Computed tomography perfusion (CTP) method and apparatus using blood flow for discriminating types of cancer
Inventors
Mensah, Eugene A. • BREWINGTON, Cecelia • ANGEL, Erin • ARBIQUE, Gary • NORDECK, Shaun
Assignees
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Publication Number
US-10363008-B2
Publication Date
2019-07-30
Expiration Date
Abstract
Computed tomography perfusion (CTP) is used in a method to identify cancerous lesions having genetic mutations and treat them accordingly. Also, CTP values are used to distinguish primary versus metastatic lesions. For example, pulmonary blood flow is identified as one biomarker for EGFR and KRAS genetic mutations in lung cancer, lesion having dual-input pulmonary blood flow exceeding a threshold (e.g., 103 ml/min/100 mL with sensitivity 100% and specificity 62%) are determined as having mutations. The CTP values are calculated using a lesion region-of-interest (ROI) placed to include the area of maximum perfusion intensity within the lesion base and surrounding blush, while avoiding regions of perfusion inhomogeneity (e.g., due to necrosis). In certain implementations, instead of a binary determination, the method can generate probabilities associated with respective alternatives (e.g., mutation/non-nutation and/or primary/secondary), and the method can use multivariable statistical analysis that incorporates patient and/or medical information in addition to CTP values.
Core Innovation
The disclosure provides computed tomography perfusion (CTP) image-based identification and classification of a pulmonary lesion by extracting perfusion-related CTP values from a region of interest (ROI) within the lesion and then classifying whether the pulmonary lesion has a genetic mutation. The classification uses one or more predefined thresholds corresponding respectively to one or more of the CTP values, so that CTP values representing perfusion in the ROI are used to make a mutation-related determination for the pulmonary lesion.
The approach addresses the problem of determining a treatment for a pulmonary lesion by using non-invasive CTP-derived information related to blood flow in a lung region that includes the pulmonary lesion. Background content in the provided material indicates a need to non-invasively identify lung lesions with genetic mutations and to discriminate primary versus metastatic lesions, using CTP dual-input pulmonary blood flow as a biomarker.
In embodiments, the ROI of the pulmonary lesion is identified using the CTP image with attention to perfusion characteristics such as blood-flow uniformity and selection of a region of maximum blood flow, including determining that blood-flow in the volume is uniform when blood-flow variability meets a predefined variability criterion. The disclosure also supports classification refinements that include estimating a probability that the pulmonary lesion has the genetic mutation and using multivariable statistical or machine learning approaches to discriminate based on CTP values and additional patient- and image-derived inputs.
Claims Coverage
The independent claims provided are clm-00001, clm-00014, and clm-00025. Across these independent claims, three main inventive feature groups are covered: CTP-based ROI extraction and CTP value determination, threshold-based genetic-mutation classification for lesions, and CT perfusion apparatus structures configured to perform the same CTP workflow, with additional dependent refinements including uniform-blood-flow ROI selection and probabilistic or multivariable classification.
Threshold-based genetic-mutation classification using CTP values from a lesion ROI
obtaining a computed tomography perfusion (CTP) image representing blood flow in a region of a lung that includes the pulmonary lesion; identifying, using the CTP image, a region of interest (ROI) of the pulmonary lesion; determining, using the ROI and the CTP image, CTP values representing perfusion in the ROI of the lesion; classifying the pulmonary lesion according to whether the pulmonary lesion has a genetic mutation based on the CTP values and using one or more predefined thresholds corresponding respectively to one or more of the CTP values.
CTP apparatus configured for pre/post contrast projection data to perform mutation classification
an X-ray source fixed to the annular rotating member and configured to emit a beam of X-rays; an X-ray detector fixed to the annular rotating member and configured across the central opening diametrically opposed to the X-ray source, the X-ray detector including a plurality of detector elements arranged to detect the X-rays and generate projection data representing an intensity of the X-rays detected at the plurality of detector elements; processing circuitry configured to obtain CTP projection data that is the projection data obtained by computed tomography (CT) scans of a lung region of the cancer patient before and after an injection of a contrast agent, generate, using the CTP projection data, a computed tomography perfusion (CTP) image representing blood flow in the lung region, which includes a pulmonary lesion, identify, using the CTP image, a region of interest (ROI) of the pulmonary lesion, determine, using the ROI and the CTP image, CTP values representing perfusion in the ROI of the lesion, and classify the pulmonary lesion according to whether the pulmonary lesion has a genetic mutation based on the CTP values and using one or more predefined thresholds corresponding respectively to one or more of the CTP values.
Uniform blood-flow ROI selection with maximum blood flow for CTP-based mutation classification
obtaining a computed tomography perfusion (CTP) image representing blood flow in a region of a patient that includes the lesion; selecting, using the CTP image, within the lesion and surrounding blush a region of uniform blood flow including a maximum blood flow to generate a region of interest (ROI) of the lesion; determining, using the ROI of the lesion and the CTP image, CTP values representing perfusion in the ROI of the lesion; classifying, using the CTP values, the lesion according to whether the lesion has a genetic mutation.
The independent claims collectively cover using CTP to generate a lesion ROI, determine CTP values representing perfusion within that ROI, and classify whether the lesion has a genetic mutation using predefined thresholds; additionally, an apparatus claim specifies an annular rotating CT hardware arrangement and processing circuitry that obtains pre/post contrast CT projection data and generates a CTP image used to perform the ROI extraction and threshold-based mutation classification.
Stated Advantages
Non-invasively identifying lung lesions with genetic mutations using computed tomography perfusion.
Discriminating primary versus metastatic lesions using CTP dual-input pulmonary blood flow as a biomarker.
Enabling treatment determination for a pulmonary lesion based on CTP-derived classification of genetic mutation status.
Documented Applications
Using computed tomography perfusion (CTP) to determine a treatment of a pulmonary lesion based on whether the pulmonary lesion has a genetic mutation.
Discriminating primary versus metastatic lesions using CTP dual-input pulmonary blood flow as a biomarker.
Classifying a lesion (including a pulmonary lesion) according to genetic mutation status derived from CTP values, including embodiments that produce a mutation probability and may support recommending additional testing and treatment tailoring [procedural detail omitted for safety].
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