Translational Neurosurgery
- 1st Edition - January 1, 2026
- Imprint: Academic Press
- Editors: Adam E.M. Eltorai, Jeffrey A. Bakal, Maleeha Ahmad
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 5 0 9 - 1
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 5 2 3 - 7
Translational Neurosurgery provides a comprehensive overview reflecting the depth and breadth of the field of translational research focused on neurosurgery, with input from a dist… Read more
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Translational Neurosurgery provides a comprehensive overview reflecting the depth and breadth of the field of translational research focused on neurosurgery, with input from a distinguished team of basic and clinical investigators. It covers the principles of evidence-based medicine and applies these principles to the design of translational investigations, helping researchers navigate challenging considerations in study design and implementation.
This book is a valuable resource for neurosurgeons and neurosurgery investigators who want to understand more about translational research, and also for basic scientists interested in translating their research into clinical practice.
This book is a valuable resource for neurosurgeons and neurosurgery investigators who want to understand more about translational research, and also for basic scientists interested in translating their research into clinical practice.
- Focuses on the principles of evidence-based medicine and applies these principles to the design of translational investigations within neurosurgery
- Provides a practical, straightforward approach that helps investigators navigate challenging considerations in study design and implementation
- Includes valuable discussions of the critical appraisal of published studies in translational neurosurgery and provides specific examples from the recent literature
Clinicians, neurosurgeons, neurosurgery investigators, basic scientists interested in translating their research into clinical practice
Section 1: Introduction
1. Translational Process
2. Scientific Method
Section 2: Pre-Clinical
4. What problem are you solving?
5. Types of interventions
6. Drug testing
7. Device discovery and prototyping
8. Diagnostic testing
9. Artificial Intelligence
Section 3: Statistical Principles
10. Basic statistical principles
11. Distributions
12. Hypotheses and error types
13. Power
14. Continuous variable analyses
15. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel
16. Analysis of variance
17. Correlation
18. Basic science statistics
19. Sample Size
20. Statistical Software
Section 4: Clinical: Study Types
21. Outcome measurements: What data is being collected and why?
22. Case series: Design, measures, classic example
23. Case-control study: Design, measures, classic example
24. Cross-section study: Design, measures, classic example
25. Longitudinal study: Design, measures, classic example
26. Meta-analysis: Design, measures, classic example
27. Qualitative methods and mixed methods
Section 5: Clinical Trials
28. Randomization and Multicentric Considerations in Clinical Trials
29. Nonrandomized Control
30. Historical Control
31. Study Types with Design, Measures, Classic Example
32. Blinding: Who and How?
33. Adaptive: Design, measures, classic example
34. Phase 0 Trials: Window of Opportunity
35. Registries, Phases of Clinical Trials, IDEAL Framework
Section 6: Regulatory Basics
36. FDA overview
37. IND
38. Devices
39. Radiation-emitting Electronic Products
40. Biologics
41. Combination Products
42. A Brief Overview of the FDAs Involvement in the Regulation of Dietary Supplements
43. Cosmetics
44. CMC and GxP
45. Non-US regulatory
46. Post-Market Drug Safety Monitoring
47. Post-Market Device Safety Monitoring
Section 7: Public Health
48. Public Health
49. Epidemiology
50. Factors
51. Good Questions
52. Population- and Environmental-specific Considerations
53. Healthcare Institutions and Systems
54. Public Health Institutions and Systems
55. Presenting Data
1. Translational Process
2. Scientific Method
Section 2: Pre-Clinical
4. What problem are you solving?
5. Types of interventions
6. Drug testing
7. Device discovery and prototyping
8. Diagnostic testing
9. Artificial Intelligence
Section 3: Statistical Principles
10. Basic statistical principles
11. Distributions
12. Hypotheses and error types
13. Power
14. Continuous variable analyses
15. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel
16. Analysis of variance
17. Correlation
18. Basic science statistics
19. Sample Size
20. Statistical Software
Section 4: Clinical: Study Types
21. Outcome measurements: What data is being collected and why?
22. Case series: Design, measures, classic example
23. Case-control study: Design, measures, classic example
24. Cross-section study: Design, measures, classic example
25. Longitudinal study: Design, measures, classic example
26. Meta-analysis: Design, measures, classic example
27. Qualitative methods and mixed methods
Section 5: Clinical Trials
28. Randomization and Multicentric Considerations in Clinical Trials
29. Nonrandomized Control
30. Historical Control
31. Study Types with Design, Measures, Classic Example
32. Blinding: Who and How?
33. Adaptive: Design, measures, classic example
34. Phase 0 Trials: Window of Opportunity
35. Registries, Phases of Clinical Trials, IDEAL Framework
Section 6: Regulatory Basics
36. FDA overview
37. IND
38. Devices
39. Radiation-emitting Electronic Products
40. Biologics
41. Combination Products
42. A Brief Overview of the FDAs Involvement in the Regulation of Dietary Supplements
43. Cosmetics
44. CMC and GxP
45. Non-US regulatory
46. Post-Market Drug Safety Monitoring
47. Post-Market Device Safety Monitoring
Section 7: Public Health
48. Public Health
49. Epidemiology
50. Factors
51. Good Questions
52. Population- and Environmental-specific Considerations
53. Healthcare Institutions and Systems
54. Public Health Institutions and Systems
55. Presenting Data
- Edition: 1
- Published: January 1, 2026
- Imprint: Academic Press
- Language: English
AE
Adam E.M. Eltorai
Adam E. M. Eltorai, MD, PhD completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University. His work has spanned the translational spectrum with a focus on medical technology innovation and development. Dr. Eltorai has published numerous articles and books.
Affiliations and expertise
Harvard Medical School, Boston, MA, USAJB
Jeffrey A. Bakal
Jeff Bakal PhD, P.Stat. is the Program Director for Provincial Research Data Services at Alberta Health Services which operates the Alberta Strategy for Patient Oriented Research (SPOR) data platform and Health Service Statistical & Analytics Methods teams. He has over 10 years of experience working with Health Services data and Randomized Clinical Trials. He completed his PhD jointly with the Department of Mathematics and Statistics and the School of Physical Health and Education at Queen's University. He has worked on the methodology and analysis of several international studies in business strategy, ophthalmology, cardiology, geriatric medicine and the analysis of kinematic data resulting in several peer reviewed articles and conference presentations. His current interests are in developing statistical methodology for time-to-event data and the development of classification tools to assist in patient decision making processes.
Affiliations and expertise
Division General Internal Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton Alberta, CanadaMA
Maleeha Ahmad
Maleeha Ahmad, MD, FRCS, FACS is a neurosurgeon with advanced fellowships spanning skull base, neurosurgical oncology, and stereotactic radiosurgery. Her work bridges the operating room, neurosurgical systems design, and the frontier of intelligent healthcare. With over a decade of expertise and more than 1,000 citations to her peer-reviewed publications, she is recognized as an authority in translational neurosurgery, with leadership across clinical trials, academic service lines, and editorial roles in leading neurosurgical publications. Having worked both within and beyond traditional academic silos—including ten years in academic medicine—she brings an outcomes-driven perspective shaped by high-volume integrated care systems. Her current focus lies in translating data-rich insights—from artificial intelligence and radiogenomics to global health frameworks—into advanced, safe, and patient-centric neurosurgical decision-making. As Lead Book Editor of Translational Neurosurgery, she curates this volume as a blueprint for the discipline’s next evolutionary leap.
Affiliations and expertise
UHS and HCA Healthcare Systems, Riverside, California, USA