John Kirkpatrick

Overview:

Malignant and benign tumors of the brain, spine and base of skull. Mathematical modelling of tumor metabolism, mass transfer and the response to ionizing radiation. Enhancing clinical outcome in stereotactic radiosurgery, fractionated stereotactic radiotherapy and stereotactic body radiotherapy.

Positions:

Professor of Radiation Oncology

Radiation Oncology
School of Medicine

Professor in Neurosurgery

Neurosurgery
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 1978

Rice University

M.D. 1999

University of Texas Health Science Center San Antonio

Grants:

Validation of Novel Therapeutic Approach for Leptomeningeal Metastases

Administered By
Neurosurgery
Role
Investigator
Start Date
End Date

BMX-001 AS A THERAPEUTIC AGENT FOR TREATMENT OF MULTIPLE BRAIN METASTASES

Administered By
Radiation Oncology
Role
Principal Investigator
Start Date
End Date

Publications:

Beyond an Updated Graded Prognostic Assessment (Breast GPA): A Prognostic Index and Trends in Treatment and Survival in Breast Cancer Brain Metastases From 1985 to Today.

PURPOSE: Brain metastases are a common sequelae of breast cancer. Survival varies widely based on diagnosis-specific prognostic factors (PF). We previously published a prognostic index (Graded Prognostic Assessment [GPA]) for patients with breast cancer with brain metastases (BCBM), based on cohort A (1985-2007, n = 642), then updated it, reporting the effect of tumor subtype in cohort B (1993-2010, n = 400). The purpose of this study is to update the Breast GPA with a larger contemporary cohort (C) and compare treatment and survival across the 3 cohorts. METHODS AND MATERIALS: A multi-institutional (19), multinational (3), retrospective database of 2473 patients with breast cancer with newly diagnosed brain metastases (BCBM) diagnosed from January 1, 2006, to December 31, 2017, was created and compared with prior cohorts. Associations of PF and treatment with survival were analyzed. Kaplan-Meier survival estimates were compared with log-rank tests. PF were weighted and the Breast GPA was updated such that a GPA of 0 and 4.0 correlate with the worst and best prognoses, respectively. RESULTS: Median survival (MS) for cohorts A, B, and C improved over time (from 11, to 14 to 16 months, respectively; P < .01), despite the subtype distribution becoming less favorable. PF significant for survival were tumor subtype, Karnofsky Performance Status, age, number of BCBMs, and extracranial metastases (all P < .01). MS for GPA 0 to 1.0, 1.5-2.0, 2.5-3.0, and 3.5-4.0 was 6, 13, 24, and 36 months, respectively. Between cohorts B and C, the proportion of human epidermal receptor 2 + subtype decreased from 31% to 18% (P < .01) and MS in this subtype increased from 18 to 25 months (P < .01). CONCLUSIONS: MS has improved modestly but varies widely by diagnosis-specific PF. New PF are identified and incorporated into an updated Breast GPA (free online calculator available at brainmetgpa.com). The Breast GPA facilitates clinical decision-making and will be useful for stratification of future clinical trials. Furthermore, these data suggest human epidermal receptor 2-targeted therapies improve clinical outcomes in some patients with BCBM.
Authors
Sperduto, PW; Mesko, S; Li, J; Cagney, D; Aizer, A; Lin, NU; Nesbit, E; Kruser, TJ; Chan, J; Braunstein, S; Lee, J; Kirkpatrick, JP; Breen, W; Brown, PD; Shi, D; Shih, HA; Soliman, H; Sahgal, A; Shanley, R; Sperduto, W; Lou, E; Everett, A; Boggs, DH; Masucci, L; Roberge, D; Remick, J; Plichta, K; Buatti, JM; Jain, S; Gaspar, LE; Wu, C-C; Wang, TJC; Bryant, J; Chuong, M; Yu, J; Chiang, V; Nakano, T; Aoyama, H; Mehta, MP
MLA Citation
Sperduto, Paul W., et al. “Beyond an Updated Graded Prognostic Assessment (Breast GPA): A Prognostic Index and Trends in Treatment and Survival in Breast Cancer Brain Metastases From 1985 to Today.Int J Radiat Oncol Biol Phys, vol. 107, no. 2, June 2020, pp. 334–43. Pubmed, doi:10.1016/j.ijrobp.2020.01.051.
URI
https://scholars.duke.edu/individual/pub1433227
PMID
32084525
Source
pubmed
Published In
Int J Radiat Oncol Biol Phys
Volume
107
Published Date
Start Page
334
End Page
343
DOI
10.1016/j.ijrobp.2020.01.051

Retrospective quality metrics review of stereotactic radiosurgery plans treating multiple targets using single-isocenter volumetric modulated arc therapy.

To characterize key plan quality metrics in multi-target stereotactic radiosurgery (SRS) plans treated using single-isocenter volumetric modulated arc therapy (VMAT) in comparison to dynamic conformal arc (DCA) plans treating single target. To investigate the feasibility of quality improvement in VMAT planning based on previous planning knowledge. 97 VMAT plans of multi-target and 156 DCA plans of single-target treated in 2017 at a single institution were reviewed. A total of 605 targets were treated with these SRS plans. The prescription dose was normalized to 20 Gy in all plans for this analysis. Two plan quality metrics, target conformity index (CI) and normal tissue volume receiving more than 12 Gy (V12Gy), were calculated for each target. The distribution of V12Gy per target was plotted as a function of the target volume. For multi-target VMAT plans, the number of targets being treated in the same plan and the distance between targets were calculated to evaluate their impact on V12Gy. VMAT plans that had a large deviation of V12Gy from the average level were re-optimized to determine the possibility of reducing the variation of V12Gy in VMAT planning. Conformity index of multi-target VMAT plans were lower than that of DCA plans while the mean values of 12 Gy were comparable. The V12Gy for a target in VMAT plan did not show apparent dependence on the total number of targets or the distance between targets. The distribution of V12Gy exhibited a larger variation in VMAT plans compared to DCA plans. Re-optimization of outlier plans reduced V12 Gy by 33.9% and resulted in the V12Gy distribution in VMAT plans more closely resembling that of DCA plans. The benchmark data on key plan quality metrics were established for single-isocenter multi-target SRS planning. It is feasible to use this knowledge to guide VMAT planning and reduce high V12Gy outliers.
Authors
MLA Citation
Cui, Yunfeng, et al. “Retrospective quality metrics review of stereotactic radiosurgery plans treating multiple targets using single-isocenter volumetric modulated arc therapy.Journal of Applied Clinical Medical Physics, Apr. 2020. Epmc, doi:10.1002/acm2.12869.
URI
https://scholars.duke.edu/individual/pub1436642
PMID
32239746
Source
epmc
Published In
Journal of Applied Clinical Medical Physics
Published Date
DOI
10.1002/acm2.12869

Current multidisciplinary management of brain metastases.

Brain metastasis (BM), the most common adult brain tumor, develops in 20% to 40% of patients with late-stage cancer and traditionally are associated with a poor prognosis. The management of patients with BM has become increasingly complex because of new and emerging systemic therapies and advancements in radiation oncology and neurosurgery. Current therapies include stereotactic radiosurgery, whole-brain radiation therapy, surgical resection, laser-interstitial thermal therapy, systemic cytotoxic chemotherapy, targeted agents, and immune-checkpoint inhibitors. Determining the optimal treatment for a specific patient has become increasingly individualized, emphasizing the need for multidisciplinary discussions of patients with BM. Recognizing and addressing the sequelae of BMs and their treatment while maintaining quality of life and neurocognition is especially important because survival for patients with BMs has improved. The authors present current and emerging treatment options for patients with BM and suggest approaches for managing sequelae and disease recurrence.
Authors
MLA Citation
Moravan, Michael J., et al. “Current multidisciplinary management of brain metastases.Cancer, vol. 126, no. 7, Apr. 2020, pp. 1390–406. Pubmed, doi:10.1002/cncr.32714.
URI
https://scholars.duke.edu/individual/pub1428070
PMID
31971613
Source
pubmed
Published In
Cancer
Volume
126
Published Date
Start Page
1390
End Page
1406
DOI
10.1002/cncr.32714

An investigation of machine learning methods in delta-radiomics feature analysis.

PURPOSE: This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the effectiveness of machine learning methods for delta-radiomics feature selection and building classification models. METHODS: The pre-treatment, one-week post-treatment, and two-month post-treatment T1 and T2 fluid-attenuated inversion recovery (FLAIR) MRI were acquired. 61 radiomic features (intensity histogram-based, morphological, and texture features) were extracted from the gross tumor volume in each image. Delta-radiomics were calculated between the pre-treatment and post-treatment features. Univariate Cox regression and 3 multivariate machine learning methods (L1-regularized logistic regression [L1-LR], random forest [RF] or neural networks [NN]) were used to select a reduced number of features, and 7 machine learning methods (L1-LR, L2-LR, RF, NN, kernel support vector machine [KSVM], linear support vector machine [LSVM], or naïve bayes [NB]) was used to build classification models for predicting OS. The performances of the total 21 model combinations built based on single-time-point radiomics (pre-treatment, one-week post-treatment, and two-month post-treatment) and delta-radiomics were evaluated by the area under the receiver operating characteristic curve (AUC). RESULTS: For a small cohort of 12 patients, delta-radiomics resulted in significantly higher AUC than pre-treatment radiomics (p-value<0.01). One-week/two-month delta-features resulted in significantly higher AUC (p-value<0.01) than the one-week/two-month post-treatment features, respectively. 18/21 model combinations were with higher AUC from one-week delta-features than two-month delta-features. With one-week delta-features, RF feature selector + KSVM classifier and RF feature selector + NN classifier showed the highest AUC of 0.889. CONCLUSIONS: The results indicated that delta-features could potentially provide better treatment assessment than single-time-point features. The treatment assessment is substantially affected by the time point for computing the delta-features and the combination of machine learning methods for feature selection and classification.
Authors
MLA Citation
Chang, Yushi, et al. “An investigation of machine learning methods in delta-radiomics feature analysis.Plos One, vol. 14, no. 12, 2019, p. e0226348. Pubmed, doi:10.1371/journal.pone.0226348.
URI
https://scholars.duke.edu/individual/pub1423241
PMID
31834910
Source
pubmed
Published In
Plos One
Volume
14
Published Date
Start Page
e0226348
DOI
10.1371/journal.pone.0226348

Recurrent Extradural Myxopapillary Ependymoma With Oligometastatic Spread.

Myxopapillary ependymomas are a slow-growing, grade I type glial tumor in the lumbosacral region. More rarely, they can present as extradural, subcutaneous sacrococcygeal, or perisacral masses, and it is under these circumstances that they are more likely to spread. Here, we report the presentation of a sacrococcygeal mass in patient that was initially resected confirming extradural myxopapillary ependymoma. At initial resection, multiple small pulmonary nodules were detected. This mass recurred 2 years later at the resection site with an interval increase in the previously imaged pulmonary nodules. Resection of both the post-sacral mass and largest lung metastasis confirmed recurrent myxopapillary ependymoma with oligometastatic spread. Because these tumors are rare, with extradural presentation being even more infrequent, to this date there are no definitive therapeutic guidelines for initial treatment and continued surveillance. For myxopapillary ependymoma, current standard of care is first-line maximal surgical resection with or without postoperative radiotherapy depending on the extent of disease and extent of resection. However, there remains insufficient evidence on the role of radiotherapy to oligometastatic foci in providing any further survival benefit or extending time to recurrence. Thus, prospective studies assessing the role of upfront treatment of oligometastases with local resection and adjuvant radiotherapy are needed for improved understanding of extradural myxopapillary ependymoma.
Authors
Batich, KA; Riedel, RF; Kirkpatrick, JP; Tong, BC; Eward, WC; Tan, CL; Pittman, PD; McLendon, RE; Peters, KB
MLA Citation
Batich, Kristen A., et al. “Recurrent Extradural Myxopapillary Ependymoma With Oligometastatic Spread.Front Oncol, vol. 9, 2019, p. 1322. Pubmed, doi:10.3389/fonc.2019.01322.
URI
https://scholars.duke.edu/individual/pub1424463
PMID
31850213
Source
pubmed
Published In
Frontiers in Oncology
Volume
9
Published Date
Start Page
1322
DOI
10.3389/fonc.2019.01322