The Long and Short of It Series
Oncologists have relied on Long and Short diameter measurements as a surrogate for the volume of a tumor for decades. In fact, the most common therapy response assessment protocol—Response Evaluation Criteria In Solid Tumors version 1.1 (RECIST 1.1) —defines a tumor’s size by its longest in-plane diameter in any CT image.
In recent years, a growing body of evidence suggests that recording changes in diameter may not be the most accurate representation of tumor growth or shrinkage, leading many to consider the value of volume as a standard measurement. Consider the following scenario:
An oncologist for a patient with lung cancer as part of ongoing monitoring of a tumor. RECIST measurement guidelines reveal a tumor size of two centimeters in longest diameter. A follow-up appointment two months later reveals no significant change, providing the oncologist with some level of confidence that current treatment approaches are effective. What the oncologist does not know is that the tumor is growing in the out of plane direction—an observation that traditional one-dimensional (1D) and two-dimensional (2D) imaging methods cannot detect. A measurement in the out of plane direction—or even better, a measurement of the three-dimensional (3D) volume—could have revealed the true situation of tumor progression. Similarly, longest diameter measurements may imply a significant increase in size, when in fact, the tumor has remained almost the same volume but become longer and thinner.
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When reviewed for diametric changes alone the lesion appears to be stable, but when evidence-based metrics such as Volume and Volume Doubling Time are considered, a different story emerges.
Research reveals that Long and Short measurements don’t provide an accurate or comprehensive depiction of a patient’s cancer burden because they don’t recognize that lesions are 3D. For example, clinicians often use diameter measurements as a surrogate for volume to ascertain response to therapies. Yet, one study conducted at Sanford Medical Center in Bismarck North Dakota found that on average, the estimated volume from diameter measurements varied by 88.03% from the actual measured volumes, suggesting that “diametric measurements cannot be correlated to actual tumor size.” 1
Failing to capture true changes in a lesion, which often happens when measured strictly by diameter, can impact patient outcomes and clinical trial results by providing misleading information on response to treatment. In contrast, another study revealed that 3D volume-based sizing—when compared to 1D and 2D sizing—had low bias across shapes of lung nodules, significantly improving accuracy of response classification. 2
An average 88.03% variance was observed between estimated and actual volumes. Variance was independent of tumor size and the range was widely scattered.1scovered.
Volumetrics shows great promise as a methodology for capturing a more accurate representation of change in the size of a lesion. The Sanford study noted that “as imaging technology advances, so must our associated practices. The utilization of a volumetric method provides a more comprehensive and accurate assessment of tumor size, which may alter clinical decisions.” 3
Volumetrics: A Superior Approach
Volumetric measurement combines the 2D slices of a CT scan to create a 3D representation of the tumor, revealing the true volume it occupies. However, most studies examining the impact of use of volumetric versus diametric measurements have used relatively simple shapes where the impact may not be as great as for tumors associated with complex cancers.
2D Data - diametric measures only
3D Data - accurate
One study addressed this challenge in a clever way by employing diapers as phantoms to mimic the complex shapes and fuzzy boundaries of real tumors. 4 Researchers compared the methods by injecting water into the diapers to create “tumors”, then weighing the diapers to determine the volume of each tumor from the mass. The study found that volumetric analysis outperformed RECIST diametric measurements by at least a factor of five in estimating mass and thus true volume. Assuming that volume is representative of cancer burden, accurate volumetric measurements can provide a more consistent interpretation of tumor response and an improved prediction of patient outcomes.
Notably, research shows that deeper insights provided through volumetrics can help clinical teams detect survivable cancers earlier and better stage cancers. 5 In addition, volumetric measurements are more likely to show a correlation with survival and help identify a survival difference between responders and non-responders, something 1D and 2D imaging biomarkers are sometimes unable to do. 6
Volumetrics empowers clinical teams by turning images into rich data for analysis and decision support, enabling more precise patient management, the potential for improved outcomes and a reduced cost of care. Beyond clinical studies, technology that supports this kind of quantitative analysis now makes possible more precise analysis across different time points for each patient while also looking at differences and similarities between patients.
The challenge, however, is that it’s impractical with conventional radiology systems for radiologists to delineate tumor volumes to generate the needed insights into growth and therapy response. 7
The Role of Technology
While 3D segmentation may be the most accurate measure of a lesion, the challenge is that it is a complex undertaking without the benefit of innovative technology, specifically semi-automated tools that provide volumetric measures across time. Examples of quantities that can be extracted, in addition to tumor volume, are doubling time of the volume (showing growth rate), average tumor attenuation (revealing density, degree of blood perfusion or necrosis), total mass of a nodule and corresponding doubling time.
Advanced solutions exist that leverage the value of these measurements with just a mouse click. A framework of automation streamlines analysis and empowers radiologists with a level of precision that is difficult to achieve via manual processes. By reducing the potential for variation, semi-automated measurement tools deliver actionable information in a timely manner for proactive management of patients, helping clinical teams adapt therapies earlier to circumvent disease progression and improve outcomes.
Technology also provides a streamlined method of communication between radiologists and oncologists that is powered by a foundation of decision support to ensure standardized adoption of best practice protocols. Studies repeatedly point to a correlation between use of technology and optimal standardization. One study found that computer-assisted measurements reduced inter-reader variability by half compared to manual measurements. 8
Computer-assisted measurements reduced inter-reader variability by half compared to manual measurements.
A Better Analysis of Cancer Burden
A tumor’s volume—or the space it inhabits—is an important indicator of the number of cancer cells it harbors. Oncologists cannot begin to quantitatively assess the response to a therapy in terms of how it impacts cancer burden without first understanding changes in tumor volume. For decades, Long and Short measurements have provided oncologists with a standard for measuring tumor size and determining response or progression. New evidence suggests that this approach has notable limitations that are effectively addressed through volumetric measurements—and more specifically through use of semi-automated approaches that make these measurements practical.
In sync with the industry’s focus on early detection and treatment of cancer, volumetric tools show great promise in advancing disease identification and improving survival rates. Researchers from the previously-mentioned lung cancer research study say it well: “The positive results of previous studies on volume and diameter measurements of lung nodules suggest that manual measurements of nodule diameter may be replaced by semi-automated volume measurements in the (near) future.” 9
- A. Frenette, J. Morrell, K. Bjella, E. Fogarty, J. Beal and V. Chaudhary, “Do Diametric Measurements Provide Sufficient and Reliable Tumor Assessment? An Evaluation of Diametric, Areametric, and Volumetric Variability of Lung Lesion Measurements on Computerized Tomography Scans,” Journal of Oncology, 2015.
- N. Petrick, H. Kim, D. Clunie, K. Borradaile, R. Ford, R. Zeng, et al, “Comparison of 1D, 2D, and 3D Nodule Sizing Methods by Radiologists for Spherical and Complex Nodules on Thoracic CT Phantom Images,” Academic Radiology, 2014.
- A. Frenette, et al. “Do Diametric Measurements Provide Sufficient and Reliable Tumor Assessment? An Evaluation of Diametric, Areametric, and Volumetric Variability of Lung Lesion Measurements on Computerized Tomography Scans.”
- Z. Levine, H. Chen-Mayer, A. Peskin and A. Pintar, “Comparison of One-Dimensional and Volumetric Computed Tomography Measurements of Injected-Water Phantoms,” Journal of Research of the National Institute of Standards and Technology, 2017.
- A. Hayes, M. Pietanza, D. O’Driscoll et al, “Comparison of CT volumetric measurement with RECIST response in patients with lung cancer,” European Journal of Radiology, 2016.
- S. Sahu, R. Schernthaner, R. Ardon, J. Chapiro, et al, “Imaging Biomarkers of Tumor Response in Neuroendocrine Liver Metastases Treated with Transarterial Chemoembolization: Can Enhancing Tumor Burden of the Whole Liver Help Predict Patient Survival,” Radiology, 2017.
- Healthmyne, “Leveraging Quantitative Imaging in Precision Medicine.”
- J. Dinkel, O. Khalilzadeh, C. Hintze, et al. “Inter-observer reproducibility of semi-automatic tumor diameter measurement and volumetric analysis in patients with lung cancer,” Lung Cancer, 2013.
- D. Han, M. Heuvelmans, and M. Oudkerk, “Volume Versus Diameter Assessment of Small Pulmonary Nodules in CT Lung Cancer Screening,” Translational Lung Cancer Research, 2017.