Innovations in Technology-Guided Therapy


By Amber L. Simpson

Technology is increasingly being used to help clinicians make better-informed treatment decisions in the presence of imperfect data. According to Moore’s Law, processor speeds double approximately every two years. This rate of progress, coupled with the continuous advances in cross-sectional imaging technologies, has driven increases in the speed and resolution of CT and MRI. 

At MSK, these improvements have allowed us to develop novel computing strategies, including virtual surgical planning, image-guided surgery, and prognostic imaging markers, to provide enabling technologies for precision oncology.

Virtual Organ Volumetry for Surgical Planning

Today, we routinely perform detailed virtual planning for individual patients undergoing major liver resection. Full recovery from major hepatic resection requires a healthy, well-perfused liver remnant that is capable of regenerating to its pre-resection volume. Several studies have shown that the percentage of functional liver parenchyma remaining after major hepatic resection is one of the few reliable predictors of postoperative hepatic dysfunction and morbidity. (1), (2)

Having demonstrated that liver volumetry based on preoperative scans can be performed accurately, (3) we then developed patient-specific virtual models that provide the surgeon with three-dimensional measurements of parenchyma, tumor, and delicate vasculature in relation to resection lines.

For example, the image in Figure 1a is a virtual surgical plan for a patient with a potentially small liver remnant (dark orange) and it shows a remnant volume projection at 34 percent of the original liver volume. To stimulate growth of the liver remnant prior to resection, the patient underwent portal vein embolization. Figure 1b shows the same patient with increased remnant liver volume (dark orange) at six weeks after embolization, including the remnant volume projection at 43 percent of original liver volume. Because growth rate after portal vein embolization is a good predictor of hepatic resection outcome, (4) this patient proceeded to resection.

Virtual liver remnant

Figure 1 - Virtual liver remnant (dark orange) projected at: (a) 34% of total liver volume before portal vein embolization; and (b) 43% of total liver volume after portal vein embolization.

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Image-Guided Liver Surgery

Image-guided surgery systems provide a virtual roadmap, much like a global positioning system, through a patient’s anatomy. The liver is soft, compressible, and undergoes displacement when detached from its ligaments and positioned for resection. Consequently, the positioned liver no longer corresponds exactly in shape to the liver visible on preoperative cross-sectional imaging. This discrepancy makes it difficult to locate small, deeply placed tumors, especially after chemotherapy, when the liver parenchyma has become fatty or fibrotic. Surgical navigation systems are routinely used to more easily localize these tumors. Figure 2 shows the image displayed by one such guidance system when a tumor was successfully located on CT after it was not found using standard ultrasound alone.

Tumor, CT-based navigation combined with ultrasound

Figure 2 - Tumor successfully located using CT-based navigation combined with ultrasound: (a) green probe indicates tumor on the image-guidance display of CT; and (b) yellow arrow indicates the tumor displayed in ultrasound. Initially, the tumor was not able to be localized using standard ultrasound alone.

Continuous imaging technology represents a new paradigm of surgical guidance that has the potential to further improve surgical accuracy. The challenge is to provide surgeons with real-time, continuous visualization of internal structures, including tumors and vasculature, relative to their surgical objectives, in order to guide intervention while avoiding injury. At MSK, we are developing a solution that uses stereo-vision technology (Figure 3), where dual video cameras capture organ shape in much the same way that our eyes perceive depth.

Stereo-vision system for continuous surgical guidance

Figure 3 - Stereo-vision system for continuous surgical guidance, in development at MSK.

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Prognostic Imaging Markers

Radiologists assess subtle changes in contrast enhancement patterns on images to determine diagnosis and treatment response. These heterogeneity changes can be measured with a quantitative tool called texture analysis. Figure 4 shows a standard diagnostic abdominal CT scan with a region of interest (ROI) magnified. Changes in pixel values across the magnified region can be appreciated. Texture analysis describes the spatial variation of pixel intensity in an ROI where the ROI could be any biologically relevant structure such as parenchyma, tumor, or node.

Variation in pixel intensity visible within a magnified region

Figure 4 - Variation in pixel intensity visible within a magnified region of interest of a standard diagnostic CT scan.

With support from Cycle for Survival, we are evaluating tumor texture as a preoperative prognostic marker in pancreatic ductal adenocarcinoma (PDAC). PDAC is one of the most lethal cancers worldwide, with a five-year overall survival rate of 6 percent. (5) Complete surgical resection, achievable in 10 to 15 percent of patients, is the only curative treatment. (6) Therefore, determining preoperative prognostic factors is crucial for these patients.

At MSK, we have demonstrated that extracting texture from pretreatment scans can provide patient prognosis stratification. The Kaplan-Meier curve in Figure 5 demonstrates the power of one texture variable to stratify PDAC patients into distinct groups. In particular, texture analysis combined with differentiation enabled identification of a group of patients with a 60 percent chance of survival at five years — a group previously unknown in the study of PDAC. This marker was independent of all other clinical variables. Although this proof of principle needs further validation across a sufficiently powered study, it nonetheless shows promise for the evaluation of PDAC patients.

Kaplan-Meier curve

Figure 5 - Kaplan-Meier curve using tumor differentiation and one tumor texture variable to identify a subset of PDAC patients having a 60% overall survival probability at five years.

From virtual surgical planning and image-guided surgery to prognostic imaging markers, we continue to develop technologies with an eye toward the ultimate goal of precision therapy for hepatic and pancreatic tumors.

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  1. Shoup M, Gönen M, D’Angelica M, et al. Volumetric analysis predicts hepatic dysfunction in patients undergoing major liver resection. J Gastrointest Surg 2003;7(3):325-330.
  2. Schindl MJ, Redhead DN, Fearon KCH, Garden OJ, Wigmore SJ; Edinburgh Liver Surgery and Transplantation Experimental Research Group (eLISTER). The value of residual liver volume as a predictor of hepatic dysfunction and infection after major liver resection. Gut 2005;54(2):289-296.
  3. AL, Geller DA, Hemming AW, et al. Liver planning software accurately predicts postoperative liver volume and measures early regeneration. J Am Coll Surg 2014;219(2):199-207.
  4. Leung U, Simpson AL, Araujo RLC, et al. Remnant growth rate after portal vein embolization is a good early predictor of post-hepatectomy liver failure. J Am Coll Surg 2014;219(4):620-630.
  5. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin 2012;62(1):10-29.
  6. Alexakis N, Halloran C, Raraty M, Ghaneh P, Sutton R, Neoptolemos JP. Current standards of surgery for pancreatic cancer. Br J Surg 2004;91(11):1410-1427.