Skip to main content
NCBI home page
Technology in Cancer Research & Treatment logoLink to Technology in Cancer Research & Treatment
. 2016 Jan 27;16(1):57–65. doi: 10.1177/1533034615626614

Customized Tool for the Validation of Optical Coherence Tomography in Differentiation of Prostate Cancer

B G Muller 1,✉, A Swaan 1,2, D M de Bruin 1,2, W van den Bos 1, A W Schreurs 3, D J Faber 2, E C H Zwartkruis 4, L Rozendaal 4, A N Vis 5, J A Nieuwenhuijzen 5, R J A van Moorselaar 5, T G van Leeuwen 2, J J M C H de la Rosette 1
PMCID: PMC5616116  PMID: 26818025

Abstract

Objective:

To design and demonstrate a customized tool to generate histologic sections of the prostate that directly correlate with needle-based optical coherence tomography pullback measurements.

Materials and Methods:

A customized tool was created to hold the prostatectomy specimens during optical coherence tomography measurements and formalin fixation. Using the tool, the prostate could be sliced into slices of 4 mm thickness through the optical coherence tomography measurement trajectory. In this way, whole-mount pathology slides were produced in exactly the same location as the optical coherence tomography measurements were performed. Full 3-dimensional optical coherence tomography pullbacks were fused with the histopathology slides using the 3-dimensional imaging software AMIRA, and images were compared.

Results:

A radical prostatectomy was performed in a patient (age: 68 years, prostate-specific antigen: 6.0 ng/mL) with Gleason score 3 + 4 = 7 in 2/5 biopsy cores on the left side (15%) and Gleason score 3 + 4 = 7 in 1/5 biopsy cores on the right side (5%). Histopathology after radical prostatectomy showed an anterior located pT2cNx adenocarcinoma (Gleason score 3 + 4 = 7). Histopathological prostate slides were produced using the customized tool for optical coherence tomography measurements, fixation, and slicing of the prostate specimens. These slides correlated exactly with the optical coherence tomography images. Various structures, for example, Gleason 3 + 4 prostate cancer, stroma, healthy glands, and cystic atrophy with septae, could be identified both on optical coherence tomography and on the histopathological prostate slides.

Conclusion:

We successfully designed and applied a customized tool to process radical prostatectomy specimens to improve the coregistration of whole mount histology sections to fresh tissue optical coherence tomography pullback measurements. This technique will be crucial in validating the results of optical coherence tomography imaging studies with histology and can easily be applied in other solid tissues as well, for example, lung, kidney, breast, and liver. This will help improve the efficacy of optical coherence tomography in cancer detection and staging in solid organs.

Keywords: optical coherence tomography, prostate, needle-based, validation, histopathology

Introduction

Prostate cancer is the second most common cancer in men (after skin cancer) and the second most common cause of cancer-related death (after lung cancer). In 2014, it was estimated that 233 000 new cases developed, and approximately 29 480 deaths occurred in the United States.1 During the past 2 decades, a steady increase in the detection of prostate cancer has occurred largely due to the increased use of prostate-specific antigen (PSA) screening. This has led to an increased use of systematic transrectal ultrasound (US)-guided biopsy in which the prostate is sampled in a standardized stereotypical fashion, regardless of the tumor location, which results in a high rate of false-negative findings.2 Advanced imaging modalities have the potential to address this issue by allowing more accurate tumor localization, which would in turn enable image-guided targeted biopsies3,4 and facilitate optimal treatment planning. These advanced imaging modalities will prove especially useful with the emergence of novel and potentially less morbid targeted therapies.5

Optical coherence tomography (OCT) produces high-resolution images of tissue. The principle of this optical technology is analogous to B-mode ultrasonography, except that light is being used instead of sound. Huang et al described the first application of OCT (in the retina and the coronary artery) in 1991.6 The contrast in the OCT images is based on differences in the back-scattering properties of the tissue, which are projected by gray-scale levels. With resolutions of 5 to 10 μm and a imaging depth of around 2 mm, depending on the light source used,7,8 images comparable to histopathology can be created. In the prostate, OCT has been used for a variety of purposes. During laparoscopic radical prostatectomy, OCT has proven to be successful in identifying the neurovascular bundles, which could enhance surgical precision during nerve-sparing surgery.9 Furthermore, Doppler OCT, a technology to assess blood flow in microvasculature, was proven to be effective in the rat prostate for real-time microvascular monitoring during photodynamic therapy for prostate cancer.10 Optical coherence tomography was also used for the assessment of surgical margins of the specimens after robotic radical prostatectomy. Sensitivity, specificity, positive predictive value, and negative predictive value were 70%, 84%, 33%, and 96%, respectively.11 D’Amico et al also showed differentiation of different structures in the prostate on OCT.12

Recent technological developments have led to needle-based OCT imaging of tissue.13 Thin fiber optic helical scanning OCT probes are built into needles, which allow the introduction of the OCT probe into solid tissue such as the prostate.14 The resulting images can be analyzed on visible qualitative tissue structures15 or more quantitatively on light scattering parameters16 and/or measured size of visible structures,17 which can be compared to histopathology of tissue.18 The detection of prostate cancer with OCT would enable a digital biopsy of the prostate with instant results, resulting in the possibility of cancer diagnosis and treatment in the same session. In the prostate, OCT was successfully used in rats by Rais-Bahrami et al19 and Aron et al9 during laparoscopic radical prostatectomy to identify the cavernous nerves. Yet, one-to-one correlation of OCT images with gold-standard histopathology images is essential for validation of the technology and requires very precise colocalization.18

The correlation between imaging modalities and histopathology is challenging. Several studies reported on a similar challenge in validation of multiparametric magnetic resonance imaging (MRI) for prostate cancer.20-22 Especially in studies evaluating OCT images, one-to-one histology correlation is extra important because of the high resolution at micrometer level. This proof-of-concept study demonstrates the feasibility and use of a customized device to generate histological sections of the prostate that directly correlate with OCT pullback measurements on a millimeter level. Exemplary coregistration results between OCT and histopathology of the prostate are given.

Materials and Methods

The OCT system used in the study is the commercially available C7-XR intravascular imaging system interfaced to a C7 Dragonfly intravascular imaging probe (St Jude Medical, St Paul, Minnesota). The system is originally designed for intravascular (IV) OCT and operates a probe with a diameter of only 0.9 mm, which fits through a small 17-G needle. It is therefore possible to perform OCT measurements in solid tissue as the prostate. The C7-XR Intravascular Imaging System takes 5.4 seconds to acquire a 3-dimensional (3D)-OCT helical motorized pullback image of 540 B-scans over a trajectory of 54 mm (length) with a pullback speed of 10 mm/s (Figure 1). The radius or imaging depth is limited by scattering to approximately 2 mm.

Figure 1.

Figure 1.

Open in a new tab

St Jude C7-XR intravascular optical coherence tomography (OCT) system. A, Schematic detail of the probe tip. The OCT imaging probe (on 3-dimensional [3D] schematic illustration and as a cross section of the tip of the probe) was 0.9 mm in diameter and fitted through an intravenous catheter. The probe functions as a lighthouse, it shines light sideways, and makes pullbacks of 54 mm in 5.4 seconds. B, By the imaging console, the OCT pullback was controlled. C, C7 Dragonfly intravascular imaging probe, which was compatible to the C7-XR intravascular imaging console depicted in B. D, Detail of the C7 Dragonfly probe tip.

Directly after radical prostatectomy, a silicon tube was passed through the urethra for orientation purposes. Base (left) and apex (right) as well as ventral and dorsal side were identified. The prostate was measured, weighed, and inked ventral right side (red), ventral left side (yellow), dorsal right side (green), and dorsal left side (blue). After inking, the fresh prostate was anchored in a grid-based customized tool with 4 anchoring needles in the center of the grid (Figure 2). Six IV catheters (Intranule, 105 × 1.3 × 1.7 mm, 16 G; Vygon, Ecouen, France) were introduced from the left side to the right side of the prostate. The grid-based customized mold was used to ensure a parallel IV catheter position (Figure 2). The inner needles were removed from the IV catheters, and the OCT imaging probe was introduced into the IV catheter while flushing with water (to prevent the formation of air bubbles). The IV catheters were transparent, therefore, the OCT pullback measurements could be performed while the IV catheters were still in place. After the OCT measurements were finished, long needles were placed through the measurement trajectories in order to keep the IV catheters parallel while the prostate was fixed in formalin.

Figure 2.

Figure 2.

Open in a new tab

Customized grid for optical coherence tomography (OCT) measurements and fixation in formalin. A, Fresh prostate stained for orientation (℗) and fixed in a grid (□) on both sides for parallel OCT measurements. Ventral right side (red), ventral left side (yellow), dorsal right side (green), dorsal left side (blue). A silicon tube was inserted through the urethra for orientation purposes. B, Transparent intravenous (IV) catheters were inserted from left to right, parallel to each other, with the help of the grids on either side of the prostate (same coordinate in as out). C, The OCT imaging probe (OCT) was inserted through the transparent IV catheters. Pullback measurements were made from the right to the left side. D, Enlargement of the positioning grid on either side of the prostate. The prostate was fixed in the grid with 4 fixation needles located in the center indicated by Δ. After the OCT measurements, the prostate was fixed in formalin for 48 hours in the grid.

Subsequently, the prostate was fixed in formalin for 48 hours. After fixation, the prostate was sliced of exactly 4 mm thickness using our in-house-developed customized tool for pathology validation. One of the sides from our grid-based measurement and fixation tool was detached, and the grid was fitted in a guided cutting tool. Small rails ensured that the knife was positioned exactly in front of the IV catheters (measurement trajectories). Knife guiders that fold around the knife were introduced through the other side of the grid and inserted in the IV catheters to guide the knife exactly through the measurement trajectories (Figure 3). Slices that did not contain measurement trajectories were cut without guidance. After slicing, a high-resolution overview picture was made according to protocol (Figure 4). From the slices with measurement trajectories, whole-mount histology slides were made in order to see the entire measurement trajectory (Figure 4).

Figure 3.

Figure 3.

Open in a new tab

Customized cutting tool for the exact correlation with histopathology. A, First, one of the sides was removed from the grid, and the grid was placed in the customized cutting tool. The inner needles were removed from the first 2 intravenous (IV) catheters. Underneath the grid, there are rails that position the measurement trajectories in front of the knife (◊). From the other side, knife guiders were introduced in the grid (•) that fold around the knife and enter the IV catheter. They were locked in their position by turning the locking bar (*). The prostate is indicated by ℗. Ventral right side (red), ventral left side (yellow), dorsal right side (green), dorsal left side (blue). B, The prostate was sliced by pushing the whole grid toward the locking bar, forcing the knife to slice through the measurement trajectories. C, After slicing, it was clearly visible that the measurement trajectories are exactly sliced through the center. The forceps hold one side of the IV catheter, which is sliced exactly in 2 halves.

Figure 4.

Figure 4.

Open in a new tab

Histopathology matching. A, The prostate was stained and imaged when it was still fresh. B, After fixation in formalin, the prostate was sliced using the customized cutting tool. Slices with the trajectories in them were used for whole-mount slides, in this prostate, those were slice 2 (trajectories on the back) and slice 5. C, Enlargement of slice 5. The measurement trajectories can be clearly seen. D, Microscopy slide of slice 5. The measurement trajectories can be clearly followed.

The histopathology slides were evaluated by a single urogenital pathologist with 10 years of experience (L.R.) who was blinded to the OCT measurements. Alongside the measurement trajectories, the structures were described and correlated with the OCT measurements.

Using the imaging software AMIRA (version 5.5; FEI Visualization Sciences Group, Mérignac Cédex, France), we determined which part of the OCT measurement trajectories passed through the prostate. Subsequently, we fused the OCT data with the histopathology in a 3D computer environment. In this way, we were able to exactly correlate the OCT B-scan with the location on histopathology.

Results

A radical prostatectomy was performed in a patient (age: 68 years, PSA: 6.0 ng/mL) with Gleason score 3 + 4 = 7 in 2/5 biopsy cores on the left side (15%) and 3 + 4 = 7 in 1/5 biopsy cores on the right side (5%). Histopathology after radical prostatectomy showed an anterior located pT2cNx adenocarcinoma Gleason 3 + 4 = 7.

Using 3D imaging software AMIRA, the 3D-OCT measurement volumes were fused with the histopathology slice (Figure 5). Subsequently, we defined the number of B-scans that went through prostate tissue and divided that through the number of millimeters trajectory on histopathology. In this way, we could calculate the number of B-scans per millimeter and exactly locate the measurement site with an accuracy of 0.1 mm. We could identify various structures in the histopathology, which we also observed in the OCT measurements, which confirmed an accurate matching. Some examples are depicted in Figure 6. Alongside the measurement trajectory, the following structures were recognizable: (1) prostate cancer Gleason 3 + 4. In the OCT image, no structural information could be obtained (homogeneous aspect of tissue). However, it was clear that the light did not penetrate as far into the tissue as in other measurement locations (higher attenuation of light). The increased scattering is presumably due to the high nuclear density in that area, combined with the lowered amount of cytoplasm in these cells (lower nucleus–cytoplasm ratio), as observed in histopathology. (2) Some cystic atrophy with septae was seen alongside the OCT measurement trajectory. On the OCT B-scans, structures are clearly recognizable (Figure 6B, arrows), and light penetration is relatively deep (low attenuation). (3) Stroma was visible in the OCT B-scan as a homogeneous scattering medium in which light penetrates relatively deep (low attenuation). This is presumably because of the low nuclear density in the stroma, which could also be seen on histopathology. (4) Healthy glands were also located alongside the OCT imaging trajectory. In the OCT B-scans, the glands were recognizable (Figure 6D, arrows) and the light penetrates more deeply into the tissue (lower attenuation). (5) Cystic atrophy with large cysts was clearly seen on the OCT B-scans. They perfectly align with the shape of the cysts seen in the same area on histopathology (Figure 6E, arrows).

Figure 5.

Figure 5.

Open in a new tab

Three-dimensional (3D) fusing of optical coherence tomography (OCT) volume with histopathology slide (slice 5, Figure 4). Using 3D imaging software AMIRA, entire 3D OCT volumes were fused with the histopathology slide. For each measurement, one plane (slice of 3D volume) in the X–Z direction was visualized as well as 5 B-scans (X–Y direction). The letters correspond to the B-Scans in Figure 6.

Figure 6.

Figure 6.

Open in a new tab

Five B-scans from the fused histopathology slide. A, Area of Gleason 4 prostate cancer. In the optical coherence tomography (OCT) B-scan, this is seen as a homogenous tissue with low penetration depth. In the histopathology slides, nuclear density is seen. B, Cystic atrophy with septae. The cysts are clearly seen on the OCT images (arrows), the septae can be seen on both OCT images and histopathology (#). C, Stroma. In the OCT B-scan, this is seen as a homogenous area with high penetration depth. D, Healthy glands. The glands can be seen on the OCT B-scans as a heterogeneous area (indicated by the arrows). E, Cystic atrophy without septae. The arrows indicate some of the cysts. It is well seen that the cysts have the same shape as the areas on histopathology. NB: The letters of the B-scans correspond to the letters in Figure 5.

As can be seen in Figure 6, the structures seen on OCT correlate well with the structures on histopathology. The imaging trajectories on OCT measured 41.5 and 39.5 mm, whereas they measured 39.5 and 41.0 mm, respectively, in the whole-mount histopathology slides.

Discussion

Matching of data obtained from a high-resolution imaging techniques as OCT to histopathology is prone to fail because of slight misalignments and misorientations between the images. In order to improve the coregistration of whole-mount histology sections to fresh tissue OCT pullback measurements, we successfully designed and applied a customized tool to process radical prostatectomy specimens. A major limitation of conventional needle biopsies is that the tissue is only visualized in 2 dimensions, whereas important structures for determining cancer and invasiveness of the disease are more clearly seen in 3 dimensions. What is true in radiology is expected in pathology: 3D imaging will give an immense increase in the information content, which is expected to increase sensitivity and specificity of early cancer diagnostic technologies.23 Standard pathology protocols, however, are insufficiently accurate for the validation of a micrometer resolution needle-based technology as OCT.

For the validation of other novel diagnostic modalities, one-to-one histopathology matching is essential but presents itself with a challenge. Turkbey et al designed a custom-made 3D printed mold for the validation of multiparametric MRI for prostate cancer diagnosis. These molds, based on the 3D MRI images, allowed cutting the specimens in exactly the same plane as the MRI scans.22,24,25 This method can be used for deeply penetrating imaging technologies (as MRI and US) but are less suitable for superficial (less deeply penetrating) imaging technologies as OCT. Hariri et al designed a method to compare OCT images with histopathology in the ex vivo setting to validate OCT in bronchial tissue.26 The method worked in the ex vivo setting by cutting the bronchi open and placing ink markers on the tissue where in between the OCT measurements were performed. A similar technique had been used in cardiology27,28 for the visualization of high-risk plaques. Wagstaff et al used an approach where they acquired a core biopsy of in vivo renal tissue over the same trajectory as a biopsy was harvested,29 an approach that is challenged by the high percentage of nondiagnostic specimens that occurs in renal biopsy protocols.30

The customized tool for OCT measurements and histopathology matching does have some limitations we have to address. There is a small difference in the length of trajectory between the OCT measurements and the histopathology slide, which can be explained by the formalin fixation-related shrinkage of the prostate. A study by Jonmarker et al described an average linear shrinkage of 4.5%, corresponding to a volume correction factor of 1.15.31 Another study found a linear shrinkage of 4.3% and a net volumetric shrinkage of 12.4%, resulting in a correction factor for tissue shrinkage of 1.14.32 In our sample, we found a linear shrinkage of 4.8% and 5.3%. Moreover, in large prostates, when fixed in formalin for 48 hours, the differences in fixation can be present between the outer and inner parts of the tissue block, which may cause nonuniform shrinkage and therefore minor (<1 mm) mismatch in images and histopathology.

The axial rotation of the imaging probe in the tissue is estimated based on the location of the urethra (if visible) and steepness of the borders of the prostate. Although this method is reasonably accurate, an inaccuracy of approximately 10° in probe rotation may exist. In future studies, a marker can ensure axial probe rotation in tissue before measurements.

One of the main advantages of OCT over conventional diagnostic technologies, next to the fact that the technology provides instant real-time diagnosis, is that it is objective, by quantitative analysis of the data. Current methods of histopathology are time consuming and sensitive to subjectivity of the pathologist. By performing quantitative analysis of OCT data, we expect to avoid these diagnostic boundaries as there are in conventional pathology, as delay in diagnosis and subjectivity. We believe that OCT is not a technology to find a lesion but rather to get local information about the tissue. Therefore, we propose to integrate OCT in other technologies as MRI or contrast-enhanced US. When OCT has been validated as a reliable artificial biopsy. Diagnosis and treatment of prostate cancer can be performed on the same day, in a minimally invasive manner.

To our knowledge, we are the first to describe a one-to-one method for full specimen histopathology matching with needle-based OCT in solid tissue. By demonstrating examples of B-scans and identifying structures on OCT that could also be seen on histopathology, we showed that matching is nearly perfect. Besides prostates, the technology can also be applied in other solid tissues, for example, lung, kidney, breast, and liver. The technology presented is an important step in order to validate a high-resolution imaging technique as OCT. When OCT has proven to be valid in the ex vivo setting, the next step will be to validate the technology in vivo.

Conclusion

We successfully designed and applied a customized tool to process radical prostatectomy specimens to improve the coregistration of whole-mount histology sections to fresh tissue OCT pullback measurements. This technique is crucial in validating the results of OCT imaging studies with histology and can easily be applied in other solid tissues as well, for example, lung, kidney, breast, and liver. This method will help improve the efficacy of OCT in cancer detection and staging in solid organs. Future work will focus on a technique to validate OCT in the prostate using this method in a larger group of patients.

Supplementary Material

Supplementary material
Download video file (121.6MB, mp4)

Abbreviations

3D

3-dimensional

IV

intravascular

MRI

magnetic resonance imaging

OCT

optical coherence tomography

PSA

prostate-specific antigen

US

ultrasound

Footnotes

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by an unrestricted research grant from the Cure for Cancer Foundation.

Supplemental Material: The online supplemental video is available at http://journals.sagepub.com/doi/suppl/10.1177/1533034615626614.

References

  • 1. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014;64(1):9–29. [DOI] [PubMed] [Google Scholar]
  • 2. Stamatiou K, Alevizos A, Karanasiou V. et al. Impact of additional sampling in the TRUS-guided biopsy for the diagnosis of prostate cancer. Urol Int. 2007;78(4):313–317. [DOI] [PubMed] [Google Scholar]
  • 3. Hambrock T, Hoeks C, Hulsbergen-van de Kaa C. et al. Prospective assessment of prostate cancer aggressiveness using 3-T diffusion-weighted magnetic resonance imaging-guided biopsies versus a systematic 10-core transrectal ultrasound prostate biopsy cohort. Eur Urol. 2012;61(1):177–184. [DOI] [PubMed] [Google Scholar]
  • 4. Hong CW, Rais-Bahrami S, Walton-Diaz A. et al. Comparison of MR-US fusion-guided prostate biopsies obtained from axial and sagittal approaches. BJU Int. 2014;115(5):772–779. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Ahmed HU, Emberton M. Active surveillance and radical therapy in prostate cancer: can focal therapy offer the middle way? World J Urol. 2008;26(5):457–467. [DOI] [PubMed] [Google Scholar]
  • 6. Huang D, Swanson EA, Lin CP. et al. Optical coherence tomography. Science. 1991;254(5035):1178–1181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Pan Y, Lavelle JP, Bastacky SI. et al. Detection of tumorigenesis in rat bladders with optical coherence tomography. Med Phys. 2001;28(12):2432–2440. [DOI] [PubMed] [Google Scholar]
  • 8. Zysk AM, Nguyen FT, Oldenburg AL, Marks DL, Boppart SA. Optical coherence tomography: a review of clinical development from bench to bedside. J Biomed Opt. 2007;12(5):051403. [DOI] [PubMed] [Google Scholar]
  • 9. Aron M, Kaouk JH, Hegarty NJ. et al. Second prize: preliminary experience with the Niris optical coherence tomography system during laparoscopic and robotic prostatectomy. J Endourol. 2007;21(8):814–818. [DOI] [PubMed] [Google Scholar]
  • 10. Standish BA, Lee KK, Jin X. et al. Interstitial Doppler optical coherence tomography as a local tumor necrosis predictor in photodynamic therapy of prostatic carcinoma: an in vivo study. Cancer Res. 2008;68(23):9987–9995. [DOI] [PubMed] [Google Scholar]
  • 11. Dangle PP, Shah KK, Kaffenberger B, Patel VR. The use of high resolution optical coherence tomography to evaluate robotic radical prostatectomy specimens. Int Braz J Urol. 2009;35(3):344–353. [DOI] [PubMed] [Google Scholar]
  • 12. D’Amico AV, Weinstein M, Li X, Richie JP, Fujimoto J. Optical coherence tomography as a method for identifying benign and malignant microscopic structures in the prostate gland. Urology. 2000;55(5):783–787. [DOI] [PubMed] [Google Scholar]
  • 13. Kuo WC, Kim J, Shemonski ND, Chaney EJ, Spillman DR, Jr, Boppart SA. Real-time three-dimensional optical coherence tomography image-guided core-needle biopsy system. Biomed Opt Express. 2012;3(6):1149–1161. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Hwang JH, Cobb MJ, Kimmey MB, Li X. Optical coherence tomography imaging of the pancreas: a needle-based approach. Clin Gastroenterol Hepatol. 2005;3(7 suppl 1):s49–s52. [DOI] [PubMed] [Google Scholar]
  • 15. Jain M, Shukla N, Manzoor M, Nadolny S, Mukherjee S. Modified full-field optical coherence tomography: a novel tool for rapid histology of tissues. J Pathol Inform. 2011;2:28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Vuong B, Skowron P, Kiehl TR. et al. Measuring the optical characteristics of medulloblastoma with optical coherence tomography. Biomed Opt Express. 2015;6(4):1487–1501. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Swager A, Boerwinkel DF, de Bruin DM. et al. Volumetric laser endomicroscopy in Barrett’s esophagus: a feasibility study on histological correlation [published online May 8, 2015.] Dis Esophagus. 2015. [DOI] [PubMed] [Google Scholar]
  • 18. Muller BG, de Bruin DM, van den Bos W. et al. Prostate cancer diagnosis: the feasibility of needle-based optical coherence tomography. J Med Imaging (Bellingham). 2015;2(3):037501. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Rais-Bahrami S, Levinson AW, Fried NM. et al. Optical coherence tomography of cavernous nerves: a step toward real-time intraoperative imaging during nerve-sparing radical prostatectomy. Urology. 2008;72(1):198–204. [DOI] [PubMed] [Google Scholar]
  • 20. Jhavar SG, Fisher C, Jackson A. et al. Processing of radical prostatectomy specimens for correlation of data from histopathological, molecular biological, and radiological studies: a new whole organ technique. J Clin Pathol. 2005;58(5):504–508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Madabhushi A, Feldman MD, Metaxas DN, Tomaszeweski J, Chute D. Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI. IEEE Trans Med Imaging. 2005;24(12):1611–1625. [DOI] [PubMed] [Google Scholar]
  • 22. Shah V, Pohida T, Turkbey B. et al. A method for correlating in vivo prostate magnetic resonance imaging and histopathology using individualized magnetic resonance-based molds. Rev Sci Instrum. 2009;80(10):104301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Ikeda M, Matsumoto K, Choi D. et al. The impact of real-time 3d imaging by ultra-high speed optical coherence tomography in urothelial carcinoma. BMC Urol. 2013;13:65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Trivedi H, Turkbey B, Rastinehad AR. et al. Use of patient-specific MRI-based prostate mold for validation of multiparametric MRI in localization of prostate cancer. Urology. 2012;79(1):233–239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Turkbey B, Mani H, Shah V. et al. Multiparametric 3T prostate magnetic resonance imaging to detect cancer: histopathological correlation using prostatectomy specimens processed in customized magnetic resonance imaging based molds. J Urology. 2011;186(5):1818–1824. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Hariri LP, Applegate MB, Mino-Kenudson M. et al. Volumetric optical frequency domain imaging of pulmonary pathology with precise correlation to histopathology. Chest. 2013;143(1):64–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. van der Meer FJ, Faber DJ, Baraznji Sassoon DM, Aalders MC, Pasterkamp G, van Leeuwen TG. Localized measurement of optical attenuation coefficients of atherosclerotic plaque constituents by quantitative optical coherence tomography. IEEE Trans Med Imaging. 2005;24(10):1369–1376. [DOI] [PubMed] [Google Scholar]
  • 28. Virmani R, Otsuka F, Prati F, Narula J, Joner M. Matching human pathology is essential for validating OCT imaging to detect high-risk plaques. Nat Rev Cardiol. 2014;11(11):638. [DOI] [PubMed] [Google Scholar]
  • 29. Wagstaff PG, Swaan A, Ingels A. et al. In vivo, percutaneous, needle based, optical coherence tomography of renal masses. J Vis Exp. 2015;(97). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Barwari K, Kummerlin IP, ten Kate FJ. et al. What is the added value of combined core biopsy and fine needle aspiration in the diagnostic process of renal tumours? World J Urol. 2013;31(4):823–827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Jonmarker S, Valdman A, Lindberg A, Hellstrom M, Egevad L. Tissue shrinkage after fixation with formalin injection of prostatectomy specimens. Virchows Arch. 2006;449(3):297–301. [DOI] [PubMed] [Google Scholar]
  • 32. Schned AR, Wheeler KJ, Hodorowski CA. et al. Tissue-shrinkage correction factor in the calculation of prostate cancer volume. Am J Surg Pathol. 1996;20(12):1501–1506. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material
Download video file (121.6MB, mp4)

Articles from Technology in Cancer Research & Treatment are provided here courtesy of SAGE Publications

RESOURCES