Blood Flow Measurements Enable Optimization of Light Delivery for Personalized Photodynamic Therapy
Abstract
:1. Introduction
2. Materials and Methods
2.1. Tumor Models/PDT
2.2. Diffuse Correlation Spectroscopy
2.2.1. DCS Instrumentation
2.2.2. Tumor Blood Flow Monitoring
2.3. Illumination Schemes
- 150 mWcm−2-continuous: Continuous illumination at high irradiance of 150 mWcm−2 for 15 min.
- 25 mWcm−2-continuous: Continuous illumination at low irradiance of 25 mWcm−2 for 90 min.
- 150 mWcm−2-fractionated: 150 mWcm−2 in equal intermittent intervals of 30 s light-on and 30 s light-off for a total of 30 min.
- Blood-flow-informed-irradiance (BFI-Irrad): Continuous illumination was initially 150 mWcm−2, but illumination was cyclically decreased to 25 mWcm−2 and returned to 150 mWcm−2 in response to the blood flow monitoring parameters. Treatment time was adjusted to deliver a total fluence of 135 Jcm−2 (between 15 and 90 min).
- Blood-flow-informed-fractionated (BFI-Frac): Fractionated illumination was initiated at 150 mWcm−2, but illumination was intermittently discontinued (light-off, 0 mWcm−2) in response to blood flow monitoring. Treatment time was adjusted to deliver a total fluence of 135 Jcm−2, which was reached within 90 min in the current investigations. Note, this guidance platform requires a maximum treatment time to be established irrespective of whether or not a total fluence of 135 Jcm−2 is achieved because the light can remain “off” for extended periods of time if blood flow recovery is slow.
2.4. In Vivo/In Vitro Clonogenic Assay
2.5. Tumor Oxygenation Measurements
2.6. Statistical Analysis
3. Results
3.1. Irradiance Alters Tumor Blood Flow During PDT
3.2. BFI-PDT Alters Flow Dynamics during Illumination Compared to Standard PDT
3.3. BFI-PDT Decreases Blood Flow Reduction Rate during Light Delivery, While Shortening Treatment Time
3.4. BFI-PDT Alters Mechanisms of PDT Effect on Vascular Damage
3.5. BFI-PDT Improves Therapeutic Outcome
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Type of PDT | Group | Flow Reduction Rate (%rBFmin−1) Median (IQR) | Treatment Length in mMminutes Median (IQR) | ΔrBF(%) at 1 h after PDT Mean (SD) | |||
---|---|---|---|---|---|---|---|
150 mWcm−2 | 25 mWcm−2 | 0 mWcm−2 | Total | ||||
Standard | 150 mWcm−2 continuous | 23.0 (21.4, 49.8) | 15 | 0 | 0 | 15 | 24.8 (67.3) |
25 mWcm−2 continuous | 9.3 (7.8, 11.6) (p < 0.0011) | 0 | 90 | 0 | 90 | −46.2 (23.7) (p = 0.001 1) | |
150 mWcm−2 fractionated | 25.0 (14.9 34,6) (p = 0.0022) | 15 | 0 | 15 | 30 | −32.2 (31.3) (p = 0.018 1) | |
Blood-flow informed | BFI-Irrad | 5.2 (4.6, 5.4) (p < 0.001 1,3, p = 0.0012) | 8 (7, 9) | 45 (39, 50) | 0 | 53 (48, 57) | −31.4 (19.7) (p = 0.016 1) |
BFI-Frac | 10.0 (6.7, 10.2) (p < 0.001 1,3) | 15 | 0 | 46 (34, 55) | 61 (49, 70) | −43.6 (29.0) (p = 0.002 1) |
Group | Flow Reduction Rate (%rBFmin−1) Median (IQR) | Treatment Length in Minutes Median (IQR) | ΔrBF(%) at 1 h after PDT Mean (SD) | |||
---|---|---|---|---|---|---|
150 mWcm−2 | 25 mWcm−2 | 0 mWcm−2 | Total | |||
150 mWcm−2-continuous | 20.7 (15.5, 32.6) | 15 | 0 | 0 | 15 | −10.7 (21.6) |
25 mWcm−2-continuous | 13.4 (11.9, 16.8) | 0 | 90 | 0 | 90 | −56.6 (18.6) (p = 0.001 1) |
BFI-Irrad | 6.0 (3.7, 12.1) (p = 0.004 1, p = 0.04 2) | 11 (9, 14) | 27 (9, 36) | 0 | 37 (23, 45) | −58.5 (15.3) (p = 0.001 1) |
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Ong, Y.H.; Miller, J.; Yuan, M.; Chandra, M.; El Khatib, M.; Vinogradov, S.A.; Putt, M.E.; Zhu, T.C.; Cengel, K.A.; Yodh, A.G.; et al. Blood Flow Measurements Enable Optimization of Light Delivery for Personalized Photodynamic Therapy. Cancers 2020, 12, 1584. https://doi.org/10.3390/cancers12061584
Ong YH, Miller J, Yuan M, Chandra M, El Khatib M, Vinogradov SA, Putt ME, Zhu TC, Cengel KA, Yodh AG, et al. Blood Flow Measurements Enable Optimization of Light Delivery for Personalized Photodynamic Therapy. Cancers. 2020; 12(6):1584. https://doi.org/10.3390/cancers12061584
Chicago/Turabian StyleOng, Yi Hong, Joann Miller, Min Yuan, Malavika Chandra, Mirna El Khatib, Sergei A. Vinogradov, Mary E. Putt, Timothy C. Zhu, Keith A. Cengel, Arjun G. Yodh, and et al. 2020. "Blood Flow Measurements Enable Optimization of Light Delivery for Personalized Photodynamic Therapy" Cancers 12, no. 6: 1584. https://doi.org/10.3390/cancers12061584