Patrick Codd

Positions:

Assistant Professor of Neurosurgery

Neurosurgery
School of Medicine

Assistant Professor in the Department of Mechanical Engineering and Materials Science

Mechanical Engineering and Materials Science
Pratt School of Engineering

Assistant Professor in Head & Neck Surgery & Communication Sciences

Head and Neck Surgery & Communication Sciences
School of Medicine

Core Faculty in Innovation & Entrepreneurship

Duke Innovation & Entrepreneurship
Institutes and Provost's Academic Units

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

M.D. 2008

Harvard Medical School

General Surgery Intern, General Surgery

Massachusetts General Hospital

Neurosurgery Resident, Surgery

Massachusetts General Hospital

Grants:

Augmented Reality Assisted Placement of External Ventricular Drain

Administered By
Neurosurgery
Awarded By
American Association of Neurological Surgeons
Role
Principal Investigator
Start Date
End Date

Publications:

RFID Track for Tray Optimization: An Instrument Utilization Pilot Study in Surgical Oncology.

BACKGROUND: Surgical instrument tray reduction attempts to minimize intraoperative inefficiency and processing costs. Previous reduction methods relied on trained observers manually recording instrument use (i.e. human ethnography), and surgeon and/or staff recall, which are imprecise and inherently limited. We aimed to determine the feasibility of radiofrequency identification (RFID)-based intraoperative instrument tracking as an effective means of instrument reduction. METHODS: Instrument trays were tagged with unique RFID tags. A RFID reader tracked instruments passing near RFID antennas during 15 breast operations performed by a single surgeon; ethnography was performed concurrently. Instruments without recorded use were eliminated, and 10 additional cases were performed utilizing the reduced tray. Logistic regression was used to estimate odds of instrument use across cases. Cohen's Kappa estimated agreement between RFID and ethnography. RESULTS: Over 15 cases, 37 unique instruments were used (median 23 instruments/case). A mean 0.64 (median = 0, range = 0-3) new instruments were added per case; odds of instrument use did not change between cases (OR = 1.02, 95%CI 1.00-1.05). Over 15 cases, all instruments marked as used by ethnography were recorded by RFID tracking; 7 RFID-tracked instruments were never recorded by ethnography. Tray size was reduced 40%. None of the 25 eliminated instruments were required in 10 subsequent cases. Cohen's Kappa comparing RFID data and ethnography over all cases was 0.82 (95%CI 0.79-0.86), indicating near perfect agreement between methodologies. CONCLUSIONS: Intraoperative RFID instrument tracking is a feasible, data-driven method for surgical tray reduction. Overall, RFID tracking represents a scalable, systematic, and efficient method of optimizing instrument supply across procedures.
Authors
Olivere, LA; Hill, IT; Thomas, SM; Codd, PJ; Rosenberger, LH
MLA Citation
Olivere, Lindsey A., et al. “RFID Track for Tray Optimization: An Instrument Utilization Pilot Study in Surgical Oncology.J Surg Res, vol. 264, Apr. 2021, pp. 490–98. Pubmed, doi:10.1016/j.jss.2021.02.049.
URI
https://scholars.duke.edu/individual/pub1480386
PMID
33857793
Source
pubmed
Published In
J Surg Res
Volume
264
Published Date
Start Page
490
End Page
498
DOI
10.1016/j.jss.2021.02.049

Radiofrequency Identification Tracking for Tray Optimization: An Instrument Use Pilot Study in Breast Surgical Oncology

Authors
Olivere, LA; Hill, I; Thomas, SM; Codd, PJ; Rosenberger, LH
MLA Citation
Olivere, Lindsey A., et al. “Radiofrequency Identification Tracking for Tray Optimization: An Instrument Use Pilot Study in Breast Surgical Oncology.” Journal of the American College of Surgeons, vol. 231, no. 4, 2020, pp. S147–S147.
URI
https://scholars.duke.edu/individual/pub1468278
Source
wos-lite
Published In
Journal of the American College of Surgeons
Volume
231
Published Date
Start Page
S147
End Page
S147

In Reply to the Letter to the Editor Regarding "Enhancing Reality: A Systematic Review of Augmented Reality in Neuronavigation and Education".

Authors
Rahimpour, S; Cho, J; Goodwin, CR; Codd, P
MLA Citation
Rahimpour, Shervin, et al. “In Reply to the Letter to the Editor Regarding "Enhancing Reality: A Systematic Review of Augmented Reality in Neuronavigation and Education".World Neurosurg, vol. 140, Aug. 2020, p. 432. Pubmed, doi:10.1016/j.wneu.2020.05.253.
URI
https://scholars.duke.edu/individual/pub1456200
PMID
32797958
Source
pubmed
Published In
World Neurosurg
Volume
140
Published Date
Start Page
432
DOI
10.1016/j.wneu.2020.05.253

Characterization of photoablation versus incidence angle in soft tissue laser surgery: An experimental phantom study

The removal of tissue with a laser scalpel is a complex process that is affected by the laser incidence angle on the surface of the tissue. Current models of laser ablation, however, do not account for the angle of incidence, assuming that it is always normal to the surface. In order to improve ablation modeling in soft tissue, this work characterizes photoablation crater profiles at incidence angles ranging from 0 degrees to 45 degrees off perpendicular. Simulated results, based on a discretized steady-state ablation model, are generated for comparison based on the assumption that material removal occurs in the direction of the laser. Experiments in an agarose-based, homogeneous soft tissue phantom are performed with a carbon dioxide (CO ) laser. Surface profiles of the craters are acquired using a micro x-ray computed tomography scanner (Micro-CT) and compared to results from the simulation. The difference of the simulated and experimental results are measured and the error analysis is reported. 2
Authors
Ma, G; Ross, W; Tucker, M; Codd, P
MLA Citation
Ma, G., et al. “Characterization of photoablation versus incidence angle in soft tissue laser surgery: An experimental phantom study.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 11238, 2020. Scopus, doi:10.1117/12.2546229.
URI
https://scholars.duke.edu/individual/pub1435986
Source
scopus
Published In
Progress in Biomedical Optics and Imaging Proceedings of Spie
Volume
11238
Published Date
DOI
10.1117/12.2546229

Creation of a non-contact, automated brain tumor detection device for use in brain tumor resection

The ability to differentiate healthy and tumorous tissue is vital during the surgical removal of tumors. This ability is especially critical during neurosurgical tumor resection due to the risk associated with removing healthy brain tissue. In this paper, we present an epifluorescence spectroscopy guided device that is not only capable of autonomously classifying a region of tissue as tumorous or healthy in real-time-but is also able to differentiate between different tumor types. For this study, glioblastoma and melanoma were chosen as the two different tumor types. Six mice were utilized in each of the three classes (healthy, glioblastoma, melanoma) for a total of eighteen mice. A "one-vs-the-all" approach was used to create a multi-class classifier. The multi-class classifier was capable of classifying with 100% accuracy. Future work includes increasing the number of mice in each of the three tumor classes to create a more robust classifier and expanding the number of tumor types beyond glioblastoma and melanoma.
Authors
Tucker, MB; Joseph, S; Ross, W; Ma, G; Chongsathidkiet, P; Fecci, P; Codd, P
MLA Citation
Tucker, M. B., et al. “Creation of a non-contact, automated brain tumor detection device for use in brain tumor resection.” Progress in Biomedical Optics and Imaging  Proceedings of Spie, vol. 11225, 2019. Scopus, doi:10.1117/12.2546603.
URI
https://scholars.duke.edu/individual/pub1435965
Source
scopus
Published In
Progress in Biomedical Optics and Imaging Proceedings of Spie
Volume
11225
Published Date
DOI
10.1117/12.2546603