Abstract: A computer-implemented method for determining and evaluating an objective tumor response to an anti-cancer therapy using cross-sectional images can include receiving cross-sectional images of digital medical image data and identifying target lesions within the cross-sectional images. For each of the target lesions, a target lesion type and anatomical location is identified, a segmenting tool is activated for segmenting the target lesions into regions of interest, lesion metrics are automatically extracted from the regions of interest according to tumor response criteria, and conformity of target lesion identification is monitored using rules associated with the tumor response criteria, prompting a user to address any nonconforming target lesion. The method also includes receiving a presence/absence of metastases, determining changes in lesions metrics, and deriving an objective tumor response based on the tumor response criteria.

Abstract: Systems and methods for standardizing target lesion selection within cross-sectional medical images can include the acts of: (i) sending a plurality of cross-sectional images to a user device, where each cross-sectional image is a cross-sectional slice of digital medical image data captured at a first timepoint from a radiologic device; (ii) receiving a user input identifying a set of pixels corresponding to a target lesion within a cross-sectional image of the plurality of cross-sectional images; and (iii) generating a target lesion location file that includes a precise anatomical location of the cross-sectional image and a pixel location of the target lesion within the cross-sectional image. The systems and methods can additionally include the act of causing a digital marker to be displayed on the cross-sectional image and on each analogous cross-sectional image captured at a later timepoint.

Abstract: A computerized method for determining an objective tumor response to an anti-cancer therapy using cross-sectional images includes receiving a cross-sectional image of digital medical image data, identifying a set of pixels within the cross-sectional image corresponding to a target lesion, and analyzing the set of pixels with an image processing module to identify an upper and lower threshold of pixel intensities within a total range of pixel intensities, define a subset of pixels from the set of pixels that correspond to vascularized tumor and that have pixel intensities greater than or equal to the lower threshold and lower than or equal to the upper threshold, and derive a vascular tumor burden for the set of pixels. The method further includes determining the objective tumor response for the target lesion, wherein the objective tumor response is based on the vascular tumor burden.

Abstract: A computerized method for determining an objective tumor response to an anti-cancer therapy using one or more cross-sectional images can comprise receiving one or more cross-sectional images that comprise one or more cross-sectional slices of digital medical image data and identifying one or more target lesions within the one or more cross-sectional images. The method can also comprise analyzing at least one of the target lesions with an image-processing module configured to identify a total range of pixel intensities and restrict the total range of pixel intensities to a first restricted range that corresponds to pixel intensities representative of vascularized tumor. Further still, the method can comprise deriving a vascular tumor burden for the at least one of the one or more target lesions and determining the objective tumor response for the at least one of the one or more target lesions based on the vascular tumor burden.