contour Propagation from Planning CT to Cone Beam CT in Head and Neck Radiotherapy. Acta Oncologica.
La Macchia, M., Fellin, F., Amichetti, M. et al. Systematic Evaluation of Three Different Commercial Software Solutions for Automatic Segmentation for Adaptive Therapy in Head-and-Neck, Prostate, and Pleural Cancer. Radiat Oncol 7, 160 (2012).
Lamba N, Pittock D, Ginsburg S, Darkow D, Bonsall H, Fung WWK, M.Phil, Man HMC, Kruzer A, Nelson AS, M.D. Toward daily dose tracking for adaptive therapy: feasibility of using Monte Carlo dose calculation on corrected CBCT images. Sept. 2019 ASTRO.
Pittock D, Lamba N, Ginsburg S, Dragojevic I, Kruzer A, Nelson AS. Comparison of two CBCT correction methods for daily adaptive therapy dose tracking. July 2019 AAPM.
Bertholet J, Anastasi G, Noble D, Bel A, van Leeuwen R, Roggen T, Duchateau M, Pilskog S, Garibaldi C, Tilly N, García-Mollá R, Bonaque J, Oelfke U, Aznar MC, Heijmen B. Patterns of practice for adaptive and real-time radiation therapy (POP-ART RT) part II: Offline and online plan adaption for interfractional changes. Radiother Oncol. 2020 Dec;153:88-96.
Atlas Segmentation and Post-Processing
Hu J, Master Z, Ng YY, Yap J. Potential Improvements of Planning Workflow by Automatic Generation of Planning Support Structures for Nasopharyngeal Carcinoma (NPC) Treatment Planning. AAMD Annual Meeting 2015 Poster Presentation.
Mariangela La Macchia, Francesco Fellin, Maurizio Amichetti, Marco Cianchetti, Stefano Gianolini, Vitali Paola, Antony J Lomax, Lamberto Widesott. Systematic Evaluation of Three Different Commercial Software Solutions for Automatic Segmentation for Adaptive Therapy in Head-and-Neck, Prostate and Pleural Cancer. Radiation Oncology 2012, 7:160.
Nelson AS, Brockway J, Liu M, Javorek A, Pirozzi S, Piper JW. Evaluation of an Atlas-Based Segmentation Method for Prostate MRI. IJROBP 2014; 90(1):S419-420.
Patel RB, Traughber B, Kaminsky D, et al. Evaluation of an Atlas-Based Segmentation Method for High Risk Prostate Cancer with RTOG Defined Pelvic Lymph Node. IJROBP 2014; 90(1):S74-75.
Nelson AS, Piper JW, Javorek AR, Pirozzi SD, Lu M. Comparison of Two Atlas-Based Segmentation Methods for Head and Neck Cancer Including RTOG-Defined Lymph Node Levels. IJROBP 2014; 90(1):S882.
Horvat M, Nelson AS, Pirozzi SD. Time Savings of a Multi-Atlas Approach for Liver Segmentation. J Nucl Med. 2014; 55 (Supplement 1):1523.
Hu K, Lin A, Young A, Kubicek G, Piper JW, Nelson AS, Dolan J, Masino R, Machtay M. Timesavings for Contour Generation in Head and Neck IMRT: Multi-Institutional Experience with an Atlas-Based Segmentation Method. IJROBP. 2008; 72(1) Suppl: S391.
Lin A, Kubicek G, Piper JW, Nelson AS, Dicker AP, Valicenti RK. Atlas-Based Segmentation in Prostate IMRT: Timesavings in the Clinical Workflow. IJROBP. 2008; 72(1) Suppl: S328-329.
Ennis RD, Young AV, Wernick I, Evans AE. Atlas-Based Segmentation Improves Consistency and Decreases Time Required for Contouring Postoperative Endometrial Cancer Nodal Volumes. International Journal of Radiation Oncology * Biology * Physics. 1 November 2009 (Vol. 75, Issue 3, Supplement, Page S367).
Pirozzi SD, Horvat M, Nelson AS, Piper JW. Atlas-Based Segmentation: Evaluation of a Multi-Atlas Approach for Prostate Cancer. Accepted for Presentation at the ASTRO Annual Meeting 2012.
Pirozzi S, Horvat M, Piper J, Nelson AS. Atlas-Based Segmentation: Evaluation of a Multi-Atlas Approach for Lung Cancer. Med Phys 2012; 39:3677.
Pirozzi SD, Nelson AS, Piper JW. Atlas-Based Segmentation: Comparison of Multiple Segmentation Approaches for Lymph Level Targets and Normal Structures in Head and Neck Cancer. International Journal of Radiation Oncology * Biology * Physics 1 October 2011 (Vol.81, Issue 2, Supplement, Page S828).
Landau E, Hu K, Oppenheimer A, Skinner WKJ, Young A, Piper JW, Kalnicki S, Harrison LB. Automatic Contouring of Vital Swallowing Structures Using an Atlas-based Segmentation Method: A Time Saving and Toxicity Assessment. Accepted for Presentation at the ASTRO Annual Meeting 2009.
Padgett KR, Swallen A, Pirozzi S, Piper J, Chinea FM, Abramowitz MC, Nelson A, Pollack A, Stoyanova R. Towards a universal MRI atlas of the prostate and prostate zones: Comparison of MRI vendor and image acquisition parameters. Strahlenther Onkol. 2019 Feb;195(2):121-130.
PET Segmentation
Rohren EM, Etchebehere EC, Araujo JC, Hobbs BP, Swanston NM, Everding M, Moody T, Macapinlac HA. Determination of Skeletal Tumor Burden on 18F-Fluoride PET/CT. J Nucl Med. 2015; 56:1507-1512.
Obara P, Liu H, Wroblewski K, et al. Quantification of Metabolic Tumor Activity and Burden in Patients with Non-Small-Cell: Is Manual Adjustment of Semi-Automatic Gradient-Based Measurements Necessary? Nucl Med Commun 2015; 36(8):782-9.
Zhang G, Han D, Ma C, Lu J, Sun T, Liu T, Zhu J, Zhou J, Yin Y. Gradient-Based Delineation of the Primary GTV on FLT PET in Squamous Cell Cancer of the Thoracic Esophagus and Impact on Radiotherapy Planning. Radiation Oncology 2015, 10:11.
Sridhar P, Mercier G, Tan J, Truong MT, Daly B, Subramaniam RM. FDG PET Metabolic Tumor Volume Segmentation and Pathologic Volume of Primary Human Solid Tumors. AJR Am J Roentgenol 2014; 202(5):1114-9.
Nelson AS, Faulhaber PF, Pirozzi SD, Harper JW, Piper JW. Comparison of Gradient PET Segmentation from a Multi-Modality PET/CT Measurement Tool to Gradient PET Segmentation Alone. J Nucl Med. 2014; 55 (Supplement 1):1522.
Werner-Wasik M, Nelson D, Choi W, Arai Y, Faulhaber P, Kang P, Almeida F, Xiao Y, Ohri N, Brockway K, Piper J, Nelson A. What is the Best Way to Contour Lung Tumors on PET Scans: Multi-Observer Validation of a Gradient-Based Method Using a NSCLC Digital PET Phantom. IJROBP 2012; 82(3):1164-1171.
Fogh S, Karancke J, Nelson AS, McCue P, Axelrod R, Werner-Wasik W. Pathologic Correlation of PET-CT Based Auto-Contouring for Radiation Planning in Lung Cancer. Presented at the World Conference on Lung Cancer Meeting in 2009.
Werner-Wasik M, Kang P, Choi W, Ohri N, Faulhaber P, Nelson D, Nelson A, Piper J, Shen Z, Pirozzi S. Comparison of PET Contouring Methods in Patients With Early-Stage Resected Non-Small Cell Lung Cancer (NSCLC): A Pathologic–Imaging Correlation IJROBP 2013; 87(2):S540.
Nelson AS, Werner-Wasik M, Choi W, et al. Evaluation of Gradient PET Segmentation for Total Lesion Glycolysis Compared to Thresholds and Manual Contouring. J Nucl Med. 2011; 52 (Supplement 1):2077.
Nelson AD, Nelson AS. Tissue Segmentation in PET Image Volumes. June 2018.
(White Paper)Mirando D, Saiprasad M, Pirozzi S, Kruzer A, Nelson AS. Evaluation of an automated lung segmentation method using an iterative thresholding and processing technique. Journal of Nuclear Medicine. May 2018, Vol. 59 (Supplement 1):1756.
PET Treatment Response
Etchebehere EC, Araujo JC, Fox PS, Swanston NM, Macapinlac HA, Rohren EM. Prognostic Factors in Patients Treated with 223Ra: The Role of Skeletal Tumor Burden on Baseline 18F-Fluoride PET/CT in Predicting Overall Survival. J Nucl Med. 2015; 56:1177-1184.
Yu J, Cooley T, Truong MT, Mercier G, Subramaniam RM. Head and Neck Squamous Cell Cancers (Stages III and IV) Induction Chemotherapy Assessment: Value of FDG Volumetric Imaging Parameters. J Med Imaging Radiat Oncol 2014; 58(1):18-24.
Davison J, Mercier G, Russo G, Subramaniam RM. PET-Based Primary Tumor Volumetric Parameters and Survival of Patients with Non-Small Cell Lung Carcinoma. AJR Am J Roentgenol 2013; 200(3):635-40.
Shah B, Srivastava N, Hirsch AE, et al. Intra-Reader Reliability of FDG PET Volumetric Tumor Parameters: Effects of Primary Tumor Size and Segmentation Methods. Ann Nucl Med. 2012 Nov;26(9):707-14.
Romesser PB, Qureshi MM, Shah BA et al. Superior Prognostic Utility of Gross and Metabolic Tumor Volume Compared to Standardized Uptake Value Using PET/CT in Head and Neck Squamous Cell Carcinoma Patients Treated with Intensity Modulated Radiotherapy. Ann Nucl Med 2012; 26(7):527-34.
Dibble EH, Alvarez AC, Truong MT, et al. 18F-FDG Metabolic Tumor Volume and Total Glycolytic Activity of Oral Cavity and Oropharyngeal Squamous Cell Cancer: Adding Value to Clinical Staging. J Nucl Med 2012; 53(5):709-715.
Liao S, Penney BC, Wroblewski K, et al. Prognostic Value of Metabolic Tumor Burden on 18FFDG PET in Nonsurgical Patients with Non-Small Cell Lung Cancer. Eur J Nucl Med Mol Imaging 2012; 39(1):27-38.
Liao S, Penney BC, Zhang H, et al. Prognostic Value of the Quantitative Metabolic Volumetric Measurement on 18F-FDG PET/CT in Stage IV Nonsurgical Small-Cell Lung Cancer. Acad Radiol 2012; 19(1):69-77.
Morgan R, Chin BB, Lanning R. Feasibility of Rapid Integrated Radiation Therapy Planning with Follow-Up FDG PET/CT to Improve Overall Treatment Assessment in Head and Neck Cancer. Am J Nucl Med Mol Imaging. 2019 Feb 15;9(1):24-29.
Clinical Trials
Lawell MP, Indelicato DJ, Paulino AC, et al. An Open Invitation to Join the Pediatric Proton/Photon Consortium Registry to Standardize Data Collection in Pediatric Radiation Oncology. Br J Radiol 2019; 92: 20190673.
Deep Learning Auto-Contouring
C Halley*, H Wan, A Kruzer, D Pittock, D Darkow, M Butler, N Cole, M Bending, P Jacobs, AS Nelson. Improved Auto-Segmentation for CT Male Pelvis: Comparison of Deep Learning to Traditional Atlas Segmentation Methods. 2020 Joint AAPM | COMP Virtual Meeting Poster Presentation.
NM Cole*, H Wan, J Niedbala, YK Dewaraja, A Kruzer, D Pittock, C Halley, AS Nelson. Impact of a 3D Convolution Neural Network Method On Liver Segmentation: An Accuracy and Time-Savings Evaluation. 2020 Joint AAPM | COMP Virtual Meeting Poster Presentation.
A Kruzer*, H Wan, M Bending, C Halley, D Darkow, D Pittock, N Cole, P Jacobs, AS Nelson. Comparison of a 3D Convolutional Neural Network Segmentation Method to Traditional Atlas Segmentation for CT Head and Neck Contours. 2020 Joint AAPM | COMP Virtual Meeting Poster Presentation.
Lamba N, Wan H, Kruzer A, et al. Clinical utility of a 3D convolutional neural network kidney segmentation method for radionuclide dosimetry. J NuclMed 2019; 60(Suppl 1): 267.
Hanlin Wan, PhD. Automated Contouring Using Neural Networks. May 2023.
(White Paper)Radiology & Nuclear Medicine
Click on a publication's title to access a PDF or read an abstract.
PET Segmentation
Rohren EM, Etchebehere EC, Araujo JC, Hobbs BP, Swanston NM, Everding M, Moody T, Macapinlac HA. Determination of Skeletal Tumor Burden on 18F-Fluoride PET/CT. J Nucl Med. 2015; 56:1507-1512.
Obara P, Liu H, Wroblewski K, et al. Quantification of metabolic tumor activity and burden in patients with non-small-cell: Is manual adjustment of semi-automatic gradient-based measurements necessary? Nucl Med Commun 2015; 36(8):782-9.
Zhang G, Han D, Ma C, Lu J, Sun T, Liu T, Zhu J, Zhou J, Yin Y. Gradient-based Delineation of the Primary GTV on FLT PET in Squamous Cell Cancer of the Thoracic Esophagus and Impact on Radiotherapy Planning. Radiation Oncology 2015, 10:11.
Sridhar P, Mercier G, Tan J, Truong MT, Daly B, Subramaniam RM. FDG PET Metabolic Tumor Volume Segmentation and Pathologic Volume of Primary Human Solid Tumors. AJR Am J Roentgenol 2014; 202(5):1114-9.
Nelson AS, Faulhaber PF, Pirozzi SD, Harper JW, Piper JW. Comparison of Gradient PET Segmentation from a Multi-Modality PET/CT Measurement Tool to Gradient PET Segmentation Alone. J Nucl Med. 2014; 55 (Supplement 1):1522.
Werner-Wasik M, Nelson D, Choi W, Arai Y, Faulhaber P, Kang P, Almeida F, Xiao Y, Ohri N, Brockway K, Piper J, Nelson A. What is the Best Way to Contour Lung Tumors on PET Scans: Multi-Observer Validation of a Gradient-Based Method Using a NSCLC Digital PET Phantom. IJROBP 2012; 82(3):1164-1171.
Fogh S, Karancke J, Nelson AS, McCue P, Axelrod R, Werner-Wasik W. Pathologic Correlation of PET-CT Based Auto-Contouring for Radiation Planning in Lung Cancer. Presented at the World Conference on Lung Cancer Meeting in 2009.
Werner-Wasik M, Kang P, Choi W, Ohri N, Faulhaber P, Nelson D, Nelson A, Piper J, Shen Z, Pirozzi S. Comparison of PET Contouring Methods in Patients With Early-Stage Resected Non-Small Cell Lung Cancer (NSCLC): A Pathologic–Imaging Correlation IJROBP 2013; 87(2):S540.
Nelson AS, Werner-Wasik M, Choi W, et al. Evaluation of Gradient PET Segmentation for Total Lesion Glycolysis Compared to Thresholds and Manual Contouring. J Nucl Med. 2011; 52 (Supplement 1):2077.
PET Treatment Response
Etchebehere EC, Araujo JC, Fox PS, Swanston NM, Macapinlac HA, Rohren EM. Prognostic Factors in Patients Treated with 223Ra: The Role of Skeletal Tumor Burden on Baseline 18F-Fluoride PET/CT in Predicting Overall Survival. J Nucl Med. 2015; 56:1177-1184.
Yu J, Cooley T, Truong MT, Mercier G, Subramaniam RM. Head and Neck Squamous Cell Cancers (Stages III and IV) Induction Chemotherapy Assessment: Value of FDG Volumetric Imaging Parameters. J Med Imaging Radiat Oncol 2014; 58(1):18-24.
Davison J, Mercier G, Russo G, Subramaniam RM. PET-Based Primary Tumor Volumetric Parameters and Survival of Patients with Non-Small Cell Lung Carcinoma. AJR Am J Roentgenol 2013; 200(3):635-40.
Shah B, Srivastava N, Hirsch AE, et al. Intra-Reader Reliability of FDG PET Volumetric Tumor Parameters: Effects of Primary Tumor Size and Segmentation Methods. Ann Nucl Med. 2012 Nov;26(9):707-14.
Romesser PB, Qureshi MM, Shah BA et al. Superior Prognostic Utility of Gross and Metabolic Tumor Volume Compared to Standardized Uptake Value Using PET/CT in Head and Neck Squamous Cell Carcinoma Patients Treated with Intensity Modulated Radiotherapy. Ann Nucl Med 2012; 26(7):527-34.
Dibble EH, Alvarez AC, Truong MT, et al. 18F-FDG Metabolic Tumor Volume and Total Glycolytic Activity of Oral Cavity and Oropharyngeal Squamous Cell Cancer: Adding Value to Clinical Staging. J Nucl Med 2012; 53(5):709-715.
Liao S, Penney BC, Wroblewski K, et al. Prognostic Value of Metabolic Tumor Burden on 18FFDG PET in Nonsurgical Patients with Non-Small Cell Lung Cancer. Eur J Nucl Med Mol Imaging 2012; 39(1):27-38.
Liao S, Penney BC, Zhang H, et al. Prognostic Value of the Quantitative Metabolic Volumetric Measurement on 18F-FDG PET/CT in Stage IV Nonsurgical Small-Cell Lung Cancer. Acad Radiol 2012; 19(1):69-77.
Morgan R, Chin BB, Lanning R. Feasibility of rapid integrated radiation therapy planning with follow-up FDG PET/CT to improve overall treatment assessment in head and neck cancer. Am J Nucl Med Mol Imaging. 2019 Feb 15;9(1):24-29.
Nelson AD, Nelson AS. MIM® for Therapy Response Evaluation. June 2018. (White Paper)
Neuro & Cardiac
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Neuro
Balhorn, William; Hegedorn (Krawiec), Katherine; Cole, Natalie M. Ph.D.; Haas, Michael; Nelson, Aaron S. MD. Standardizing Quantification of Amyloid PET Using the Centiloid Scale. July 2024.
(White Paper)Breault C, Piper J, Joshi AD, Pirozzi SD, Nelson AS, Lu M, Pontecorvo MJ, Mintun MA, Devous MD. Correlation Between Two Methods of Florbetapir PET Quantitative Analysis. Am J Nucl Med Mol Imaging. 2017 Jul 15;7(3):84-91. eCollection 2017.
Partovi S, Yuh R, Pirozzi S, Lu Z, Couturier S, Grosse U, Schluchter MD, Nelson AS, Jones R, O'Donnell JK, Faulhaber P. Diagnostic Performance of an Automated Analysis Software for the Diagnosis of Alzheimer's Dementia with 18F FDG PET. Am J Nucl Med Mol Imaging. 2017 Jan 15;7(1):12-23. eCollection 2017.
Brown RK, Bohnen NI, Wong KK, Minoshima S, Frey KA. Brain PET in Suspected Dementia: Patterns of Altered FDG Metabolism. Radiographics. 2014 May-Jun; 34(3):684-701.
Piper JW, Nelson AS, Javorek A. Evaluation of a Quantitative Method for Florbetaben (FBB) PET Using SUVR. Oral Presentation EANM Annual Meeting 2014.
Piper JW, Nelson AS, Javorek A. Evaluation of a Novel Quantitative Metric, Volumetric Statistical Amyloid Burden (VSAB), for 18F Florbetapir PET Using a Probabilistic Gray Matter Brain Mask. Oral Presentation EANM Annual Meeting 2014.
Pontecorvo MJ, Arpra Al. Devine M. et al. Potential Value of a Quantitative Estimate of Cortical to Cerebellar SUVr in Aiding Visual Interpretation of Florbetapir PET Scans. Eur J Nucl Med Mol Imaging 2013; 40 (Suppl 2):S143.
Piper JW, Nelson AS, Pirozzi SD, Shen ZL. A Novel Metric of Statistical Amyloid Burden by Comparison to a Database of Health Controls. Oral Presentation RSNA Annual Meeting 2013.
Long Z, Hanson D, Mullan B, Hunt C, Brinkmann B, O’Conner M. Comparison of SISCOM, STATISCOM and MIMneuro for Seizure Localization. J Nucl Med 2016; 57(2):35.
Nelson AS, Harper JW, Pirozzi SD, Piper JW, Nelson AD. Validation of an Automated Subtraction Method Using Ictal and Interictal SPECT to aid in Seizure Localization. J Nucl Med 2013; 54 (Supplement 2):1822.
Nelson AS, Piper JW, Pirozzi SD, Shen ZL. Evaluation of an Automated Atlas-Based Method for DaTscan™ Analysis. J Nucl Med 2013; 54 (Supplement 2):2068.
Piper JW, Nelson AS. Probabilistic Human Brain Atlas: Part 1, a Surrogate for Manual VOI Definition. J Nucl Med. 2008;49 (Supplement 1):378p.
Piper JW, Nelson AS. Probabilistic Human Brain Atlas: Part 2, Validation with ADNI Data. J Nucl Med. 2008;49 (Supplement 1):379p.
Piper JW. Quantitative Comparison of Spatial Normalization Algorithms for 3D PET Brain Scans. J Nucl Med. 2007;48 Suppl 2:S403.
Pontecorvo M, Devous, M, Arora A, et al. Can Incorporation of a Quantitative Estimate of Cortical to Cerebellar SUVr as an Adjunct to Visual Interpretation Improve the Accuracy and Reliability of Florbetapir PET Scan Interpretation? J Nucl Med 2014; 55 (Supplement 1):245.
(White Paper)W. Balhorn, K. Krawiec, N.M. Cole, A.S. Nelson. Standardizing Quantification of Amyloid PET using the Centiloid Scale. March 2022.
Cardiac
Nelson AS, Nelson AD, Pirozzi SD, Piper JW. Validation of a Deformable Atlas-Based Left Ventricular Segmentation Method for PET and SPECT: Comparison to Cardiac Computed Tomography Angiography (CCTA) Volumes. J Nucl Med 2013; 54 (Supplement 2):2075.
Pirozzi SD, Nelson AS, Nelson AD, Piper JW, Traughber BJ, Faulhaber PF, O'Donnell JK, Wojtylak PF. Comparison of QGS, 4D-MSPECT, and MIMcardiac® for the Evaluation of Left Ventricular Functional Parameters for Gated Myocardial SPECT. J Nucl Med 2012 53: 2297.
Nelson AD, Nelson AS, Pirozzi SD, Piper JW. Validation of a Deformable Atlas-Based Left Ventricular Segmentation Method for PET and SPECT: Comparison to Cardiac Computed Tomography Angiography (CCTA) Volumes. 2012.
Y90 Microsphere Dosimetry
Click on a publication's title to access a PDF or read an abstract.
Y90 Literature Syllabus
Y90 Literature Syllabus. May 2020.
Image Reconstruction
Willowson KP, Tapner M, The QUEST Investigator Team, Bailey DL. A Multicentre Comparison of Quantitative Y90 PET/CT for Dosimetric Purposes after Radioembolization with Resin Microspheres. Eur J Nucl Med Mol Imaging 2015; 42:1202-1222.
Siman W, Mikell JK, Kappadath SC. Practical Reconstruction Protocol for Quantitative (90)Y Bremsstrahlung SPECT/CT. Med Phys 2016; 43(9):5093.
Liver Segmentation
Horvat M, Nelson AS, Pirozzi SD. Time Savings of a Multi-Atlas Approach for Liver Segmentation. J Nucl Med. 2014; 55 (Supplement 1):1523.
Horvat M, Nelson AS, Piper JW, Traughber B, Faulhaber P. Time Savings for Liver Volume Generation: Comparison of Manual and Deformable Segmentation Methods. J Nucl Med. 2012; 53 (Suppl 1):2264.
Lung Shunt
Allred JD, Niedbala J, Mikell JK, Owen D, Frey KA, Dewaraja YK. The Value of 99mTc-MAA SPECT/CT for Lung Shunt Estimation in 90Y Radioembolization: a Phantom and Patient Study. EJNMMI Research 2018; 8:50.
Yu N, Srinivas SM, DiFilippo FP, Shrikanthan S, Levitin A, McLennan G, Spain J, Xia P, Wilkinson A. Lung Dose Calculation with SPECT/CT for 90Yttrium Radioembolization of Liver Cancer. IJROBP 2013; 85(3):834-839.
Dose Calculation
Nelson AS, Swallen Dewaraja Y. Evaluation of a Voxel-Based Yttrium-90 (Y-90) Dose Calculation Method for Bremsstrahlung SPECT Using a Liver Phantom. J Nucl Med 2016; 57 (Suppl 2):306 (Oral Presentation).
Nelson AS, Swallen A, Dewaraja Y. Comparison of Voxel-Based Yttrium (Y-90) Dose Calculation Methods for Y-90 PET Using a Liver Phantom. J Nucl Med 2016; 57 (Suppl 2):1424.
Maughan NM, Garcia-Ramierez J, Arpidone M, Swallen A, LaForest R, Goddu SM, Parikh PJ, Zoberi JE. Commissioning of Post-Treatment PET-Based Dosimetry Software for Hepatic Radioembolization with Ytrrium-90 Microspheres. May-June 2017; 16(3):S21.
Balagopal A, Kappadath S. Effect of 90Y Self-Calibration Approaches On Absorbed Dose Quantification Following 90Y-Microsphere Selective Internal Radiation Therapy (90Y-SIRT). Med Phys 2018; 45(2);875-883.
Nelson AS, Swallen A, Arpidone M, Lindner A, et al. Dosimetry for Yttrium-90 Microsphere Brachytherapy. 2023
(White Paper)Deformable Registration
Lamba N, Kruzer A, Pirozzi S, Ginsburg S, Nelson AS. Evaluation of an Intensity-Based Deformable Registration Algorithm for the Generation of Liver Volumes on Post Y90 PET/CT. Accepted for presentation at AAPM 2018.
Nelson AS, Duchateau M, Piper JW, Verellen D, De Ridder M. Evaluation of a Free-Form Intensity Based Deformable Registration Method Using the POPI Model. Med Phys 2014; 41:202.
Pirozzi S, Piper J, Nelson A, Duchateau M, Verellen D, De Ridder M. A Novel Framework for User-Intervened Correction of Deformable Registration. IJROBP 2013; 87(2):S144.
Radiopharmaceutical Therapy
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MRT Literature Syllabus
Personalized Dosimetry for MRT: Why does it Matter?
Eberlein U, Cremonesi M, and Lassmann M. Individualized dosimetry for theranostics: Necessary, nice to have, or counterproductive? J Nucl Med2017; 58(Suppl 2): 97S-103S.
Stabin MG, Madsen MT, and Zaidi H. Personalized dosimetry is a must for appropriate molecular radiotherapy. Med Phys 2019; 46(11): 4713–4716.
Strigari L, Konijnenberg M, Chiesa C, et al. The evidence base for the use of internal dosimetry in the clinical practice of molecular radiotherapy. Eur J Nucl Med Mol Imaging. 2014; 41(10):1976-1988.
Personalized Dosimetry for MRT: How to Achieve it?
Nelson AS, Mirando D, Kruzer A, Niman R, ColeNM, and Stork T. Dosimetry for Targeted Molecular Radiotherapy
(White Paper)Dewaraja YK, Ljungberg M, Green AJ, et al. MIRD pamphlet No. 24:Guidelines for quantitative 131I SPECT in dosimetry applications. J Nucl Med2013; 54(12): 2182-2188.
Sarrut D, Halty A, Badel J, et al. Voxel-based multimodal fitting method for modeling time activity curves in SPECT images. Med Phys 2017; 44(12):6280-6288.
Monte Carlo Absorbed Dose Calculation
Sempau J, Wilderman SJ, Bielajew AF. DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations. Phys Med Biol. 2000;45(8):2263-2291. doi:10.1088/0031-9155/45/8/315
Chetty IJ, Moran JM, McShan DL, Fraass BA, Wilderman SJ, Bielajew AF. Benchmarking of the dose planning method (DPM) Monte Carlo code using electron beams from a racetrack microtron. Med Phys. 2002;29(6):1035-1041. doi:10.1118/1.1481512
Chetty IJ, Moran JM, Nurushev TS, et al. Experimental validation of the DPM Monte Carlo code using minimally scattered electron beams in heterogeneous media. Phys Med Biol. 2002;47(11):1837. doi:10.1088/0031-9155/47/11/301
Dewaraja YK, Wilderman SJ, Ljungberg M, Koral KF, Zasadny K, Kaminiski MS. Accurate dosimetry in 131I radionuclide therapy using patient-specific, 3-dimensional methods for SPECT reconstruction and absorbed dose calculation. J Nucl Med Off Publ Soc Nucl Med. 2005;46(5):840-849.
Chetty IJ, Rosu M, Kessler ML, et al. Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning. Int J Radiat Oncol Biol Phys. 2006;65(4):1249-1259. doi:10.1016/j.ijrobp.2006.03.039
Chetty IJ, Curran B, Cygler JE, et al. Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Med Phys. 2007;34(12):4818-4853. doi:10.1118/1.2795842
Wilderman SJ, Dewaraja YK. Method for Fast CT/SPECT-Based 3D Monte Carlo Absorbed Dose Computations in Internal Emitter Therapy. IEEE Trans Nucl Sci. 2007;54(1):146-151. doi:10.1109/TNS.2006.889164
Dewaraja YK, Mirando DM, Peterson AB, et al. A Pipeline for Automated Voxel Dosimetry: Application in Patients with Multi-SPECT/CT Imaging After 177Lu-Peptide Receptor Radionuclide Therapy. J Nucl Med. 2022;63(11):1665-1672. doi:10.2967/jnumed.121.263738
Van B, Dewaraja YK, Niedbala JT, et al. Experimental validation of Monte Carlo dosimetry for therapeutic beta emitters with radiochromic film in a 3D-printed phantom. Med Phys. 2023;50(1):540-556. doi:10.1002/mp.15926
Quantitative SPECT Reconstruction
Nelson AS and Horstman BP. Quantitative SPECT / CT Reconstruction with SPECTRA TM Quant
Ritt P, Vija H, Hornegger J, et al. Absolute quantification in SPECT. Eur J NuclMed Mol Imaging 2011; 38(Suppl 1): 69–77.
Dewaraja YK, Frey EC, Sgouros G, et al. MIRD Pamphlet No. 23: QuantitativeSPECT for Patient-Specific 3-Dimensional Dosimetry in Internal Radionuclide Therapy. J Nucl Med 2012; 53:1310-1325.
Peters SMB., Meyer Viol SL, van der Werf NR, et al. Variability in lutetium-177 SPECT quantification between different state-of-the-art SPECT/CT systems. EJNMMI Phys 2020; 7(1): 9 (2020).
Moore B, Galt J, Mirando D, Nelson AS, Nye J. Phantom evaluation of a vendor neutral quantitative SPECT/CT reconstruction package. J Nucl Med May 2019 Supplement 1; 60:1359.
Dosimetry for Patient Outcome Prediction and Treatment Planning: Lu-177
Ilan E, Sandström M, Wassberg C, et al. Dose response of pancreatic neuroendocrine tumors treated with peptide receptor radionuclide therapy using 177Lu-DOTATATE. J Nucl Med. 2015; 56(2):177-182.
Del Prete M, Buteau F, Arsenault F, et al. Personalized 177Lu-octreotate peptide receptor radionuclide therapy of neuroendocrine tumours: initial results from the P-PRRT trial. Eur J Nucl Med Mol Imaging 2019; 46: 728‑742.
Mirando D, Dewajara YK, Kruzer A, and Nelson A. Personalized therapy planning for 177Lu-DOTATATE using a kidney-driven dose optimization method. J Nucl Med 2019; 60(Suppl 1): 270.
Mora-Ramirez E, Santoro L, Cassol E, et al. Comparison of commercial dosimetric software platforms in patients treated with 177 Lu-DOTATATE for peptide receptor radionuclide therapy. Med Phys. 2020; 47(9): 4602-4614.
Sundlöv A, Sjögreen-Gleisner K, Svensson J, et al. Individualised 177Lu-DOTATATE treatment of neuroendocrine tumours based on kidney dosimetry. Eur J Nucl Med Mol Imaging 2017; 44(9): 1480–1489.
Sundlöv A, Sjögreen-Gleisner K, Svensson J, et al. Individualised 177Lu-DOTATATE treatment of neuroendocrine tumours based on kidney dosimetry. Eur J Nucl Med Mol Imaging 2017; 44(9): 1480–1489.
Cremonesi M, Ferrari ME, Bodei L, et al. Correlation of dose with toxicity and tumour response to 90Y- and 177Lu-PRRT provides the basis for optimization through individualized treatment planning. Eur J Nucl Med Mol Imaging 2018; 45(13): 2426–2441.
Dosimetry for Patient Outcome Prediction and Treatment Planning: I-131
Flux GD, Haq M, Chittenden SJ, et al. A dose-effect correlation for radioiodine ablation in differentiated thyroid cancer. Eur J Nucl Med Mol Imaging 2010; 37: 270–275.
Gregory RA, Murray I, Gear J, et al. Standardised quantitative radioiodine SPECT/CT Imaging for multicentre dosimetry trials in molecular radiotherapy. Phys Med Biol. 2019; 64(24):245013.
Hybrid SPECT/Planar Dosimetry
Cole NM, Mirando D, Nelson AS, et al. Hybrid SPECT/Planar Dosimetry for Targeted Molecular Radiotherapy
(White Paper)Sjogreen K, Ljunberg M, Strand S. An Activity Quantification Method Based on Registration of CT and Whole-Body Scintillation Camera Images, with Application to 131I. J Nucl Med 2002; 43:972-982.
Siegel JA, Thomas SR, Stubbs JB, Stabin MG, Hays MT, Koral KF, Robertson JS, Howell RW, Wessels BW, Fisher DR, Weber DA, Brill AB. MIRD Pamphlet 16: Techniques for Quantitative Radiopharmaceutical Biodistribution Data Acquisition and Analysis for Use in Human Radiation Dose Estimates. J Nucl Med 1999; 40:37S-61S.
Single Timepoint Dosimetry
Cole NM, Mirando D, Nelson AS. Dosimetry for Targeted Molecular Radiotherapy Using a Single Measurement Timepoint
(White Paper)Hänscheid H, Lapa C, Buck AK, et al. Dose Mapping After Endoradiotherapy with 177Lu-DOTATATE/DOTATOC by a Single Measurement After 4 Days. Nucl Med. 2018; 59(1):75-81.
Garske U, Sandström M, Johansson S, et al. Minor changes in effective half-life during fractionated 177Lu-octreotate therapy. Acta Oncol. 2012; 51(1):86-96.
Willowson KP, Eslick E, Ryu H, et al. Feasibility and accuracy of single time point imaging for renal dosimetry following 177Lu-DOTATATE (‘Lutate’) therapy. EJNMMI Phys. 2018; 5(1):33.
Del Prete M, Arsenault F, Saighi N, et al. Accuracy and reproducibility of simplified QSPECT dosimetry for personalized 177Lu-octreotate PRRT. EJNMMI Phys. 2018; 5(1):25.
Jackson PA, Hofman MS, Hicks RJ, et al. Radiation dosimetry in 177Lu-PSMA-617 therapy using a single post-treatment SPECT/CT: A novel methodology to generate tissue-specific dose factors. J Nucl Med. 2019; 61(6).
