In Vitro, Ex Vivo and In Vivo Isotherms for Renal Cryotherapy
Jennifer L. YoungSurendra B. KollaDonald L. PickPetros SountoulidesOskar Grau KaufmannCervando Ortiz–VanderdysVictor HuynhAdam G. KaplanLorena AndradeKathryn OsannMichael K. LouieElspeth M. McDougallRalph V. Clayman
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No AccessJournal of UrologyInvestigative Urology1 Feb 2010In Vitro, Ex Vivo and In Vivo Isotherms for Renal Cryotherapyis companion ofUnintended Consequences of Laparoscopic Surgery on Partial Nephrectomy for Kidney Cancer Jennifer L. Young, Surendra B. Kolla, Donald L. Pick, Petros Sountoulides, Oskar G. Kaufmann, Cervando G. Ortiz-Vanderdys, Victor B. Huynh, Adam G. Kaplan, Lorena A. Andrade, Kathryn E. Osann, Michael K. Louie, Elspeth M. McDougall, and Ralph V. Clayman Jennifer L. YoungJennifer L. Young , Surendra B. KollaSurendra B. Kolla , Donald L. PickDonald L. Pick , Petros SountoulidesPetros Sountoulides , Oskar G. KaufmannOskar G. Kaufmann , Cervando G. Ortiz-VanderdysCervando G. Ortiz-Vanderdys , Victor B. HuynhVictor B. Huynh , Adam G. KaplanAdam G. Kaplan , Lorena A. AndradeLorena A. Andrade , Kathryn E. OsannKathryn E. Osann , Michael K. LouieMichael K. Louie , Elspeth M. McDougallElspeth M. McDougall , and Ralph V. ClaymanRalph V. Clayman View All Author Informationhttps://doi.org/10.1016/j.juro.2009.09.072AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract Purpose: Preoperative planning for renal cryotherapy is based on isotherms established in gel. We replicated gel isotherms and correlated them with ex vivo and in vivo isotherms in a porcine model. Materials and Methods: PERC-17 CryoProbes™ (1.7 mm) and IceRods™ (1.47 mm) underwent trials in gel, ex vivo and in vivo porcine kidneys. Temperatures were recorded at 13 predetermined locations with multipoint thermal sensors. Results: At the cryoprobe temperatures were not significantly different along the probe in any medium for either system (p = 0.0947 to 0.9609). However, away from the probe ex vivo and in vivo trials showed warmer temperatures toward the cryoprobe tip for each system (p = 0.0003 to 0.2141). Mean ± SE temperature 5 mm distal to the cryoprobe tip in vivo was 19.2C ± 16.1C for CryoProbes and 27.3C ± 11.2C for IceRods. Temperatures were consistently colder with CryoProbes than with IceRods in gel (p <0.00005), ex vivo (p <0.00005) and in vivo (p = 0.0014). At almost all sites temperatures were significantly colder in gel and in ex vivo kidney than in in vivo kidney for CryoProbes (p = 0.0107 and 0.0008, respectively) and for IceRods (each p <0.00005). Conclusions: Gel and ex vivo isotherms do not predict the in vivo pattern of freezing. Thus, they should not be used for preoperative planning. The cryoprobe should be passed 5 mm beyond the tumor border to achieve suitably cold temperatures. Multipoint thermal sensor probes are recommended to record actual temperature during renal cryotherapy. References 1 : Global increases in kidney cancer incidence, 1973–1992. Eur J Cancer Prev2002; 11: 171. Google Scholar 2 : The natural history of incidentally detected small renal masses. Cancer2004; 100: 738. Google Scholar 3 : Independent validation of the 2002 American Joint Committee on Cancer primary tumor classification for renal cell carcinoma using a large, single institution cohort. J Urol2005; 173: 1889. Link, Google Scholar 4 : The natural history of observed enhancing renal masses: meta-analysis and review of the world literature. J Urol2006; 175: 425. Link, Google Scholar 5 : Watchful waiting for solid renal masses: insight into the natural history and results of delayed intervention. J Urol2007; 177: 466. Link, Google Scholar 6 : Renal cryotherapy: a detailed review including a 5-year follow-up. BJU Int2007; 99: 1265. Google Scholar 7 : Excise, ablate or observe: the small renal mass dilemma—a meta-analysis and review. J Urol2008; 179: 1227. Link, Google Scholar 8 : Laparoscopic renal cryoablation: oncologic outcomes at 5 years. J Endourol2006; 20: A12. abstract. Google Scholar 9 : A pig model of hepatic cryotherapy: In vivo temperature distribution during freezing and histopathological changes. Cryobiology2003; 47: 214. Google Scholar 10 : Cryosurgical effects on growing vessels. Am Surg1999; 65: 677. Google Scholar 11 : Numerical solution of multidimensional freezing problem during cryosurgery. ASME-JBME1998; 120: 32. Google Scholar 12 : Rate of lesion growth around spherical and cylindrical cryoprobes. Cryobiology1971; 7: 183. Google Scholar 13 : Cryosurgical changes in the porcine kidney: histologic analysis with thermal history correlation. Cryobiology2002; 45: 167. Google Scholar 14 : Effect of freezing parameters (freeze cycle and thaw process) on tissue destruction following renal cryoablation. J Endourol2002; 16: 519. Google Scholar 15 : Effect of freeze time during renal cryoablation: a swine model. J Endourol2006; 20: 1101. Google Scholar 16 : In vivo efficacy of laparoscopic assisted percutaneous renal cryotherapy: evidence based guidelines for the practicing urologist. J Urol2008; 179: 333. Link, Google Scholar 17 : Precised characterization of renal parenchymal response to single and multiple cryoablation probes. J Urol2006; 176: 784. Link, Google Scholar 18 : An assessment of tumor cell viability after in vitro freezing. Cryobiology1985; 22: 417. Google Scholar 19 : Percutaneous cryosurgery for renal tumors. Br J Urol1995; 75: 132. Google Scholar 20 : Monitoring renal cryosurgery: predictors of tissue necrosis in swine. J Urol1998; 159: 1370. Link, Google Scholar 21 : Renal cryosurgery: experimental evaluation of treatment parameters. Urology1998; 52: 29. Crossref, Medline, Google Scholar 22 : Mechanisms of tissue injury in cryosurgery. Cryobiology1998; 37: 171. Google Scholar 23 : Measurement and prediction of thermal behavior and acute assessment of injury in a pig model of renal cryosurgery. J Endourol2001; 15: 193. Google Scholar 24 : Temperature measurements of the low-attenuation radiographic ice ball during CT-guided renal cryoablation. Cardiovasc Intervent Radiol2008; 31: 116. Google Scholar University of California-Irvine, Orange, California© 2010 by American Urological AssociationFiguresReferencesRelatedDetailsRelated articlesJournal of Urology14 Dec 2009Unintended Consequences of Laparoscopic Surgery on Partial Nephrectomy for Kidney Cancer Volume 183Issue 2February 2010Page: 752-758 Advertisement Copyright & Permissions© 2010 by American Urological AssociationKeywordstemperaturekidney neoplasmsinstrumentationcryosurgerykidneyMetricsAuthor Information Jennifer L. Young More articles by this author Surendra B. Kolla More articles by this author Donald L. Pick More articles by this author Petros Sountoulides More articles by this author Oskar G. Kaufmann More articles by this author Cervando G. Ortiz-Vanderdys More articles by this author Victor B. Huynh More articles by this author Adam G. Kaplan More articles by this author Lorena A. Andrade More articles by this author Kathryn E. Osann More articles by this author Michael K. Louie More articles by this author Elspeth M. McDougall More articles by this author Ralph V. Clayman More articles by this author Expand All Advertisement PDF downloadLoading ...Keywords:
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Aims/Purpose: We recently introduced a new method for in vivo meibography in BALB/c mice. In this study, we compared the in vivo and ex vivo meibography in young and old mice. Methods: Eighteen male BALB/c mice (9 young mice and 9 old mice) were used in this study. We performed in vivo meibography on the upper and lower eyelids of the mice. Then, the mice were sacrificed, and the eyelids were excised en bloc . Ex vivo meibography was performed on the eyelids. For quantitative comparison, the number of meibomian glands(MG) identifiable in in vivo and ex vivo meibography was counted. For the same MG in lower eyelids of in vivo and ex vivo meibography, the horizontal length(HL), vertical length(VL), and area of the MG were measured and compared using image J. Results: The number of mean identifiable MG of in vivo and ex vivo meibography was 7.4 ± 0.8 and 11.6 ± 0.6 in upper eyelids ( p < 0.001), and 8.4 ± 0.7 and 11.8 ± 0.9 in lower eyelids ( p < 0.001), respectively. The mean HL of the same MG of in vivo and ex vivo meibography was 0.16 ± 0.03 and 0.17 ± 0.03 mm ( p = 0.001). The mean VL of the same MG of in vivo and ex vivo meibography was 0.59 ± 0.08 and 0.69 ± 0.09 mm ( p = 0.001). The mean area of the same MG of in vivo and ex vivo meibography was 0.14 ± 0.05 and 0.17 ± 0.05 mm 2 ( p = 0.001). The HL ( r = 0.929, p < 0.001), VL ( r = 0.737, p < 0.001), and area ( r = 0.777, p < 0.001) of a MG of in vivo and ex vivo showed a strong positive correlation between them. The in vivo/ex vivo ratios of HL, VL, and area was 0.92 ± 0.09, 0.82 ± 0.05, and 0.82 ± 0.23 in young mice, and 0.95 ± 0.06, 0.89 ± 0.10, and 0.82 ± 0.16 in old mice. They showed no significant difference between young and old mice ( p = 0.404, 0.102, and 0.984, respectively). Conclusions: This is the first study to compare quantitatively in vivo and ex vivo meibography in mice, the most common animal models for dry eye syndrome. In vivo meibography showed shorter HL, VL, and smaller area compared to ex vivo meibography, but there was a strong positive correlation between them. Because there was no significant difference in the in vivo/ex vivo ratio of HL, VL, and area between young and old mice, there is no problem comparing in vivo meibography between young and old mice. Reference Hwang HS et al. A novel transillumination meibography device for in vivo imaging of mouse meibomian glands. Ocul Surf. 2021 Jan;19:201–209.
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No AccessJournal of UrologyInvestigative Urology1 Feb 2010In Vitro, Ex Vivo and In Vivo Isotherms for Renal Cryotherapyis companion ofUnintended Consequences of Laparoscopic Surgery on Partial Nephrectomy for Kidney Cancer Jennifer L. Young, Surendra B. Kolla, Donald L. Pick, Petros Sountoulides, Oskar G. Kaufmann, Cervando G. Ortiz-Vanderdys, Victor B. Huynh, Adam G. Kaplan, Lorena A. Andrade, Kathryn E. Osann, Michael K. Louie, Elspeth M. McDougall, and Ralph V. Clayman Jennifer L. YoungJennifer L. Young , Surendra B. KollaSurendra B. Kolla , Donald L. PickDonald L. Pick , Petros SountoulidesPetros Sountoulides , Oskar G. KaufmannOskar G. Kaufmann , Cervando G. Ortiz-VanderdysCervando G. Ortiz-Vanderdys , Victor B. HuynhVictor B. Huynh , Adam G. KaplanAdam G. Kaplan , Lorena A. AndradeLorena A. Andrade , Kathryn E. OsannKathryn E. Osann , Michael K. LouieMichael K. Louie , Elspeth M. McDougallElspeth M. McDougall , and Ralph V. ClaymanRalph V. Clayman View All Author Informationhttps://doi.org/10.1016/j.juro.2009.09.072AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract Purpose: Preoperative planning for renal cryotherapy is based on isotherms established in gel. We replicated gel isotherms and correlated them with ex vivo and in vivo isotherms in a porcine model. Materials and Methods: PERC-17 CryoProbes™ (1.7 mm) and IceRods™ (1.47 mm) underwent trials in gel, ex vivo and in vivo porcine kidneys. Temperatures were recorded at 13 predetermined locations with multipoint thermal sensors. Results: At the cryoprobe temperatures were not significantly different along the probe in any medium for either system (p = 0.0947 to 0.9609). However, away from the probe ex vivo and in vivo trials showed warmer temperatures toward the cryoprobe tip for each system (p = 0.0003 to 0.2141). Mean ± SE temperature 5 mm distal to the cryoprobe tip in vivo was 19.2C ± 16.1C for CryoProbes and 27.3C ± 11.2C for IceRods. Temperatures were consistently colder with CryoProbes than with IceRods in gel (p <0.00005), ex vivo (p <0.00005) and in vivo (p = 0.0014). At almost all sites temperatures were significantly colder in gel and in ex vivo kidney than in in vivo kidney for CryoProbes (p = 0.0107 and 0.0008, respectively) and for IceRods (each p <0.00005). Conclusions: Gel and ex vivo isotherms do not predict the in vivo pattern of freezing. Thus, they should not be used for preoperative planning. The cryoprobe should be passed 5 mm beyond the tumor border to achieve suitably cold temperatures. Multipoint thermal sensor probes are recommended to record actual temperature during renal cryotherapy. References 1 : Global increases in kidney cancer incidence, 1973–1992. Eur J Cancer Prev2002; 11: 171. Google Scholar 2 : The natural history of incidentally detected small renal masses. Cancer2004; 100: 738. Google Scholar 3 : Independent validation of the 2002 American Joint Committee on Cancer primary tumor classification for renal cell carcinoma using a large, single institution cohort. J Urol2005; 173: 1889. Link, Google Scholar 4 : The natural history of observed enhancing renal masses: meta-analysis and review of the world literature. J Urol2006; 175: 425. Link, Google Scholar 5 : Watchful waiting for solid renal masses: insight into the natural history and results of delayed intervention. J Urol2007; 177: 466. Link, Google Scholar 6 : Renal cryotherapy: a detailed review including a 5-year follow-up. BJU Int2007; 99: 1265. Google Scholar 7 : Excise, ablate or observe: the small renal mass dilemma—a meta-analysis and review. J Urol2008; 179: 1227. Link, Google Scholar 8 : Laparoscopic renal cryoablation: oncologic outcomes at 5 years. J Endourol2006; 20: A12. abstract. Google Scholar 9 : A pig model of hepatic cryotherapy: In vivo temperature distribution during freezing and histopathological changes. Cryobiology2003; 47: 214. Google Scholar 10 : Cryosurgical effects on growing vessels. Am Surg1999; 65: 677. Google Scholar 11 : Numerical solution of multidimensional freezing problem during cryosurgery. ASME-JBME1998; 120: 32. Google Scholar 12 : Rate of lesion growth around spherical and cylindrical cryoprobes. Cryobiology1971; 7: 183. Google Scholar 13 : Cryosurgical changes in the porcine kidney: histologic analysis with thermal history correlation. Cryobiology2002; 45: 167. Google Scholar 14 : Effect of freezing parameters (freeze cycle and thaw process) on tissue destruction following renal cryoablation. J Endourol2002; 16: 519. Google Scholar 15 : Effect of freeze time during renal cryoablation: a swine model. J Endourol2006; 20: 1101. Google Scholar 16 : In vivo efficacy of laparoscopic assisted percutaneous renal cryotherapy: evidence based guidelines for the practicing urologist. J Urol2008; 179: 333. Link, Google Scholar 17 : Precised characterization of renal parenchymal response to single and multiple cryoablation probes. J Urol2006; 176: 784. Link, Google Scholar 18 : An assessment of tumor cell viability after in vitro freezing. Cryobiology1985; 22: 417. Google Scholar 19 : Percutaneous cryosurgery for renal tumors. Br J Urol1995; 75: 132. Google Scholar 20 : Monitoring renal cryosurgery: predictors of tissue necrosis in swine. J Urol1998; 159: 1370. Link, Google Scholar 21 : Renal cryosurgery: experimental evaluation of treatment parameters. Urology1998; 52: 29. Crossref, Medline, Google Scholar 22 : Mechanisms of tissue injury in cryosurgery. Cryobiology1998; 37: 171. Google Scholar 23 : Measurement and prediction of thermal behavior and acute assessment of injury in a pig model of renal cryosurgery. J Endourol2001; 15: 193. Google Scholar 24 : Temperature measurements of the low-attenuation radiographic ice ball during CT-guided renal cryoablation. Cardiovasc Intervent Radiol2008; 31: 116. Google Scholar University of California-Irvine, Orange, California© 2010 by American Urological AssociationFiguresReferencesRelatedDetailsRelated articlesJournal of Urology14 Dec 2009Unintended Consequences of Laparoscopic Surgery on Partial Nephrectomy for Kidney Cancer Volume 183Issue 2February 2010Page: 752-758 Advertisement Copyright & Permissions© 2010 by American Urological AssociationKeywordstemperaturekidney neoplasmsinstrumentationcryosurgerykidneyMetricsAuthor Information Jennifer L. Young More articles by this author Surendra B. Kolla More articles by this author Donald L. Pick More articles by this author Petros Sountoulides More articles by this author Oskar G. Kaufmann More articles by this author Cervando G. Ortiz-Vanderdys More articles by this author Victor B. Huynh More articles by this author Adam G. Kaplan More articles by this author Lorena A. Andrade More articles by this author Kathryn E. Osann More articles by this author Michael K. Louie More articles by this author Elspeth M. McDougall More articles by this author Ralph V. Clayman More articles by this author Expand All Advertisement PDF downloadLoading ...
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Cardiac fibrosis is a major hallmark of cardiac diseases. For evaluation of cardiac fibrosis, the development of highly specific and preferably noninvasive methods is desired. Our aim was to evaluate CNA35, a protein known to specifically bind to collagen, as a specific marker of cardiac fibrosis. Fluorescently labeled CNA35 was applied ex vivo on tissue sections of fibrotic rat, mouse, and canine myocardium. After quantification of CNA35, sections were examined with picrosirius red (PSR) and compared to CNA35. Furthermore, fluorescently labeled CNA35 was administered in vivo in mice. Hearts were isolated, and CNA35 labeling was examined in tissue sections. Serial sections were histologically examined with PSR. Ex vivo application of CNA35 showed specific binding to collagen and a high correlation with PSR (Pearson r = .86 for mice/rats and r = .98 for canine; both p < .001). After in vivo administration, CNA35 labeling was observed around individual cardiomyocytes, indicating its ability to penetrate cardiac endothelium. High correlation was observed between CNA35 and PSR ( r = .91, p < .001). CNA35 specifically binds to cardiac collagen and can cross the endothelial barrier. Therefore, labeled CNA35 is useful to specifically detect collagen both ex vivo and in vivo and potentially can be converted to a noninvasive method to detect cardiac fibrosis.
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Abstract In vivo data acquisition using fiberoptic diffuse reflectance spectroscopy (DRS) is more complicated and less controlled compared to ex vivo data acquisition. It would be of great benefit if classifiers for in vivo tissue discrimination based on DRS could be trained on data obtained ex vivo. In this study, in vivo and ex vivo DRS measurements are obtained during colorectal cancer surgery. A mixed model statistical analysis is used to examine the differences between the two datasets. Furthermore, classifiers are trained and tested using in vivo and ex vivo data. It is found that with a classifier trained on ex vivo data and tested on in vivo data, similar results are obtained compared to a classifier trained and tested on in vivo data. In conclusion, under the conditions used in this study, classifiers intended for in vivo tissue discrimination can be trained on ex vivo data.
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Combinations of in vitro, ex vivo and in vivo animal testing have historically played a vital role in the research and the development of new therapeutic treatments. However, understanding the translation of these data across assays, as well as how these data translate to humans has proven to be challenging, especially with regards to the complex and integrated mechanism involved in blood pressure (BP) and heart rate (HR) regulation. We have evaluated the translation of several in vitro and ex vivo assays to in vivo CV assessments, as well as the translation of rat to large animal (LA), and LA to human BP and HR data. To investigate the translation of in vitro and ex vivo findings to in vivo hemodynamic results, 41 compounds with direct, indirect or unknown mechanisms of BP and/or HR modulation as well as 13 negative controls were evaluated in ppMLC (phosphorylation of myosin light chain), functional pharmacology (19 receptors/ion channels), ex vivo aortic vascular reactivity and isolated guinea pig Langendorff heart assays. Results from the in vitro and ex vivo assays were compared to in vivo conscious rat telemetry BP and HR findings. Vascular aortic relaxation and the paced guinea pig isolated heart assay detected 40% and 35%, respectively, of the in vivo positive compounds within 10× of the free Cmax that produced a 5 mmHg change in BP. The guinea pig isolated heart assay had a lower false positive rate than the aortic assay. The ppMLC assay detected 30% of compounds targeted at kinases within 10× the 5 mmHg in vivo Cmax concentration, but did not identify compounds with BP/HR risk with non‐kinase primary targets. Additional translation analyses were performed to more fully understand in vivo rat to large animal hemodynamic changes, as well as large animal preclinical to phase 1 clinical BP and HR measures. 83 compounds were assessed in both rat and LA studies. The specificity observed (true positive rate) was 71% and sensitivity (true negative rate) was 84%. Suggesting that rat is an effective model for evaluating hemodynamic risk. In evaluating 79 compounds in both LA and preclinical Phase 1 trials there was also good specificity (79%) and sensitivity (78%). These studies demonstrate that several in vitro/ex vivo assays are useful for identifying in vivo BP and HR changes; however due to the complexity of the CV system, have limited predictivity. Preclinical in vivo BP and HR testing was demonstrated to translate not only across species but also to the clinic. These data confirm the importance of pre‐clinical in vitro, ex vivo and animal models in the examination of the efficacy and safety of drugs, and the usefulness of these models for selection of compounds for advancement to clinical testing and ultimately the treatment of disease.
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Determination of in vivo optical properties is a challenging problem. Absorption and scattering measured ex vivo are often used for in vivo applications. To investigate the validity of this approach, we have obtained and compared the optical properties of mouse ears in vivo and ex vivo in the spectral range from 370 to 1650 nm. Integrating sphere spectrophotometry in combination with the inverse Monte Carlo technique was employed to determine absorption coefficients, μa, scattering coefficients, μs, and anisotropy factors, g. Two groups of mice were used for the study. The first group was measured in vivo and ex vivo within 5–10 min post mortem. The second group was measured in vivo and ex vivo every 24 h for up to 72 h after sacrifice. Between the measurements the tissues were kept at 4 °C wrapped in a gauze moistened with saline solution. Then the specimens were frozen at −25 °C for 40 min, thawed and measured again. The results indicate that the absorption coefficients determined in vivo and ex vivo within 5–10 min post mortem differed considerably only in the spectral range dominated by hemoglobin. These changes can be attributed to rapid deoxygenation of tissue and blood post mortem. Absorption coefficients determined ex vivo up to 72 h post mortem decreased gradually with time in the spectral regions dominated by hemoglobin and water, which can be explained by the continuing loss of blood. Absorption properties of the frozen-thawed ex vivo tissues showed increase in oxygenation, which is likely caused by the release of hemoglobin from hemolyzed erythrocytes. Scattering of the ex vivo tissues decreased gradually with time in the entire spectral range due to the continuing loss of blood and partial cell damage. Anisotropy factors did not change considerably.
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