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Quantitative image reconstruction in dual-energy computed tomography (CT)remains a topic of active research. We read with interest ``DIRECT-Net: Aunified mutual-domain material decomposition network for quantitativedual-energy CT imaging,'' which appears in the 2022 February Issue of Med Phys.In the paper the authors propose a deep-learning (DL) method, referred to asthe Direct-Net method, to address the problem of quantitative imagereconstruction directly from data in full-scan dual-energy CT (DECT). Wecomment on the study and conclusion in the paper. The Reply to this commentappears under Communications on medphys.org:https://www.medphys.org/Communications/Reply-Pan_Response-Su.pdf In order tohave context for the Reply, we provide the full text of our Comments.

Comments on "DIRECT-Net: A unified mutual-domain material decomposition  network for quantitative dual-energy CT Imaging'', Med. Phys. 2022, Vol. 49,  pgs. 917-934