Cancer is a complex category of diseases that requires the use of highly specific treatment protocols depending on stage and presentation. The early detection of tumours allows oncologists to select the most appropriate treatment regimen, and provides a proven survival benefit. Early detection is also critical in establishing if a primary tumour has metastasised and spread to other parts of the body, in which case a patient may require more aggressive therapy.

Patients with early stage, localised cancers are generally more likely to survive the disease than those whose primary tumours have already spread by the time the cancer is detected. After establishing a diagnosis, physicians must closely monitor disease progression in order to accurately determine if their patients are responding to therapy. Tracking changes in tumour volume over time can provide physicians with a discrete and trustworthy metric of cancer progression.

Malignant cancer cells are unique in their ability to penetrate the walls of lymph and blood vessels, allowing them to circulate throughout the body and spread to distant tissues. Tumours that spread far from the primary site to other organs or to the lymph nodes are referred to as metastatic cancers. The extent of metastatic infiltration significantly affects disease prognosis; predictions of patient survival and their therapeutic options can be severely limited in instances of advanced metastatic cancer.

“The early detection of tumours allows oncologists to select the most appropriate treatment regimen.”

The metabolic processes and biophysical changes within the lymph nodes often give physicians insight into the health of their patients, and in the case of cancer, serve as powerful indicators of disease progression.

The lymph nodes, which filter foreign particles throughout the body, are a primary site of metastatic spread for almost all malignant tumours. Cancer cells tend to cluster inside lymph nodes, allowing them to spread throughout the body, and often can be found within lymphatic tissue before metastases have developed elsewhere. The analysis of the lymph nodes is therefore vital to identifying the spread of cancer cells from a primary tumour.

However, lymph nodes are notoriously difficult to analyse. These small glands are distributed throughout the body in a multitude of cellular environments. Identifying changes in lymph nodes over time can be a technically challenging and labour-intensive process. Traditionally, radiologists have relied on the visual inspecnd CT represent three-dimensional objects as very large datasets of two dimensional images. To effectively analyse lymph nodes in a patient, large volumes of images must be visually inspected, and multiple layers of images are used to understand changes in the volume and shape of a lymph node in three dimensions. This process can be extremely time-consuming and expensive.

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In analysing lymph nodes and their associated lesions, radiologists rely on a set of clinical guidelines based on comparing two-dimensional measurements over time. Introduced in 2000, the Response Evaluation Criteria in Solid Tumours (RECIST) supplanted older World Health Organisation (WHO) guidelines developed in the late 1970s.

Whereas WHO guidelines were criticised for being overly complex and required the radiologist to apply a complicated mathematical formula, the original RECIST guidelines were based on measurements of only the longest diameter of a lymph node or lesion. In 2009 these guidelines were adapted into RECIST 1.1 because of a consensus among experts that measurements of the short axis of the lymph node are more reproducible and more predictive of malignancy. Although the clinical guidelines to assess lymph nodes have changed over time, they have relied upon manual measurement and assessment, and are therefore saddled with the possibility of human error.

“Malignant cancer cells are unique in their ability to penetrate the walls of lymph and blood vessels.”

Clinical guidelines are also problematic because they fail to account for the three-dimensional nature of human anatomy. Lymph nodes can grow or shrink in multiple planes, so forming diagnoses based on the measurement of a single axis is insufficient to fully understand how they are changing over time. Manual measurement and analysis may lack the sensitivity and speed required to detect very small changes in size.

Recent research has supported the use of computer-aided volumetric analysis to provide a more complete and accurate assessment of changes in lymph nodes and associated lesions over time. Figure 1 shows images of a patient examined at two different points in time.

The baseline scan on the left was taken at an earlier point in the patient’s treatment protocol, and the follow-up scan on the right was taken approximately six weeks later.

Whereas the perpendicular diameter shows only a modest change during this time period, the volumetric analysis reveals a significant shrinking of the node. The shortest perpendicular diameter, measured according to RECIST 1.1, decreased by 7% in this time period, from 8.8 to 8.2mm. However, the volume of this lymph node shrank from 3,000 to 1,107mm³, a decrease of 64%. A comparison of these two images shows that the use of volumetric computer-aided analysis provides a more accurate and complete picture than RECIST.

Volumetric analysis enables oncologists to more closely follow a patient’s response to therapy, and more rapidly implement the most effective treatments. Until recently, it has been a major challenge to track changes in individual lesions for patients with multiple metastases. Just as important, this technology supports the development of more personalised treatment strategies, and could also lead to reduced costs by allowing oncologists to discontinue unsuccessful treatments earlier in the treatment process.

Fully automated analysis

Beyond oncology, the insights gained from computer-aided volumetric analysis could make pharmaceutical development more responsive and cost effective. A recently conducted study established that volumetric analysis is an effective method of measuring the efficacy of experimental compounds. The ability to more quickly determine the efficacy of a compound shortens clinical trials, moves the development process forward and provides substantial cost savings for the pharmaceutical and biotech industries.

“The analysis of the lymph nodes is vital to identifying the spread of cancer cells from a primary tumour.”

In May 2008, an interdisciplinary group of industry leaders formed the Quantitative Imaging Biomarkers Alliance (QIBA), sponsored by the Radiological Society of North America, to identify unmet needs and barriers to the adoption of new imaging technologies. The group also aims to develop and test reliable and validated quantitative imaging results. The alliance supports the implementation of volumetric analysis in the treatment of cancer and aims to establish a consensus on recommendations for more effective analysis tools and procedures for image analysis. To that end, the QIBA plans to integrate volumetric measurements into RECIST guidelines, supplanting two-dimensional measurement techniques.

The majority of software tools available for analysing lymph nodes and associated lesions utilise semi-automated protocols, meaning that radiologists must still visually inspect objects before the software takes over the process. The further development and broad adoption of fully-automated lymph node analysis software should be expected in the coming years, as this technology has been shown to eliminate reader-bias and deliver highly accurate and reproducible results. The use of semi and fully-automated software tools enables oncologists to provide superior care and will help pharmaceutical developers bring promising compounds to the market sooner.