Chromosome aberrations (CA) are associated with several genetic heredity diseases. Of concerns, prenatal diagnosis or cytogenetic screening was administered to determine if there are chromosome abnormalities, genetic diseases, or birth defects in a fetus or embryo. It is very useful to diagnose high-risk pregnancies so that delivery can be scheduled. However, conventional G-banding technique which is generally applied in CA detection for prenatal diagnosis has limit on exploit of copy number variants (CNVs) due to low resolution and tedious multiple processes. Instead, array comparative genomic hybridization (aCGH) technology enabling incremented high-resolution, even in microscale segmental CNVs, can be considered as an alternative approach for improving prenatal diagnosis. In this study, our aCGH (Illumina Infinium Human 370Quad-Duo; coverage of SNP tag and CNV regions) was used to identify copy number variations from genomic DNA in human amniotic cell specimens. The aCGH results revealed various karyotypes of CNVs including loss, homozygous loss, gain, high copy gain, and copy neutral LOH whereas using conventional G-banding only one benign cytogenetic CNV was observed in one case study. The aCGH was compatible to define small-scale chromosomal imbalances segment that were undetectable risk segment by G-banding. In contrast, abnormal G-banded karyotypes as balanced rearrangements were hidden from detection by aCGH analysis. This indicates that even though the aCGH enables us more advantage in detection of unbalanced CNVs at small-size regions with relatively high resolution, combination of both techniques is still required for efficient evaluation of various CNVs (both balanced and unbalanced ones). The aCGH also provides detailed database of copy number variant regions (CNVRs) in each chromosome. Interestingly, CNVRs containing important genes (ACADM, PPM1B, UGT2B17 and ZDHHC11) were discovered from our data, in which their defects or mutations have been reportedly to be involved in certain genetic heritable diseases and/or syndromes. Their relationships were analyzed using Pathway Studio 7.1 software to demonstrate key pathways concerning prenatal genetic defects. Respective components including protein kinases and phosphatases, transcription factors, hormones and receptors were participated in our analyzed pathway. Gathering together, our detailed CNVs and CNVR via aCGH of amniotic cells might be meaningful database to improve strategy in genetic disease-specific researches and follow- up after medication during pregnancy.