Abstract
Variation in mechanical properties is a useful marker for cancer in soft tissue and has been used in clinical diagnosis for centuries. However, to develop such methods as instrumented palpation, there remain challenges in using the mechanical response during palpation to quantify tumor load. This study proposes a computational framework of identification and quantification of cancerous nodules in soft tissue without a priori knowledge of its geometry, size, and depth. The methodology, using prostate tissue as an exemplar, is based on instrumented palpation performed at positions with various indentation depths over the surface of the relevant structure (in this case, the prostate gland). The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule. The methodology is first demonstrated using computational models and then validated using tissue-mimicking gelatin phantoms, where the depth and volume of the tumor nodule is estimated with good accuracy. The proposed framework is capable of quantifying a tumor nodule in soft tissue without a priori information about its geometry, thus presenting great promise in clinical palpation diagnosis for a wide variety of solid tumors including breast and prostate cancer.Graphical abstractThis study proposes a computational framework of quantification of cancerous nodules in soft tissue. The methodology is based on instrumental palpation performed at positions with various indentation depths. The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule.
Highlights
Highlights To propose a novel and effective computational framework to identify and quantify the tumor nodule in soft tissue, in terms of its location, size, and volume, based on mechanical measurement without a priori knowledge of its geometry. To demonstrate the clinical relevance of the proposed research and solutions in tumor quantification—the need of noninvasiveness using primary diagnostic approaches. To validate such a methodology using tissue-mimicking phantoms, which demonstrate the effectiveness and the sensitivity of the proposed method in clinical applications.Electronic supplementary material The online version of this article contains supplementary material, which is available to authorized users.Determining the size and location of a tumor nodule in soft tissue is critical
This study presents a novel diagnostic framework using palpation to determine both the size and depth of an anomaly without a priori knowledge of its location or geometry, providing a relatively non-invasive, quantitative tool for early detection, and characterization of tumor nodules
There is a need for a quantitative strategy in determining the depth and size of cancerous nodules in soft tissue, e.g., prostate, using instrumented palpation for clinical application of nodule identification and characterization
Summary
Determining the size and location of a tumor nodule in soft tissue is critical. This should occur at the earliest possible stage, giving the best chance of determining the optimal treatment improving patient outcomes. Characterizing cancer, even with the aid of conventional biopsy remains a non-trivial task, for primary diagnosis Imaging techniques such as magnetic resonance imaging (MRI) have proven useful in detecting pathological conditions such as neoplasms [1], and sonoelastography has been widely used in clinical diagnosis for such tissues as breast [2] and liver [3]. Such techniques allow maps of relative tissue density or stiffness, diagnosis still remains challenging in certain scenarios such as co-occurrence of benign prostate hyperplasia [4] or tumors located deeply from a measurable surface [5]
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