Apparatus for evaluating whether a patient is likely to have a favorable pathological stage of prostate cancer, the apparatus comprising: (a) a fluorescence imaging device configured to record at least one sample image of a tissue sample of a patient, the tissue sample treated with a plurality of fluorochrome labeled antibodies, wherein the antibodies are selected to bind with at least AR and Ki67; (b) a database configured to store patient data including clinical feature data values for the patient comprising a value indicative of the biopsy Gleason score (bGS) and biopsy Gleason grade (bGG) of the patient and a value indicative of the level of Prostate Specific Antigen in the blood of the patient; and (c) a processor configured to: (i) evaluate the at least one sample image recorded by the imaging device and generate: one or more molecular feature values indicative of a combined AR dynamic range where the measured bGG values is ≤ 3, and a total Ki67 where the measured bGG value is ≥ 4, and a plurality of morphometric measurements, including: (i) a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units; and (ii) an area of epithelial nuclei distributed away from gland units; (ii) combine the molecular feature values, morphometric measurements and clinical feature data values into the database; (iii) evaluate the patient data with a predictive model configured to output a value based on the evaluated features; and (iv) assign the patient to a low risk of cancer occurrence category where the output value is below a predetermined threshold and assign the patient to a high-risk category where the output value is above the pre-determined threshold. (a) a fluorescence imaging device configured to record at least one sample image of a tissue sample of a patient, the tissue sample treated with a plurality of fluorochrome labeled antibodies, wherein the antibodies are selected to bind with at least AR and Ki67; (b) a database configured to store patient data including clinical feature data values for the patient comprising a value indicative of the biopsy Gleason score (bGS) and biopsy Gleason grade (bGG) of the patient and a value indicative of the level of Prostate Specific Antigen in the blood of the patient; and (c) a processor configured to: (i) evaluate the at least one sample image recorded by the imaging device and generate: one or more molecular feature values indicative of a combined AR dynamic range where the measured bGG values is ≤ 3, and a total Ki67 where the measured bGG value is ≥ 4, and a plurality of morphometric measurements, including: (i) a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units; and (ii) an area of epithelial nuclei distributed away from gland units; (ii) combine the molecular feature values, morphometric measurements and clinical feature data values into the database; (iii) evaluate the patient data with a predictive model configured to output a value based on the evaluated features; and (iv) assign the patient to a low risk of cancer occurrence category where the output value is below a predetermined threshold and assign the patient to a high-risk category where the output value is above the pre-determined threshold. (i) evaluate the at least one sample image recorded by the imaging device and generate: one or more molecular feature values indicative of a combined AR dynamic range where the measured bGG values is ≤ 3, and a total Ki67 where the measured bGG value is ≥ 4, and a plurality of morphometric measurements, including: (i) a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units; and (ii) an area of epithelial nuclei distributed away from gland units; one or more molecular feature values indicative of a combined AR dynamic range where the measured bGG values is ≤ 3, and a total Ki67 where the measured bGG value is ≥ 4, and a plurality of morphometric measurements, including: (i) a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units; and (ii) an area of epithelial nuclei distributed away from gland units; (ii) combine the molecular feature values, morphometric measurements and clinical feature data values into the database; (iii) evaluate the patient data with a predictive model configured to output a value based on the evaluated features; and (iv) assign the patient to a low risk of cancer occurrence category where the output value is below a predetermined threshold and assign the patient to a high-risk category where the output value is above the pre-determined threshold.