Motivation: Quantitative information on tumor heterogeneity and cell load could assist in designing effective and refined personalized treatment strategies. It was recently shown by us that such information can be inferred from the diffusion parameter D derived from the diffusion-weighted MRI (DWI) if a relation between D and cell density can be established. However, such relation cannot a priori be assumed to be constant for all patients and tumor types. Hence to assist in clinical decisions in palliative settings, the relation needs to be established without tumor resection. It is here demonstrated that biopsies may contain sufficient information for this purpose if the localization of biopsies is chosen as systematically elaborated in this paper. Methods: The cell density is analyzed in virtual biopsies from the histological tissue images of the same solid tumor for which previously large tissue samples are studied. This permits studying the impact of biopsy location and validating our findings in virtual biopsies by direct comparisons with large tumor samples. A superpixel-based method for automated optimal localization of biopsies from the DWI D-map is proposed. The performance of the DWI-guided procedure is evaluated by extensive simulations of biopsy needle paths. The method is by construction patient-specific, not requiring prior calibration curves to relate DW-images to cell density. Results: Needle biopsies yield sufficient histological information to establish a quantitative relationship between D-value and cell density, and to investigate tumor cellularity and heterogeneity, provided they are taken from regions with high, intermediate, and low D-value in DWI. The automated localization of the biopsy regions is demonstrated from a NSCLC (non-small cell lung cancer) patient tumor. In this case, even two or three biopsies give a reasonable estimate. Simulations of needle biopsies under different conditions indicate that the DWI-guidance highly improves the estimation results. Conclusion: Tumor cellularity and heterogeneity in solid tumors may be reliably investigated from DWI and a few needle biopsies that are sampled in regions of well-separated D-values, excluding adipose tissue. This procedure could provide a way of embedding in the clinical workflow assistance in cancer diagnosis and treatment based on personalized information.